R Abbott

T D Abbott

F Acernese

K Ackley

C Adams

N Adhikari

R X Adhikari

V B Adya

C Affeldt

D Agarwal

M Agathos

K Agatsuma

N Aggarwal

O D Aguiar

L Aiello

A Ain

P Ajith

S Albanesi

A Allocca

P A Altin

A Amato

C Anand

S Anand

A Ananyeva

S B Anderson

W G Anderson

T Andrade

N Andres

T Andrić

S V Angelova

S Ansoldi

J M Antelis

S Antier

S Appert

K Arai

M C Araya

J S Areeda

M Arène

N Arnaud

S M Aronson

K G Arun

Y Asali

G Ashton

M Assiduo

S M Aston

P Astone

F Aubin

C Austin

S Babak

F Badaracco

M K M Bader

C Badger

S Bae

A M Baer

S Bagnasco

Y Bai

J Baird

M Ball

G Ballardin

S W Ballmer

A Balsamo

G Baltus

S Banagiri

D Bankar

J C Barayoga

C Barbieri

B C Barish

D Barker

P Barneo

F Barone

B Barr

L Barsotti

M Barsuglia

D Barta

J Bartlett

M A Barton

I Bartos

R Bassiri

A Basti

M Bawaj

J C Bayley

A C Baylor

M Bazzan

B Bécsy

V M Bedakihale

M Bejger

I Belahcene

V Benedetto

D Beniwal

T F Bennett

J D Bentley

M Benyaala

F Bergamin

B K Berger

S Bernuzzi

C P L Berry

D Bersanetti

A Bertolini

J Betzwieser

D Beveridge

R Bhandare

U Bhardwaj

D Bhattacharjee

S Bhaumik

I A Bilenko

G Billingsley

S Bini

R Birney

O Birnholtz

S Biscans

M Bischi

S Biscoveanu

A Bisht

B Biswas

M Bitossi

M.-A Bizouard

J K Blackburn

C D Blair

D G Blair

R M Blair

F Bobba

N Bode

M Boer

G Bogaert

M Boldrini

L D Bonavena

F Bondu

E Bonilla

R Bonnand

P Booker

B A Boom

R Bork

V Boschi

N Bose

S Bose

V Bossilkov

V Boudart

Y Bouffanais

A Bozzi

C Bradaschia

P R Brady

A Bramley

A Branch

M Branchesi

J E Brau

M Breschi

T Briant

J H Briggs

A Brillet

M Brinkmann

P Brockill

A F Brooks

J Brooks

D D Brown

S Brunett

G Bruno

R Bruntz

J Bryant

T Bulik

H J Bulten

A Buonanno

R Buscicchio

D Buskulic

C Buy

R L Byer

L Cadonati

G Cagnoli

C Cahillane

J Calderón Bustillo

J D Callaghan

T A Callister

E Calloni

J Cameron

J B Camp

M Canepa

S Canevarolo

M Cannavacciuolo

K C Cannon

H Cao

E Capote

G Carapella

F Carbognani

J B Carlin

M F Carney

M Carpinelli

G Carrillo

G Carullo

T L Carver

J Casanueva Diaz

C Casentini

G Castaldi

S Caudill

M Cavaglià

F Cavalier

R Cavalieri

M Ceasar

G Cella

P Cerdá-Durán

E Cesarini

W Chaibi

K Chakravarti

S Chalathadka Subrahmanya

E Champion

C.-H L Chan

K Chan

K Chandra

P Chanial

S Chao

P Charlton

E A Chase

E Chassande-Mottin

C Chatterjee

Debarati Chatterjee

Deep Chatterjee

D Chattopadhyay

M Chaturvedi

S Chaty

K Chatziioannou

H Y Chen

J Chen

X Chen

Y Chen

Z Chen

H Cheng

C K Cheong

H Y Cheung

H Y Chia

F Chiadini

G Chiarini

R Chierici

A Chincarini

M L Chiofalo

A Chiummo

G Cho

H S Cho

R K Choudhary

S Choudhary

N Christensen

Q Chu

S Chua

K W Chung

G Ciani

P Ciecielag

M Cieślar

M Cifaldi

A A Ciobanu

R Ciolfi

F Cipriano

A Cirone

F Clara

E N Clark

J A Clark

L Clarke

P Clearwater

S Clesse

F Cleva

E Coccia

E Codazzo

P.-F Cohadon

D E Cohen

L Cohen

M Colleoni

C G Collette

A Colombo

M Colpi

C M Compton

M Constancio

L Conti

S J Cooper

P Corban

T R Corbitt

I Cordero-Carrión

S Corezzi

K R Corley

N Cornish

D Corre

A Corsi

S Cortese

C A Costa

R Cotesta

M W Coughlin

J.-P Coulon

S T Countryman

B Cousins

P Couvares

D M Coward

M J Cowart

D C Coyne

R Coyne

J D E Creighton

T D Creighton

A W Criswell

M Croquette

S G Crowder

J R Cudell

T J Cullen

A Cumming

R Cummings

L Cunningham

E Cuoco

M Cury

P Dabadie

T Dal Canton

S Dall'osso

G Dálya

A Dana

L M Daneshgaranbajastani

B D'angelo

B Danila

S Danilishin

S D'antonio

K Danzmann

C Darsow-Fromm

A Dasgupta

L E H Datrier

S Datta

V Dattilo

I Dave

M Davier

G S Davies

D Davis

M C Davis

E J Daw

R Dean

D Debra

M Deenadayalan

J Degallaix

M De Laurentis

S Deléglise

V Del Favero

F De Lillo

N De Lillo

W Del Pozzo

L M Demarchi

F De Matteis

V D'emilio

N Demos

T Dent

A Depasse

R De Pietri

R De Rosa

C De Rossi

R Desalvo

R De Simone

S Dhurandhar

M C Díaz

M Diaz-Ortiz

N A Didio

T Dietrich

L Di Fiore

C Di Fronzo

C Di Giorgio

F Di Giovanni

M Di Giovanni

T Di Girolamo

A Di Lieto

B Ding

S Di Pace

I Di Palma

F Di Renzo

A K Divakarla

Divyajyoti

A Dmitriev

Z Doctor

L D'onofrio

F Donovan

K L Dooley

S Doravari

I Dorrington

M Drago

J C Driggers

Y Drori

J.-G Ducoin

P Dupej

O Durante

D D'urso

P.-A Duverne

S E Dwyer

C Eassa

P J Easter

M Ebersold

T Eckhardt

G Eddolls

B Edelman

T B Edo

O Edy

A Effler

J Eichholz

S S Eikenberry

M Eisenmann

R A Eisenstein

A Ejlli

E Engelby

L Errico

R C Essick

H Estellés

D Estevez

Z Etienne

T Etzel

M Evans

T M Evans

B E Ewing

V Fafone

H Fair

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S P Fanning

A M Farah

S Farinon

B Farr

W M Farr

N W Farrow

E J Fauchon-Jones

G Favaro

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M M Fejer

E Fenyvesi

D L Ferguson

A Fernandez-Galiana

I Ferrante

T A Ferreira

F Fidecaro

P Figura

I Fiori

M Fishbach

R P Fisher

R Fittipaldi

V Fiumara

R Flaminio

E Floden

H Fong

J A Font

B Fornal

P W F Forsyth

A Franke

S Frasca

F Frasconi

C Frederick

J P Freed

Z Frei

A Freise

R Frey

P Fritschel

Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run

GWTC-

2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run R Abbott, T.

The second Gravitational-Wave Transient Catalog, GWTC-2, reported on 39 compact binary coalescences observed by the Advanced LIGO and Advanced Virgo detectors between 1 April 2019 15:00 UTC and 1 October 2019 15:00 UTC. Here, we present GWTC-2.1, which reports on a deeper list of candidate events observed over the same period. We analyze the final version of the strain data over this period with improved calibration and better subtraction of excess noise, which has been publicly released. We employ three matched-filter search pipelines for candidate identification, and estimate the probability of astrophysical origin for each candidate event. While GWTC-2 used a false alarm rate threshold of 2 per year, we include in GWTC-2.1, 1201 candidates that pass a false alarm rate threshold of 2 per day. We calculate the source properties of a subset of 44 high-significance candidates that have a probability of astrophysical origin greater than 0.5. Of these candidates, 36 have been reported in GWTC-2. We also calculate updated source properties for all binary block hole events previously reported in GWTC-1. If the 8 additional high-significance candidates presented here are astrophysical, the mass range of events that are unambiguously identified as binary black holes (both objects ≥ 3M ) is increased compared to GWTC-2, with total masses from I. INTRODUCTION We are in the era of gravitational wave (GW) astronomy, started by the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) [START_REF] Aasi | Advanced LIGO[END_REF] and the Advanced Virgo [START_REF] Acernese | Advanced Virgo: a second-generation interferometric gravitational wave detector[END_REF] detectors. The first observing run (O1) of the advanced detectors yielded the first detection of GWs from a binary black hole (BBH), GW150914 [START_REF] Abbott | Observation of Gravitational Waves from a Binary Black Hole Merger[END_REF]. By the end of O1, the LIGO Scientific and Virgo Collaboration (LVC) had reported on three BBH events [START_REF] Abbott | Binary Black Hole Mergers in the first Advanced LIGO Observing Run[END_REF]. The second observing run (O2) of the advanced detectors saw the first direct detection of GWs from a binary neutron star (BNS), GW170817 [START_REF] Abbott | GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral[END_REF]. This event was also detected in electromagnetic waves [START_REF] Abbott | Ice-Cube, AstroSat Cadmium Zinc Telluride Imager Team, IPN, Insight-Hxmt[END_REF], expanding the field of multimessenger astronomy to include GWs. By the end of O2, the LVC had reported on a total of ten BBHs and one BNS event, described in the first Gravitational-Wave Transient Catalog, GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF]. The second Gravitational-Wave Transient Catalog, GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], added 39 GW events from the first half of the third observing run (O3a), and included a total of 50 events. The GW data until the end of third observing run (O3) have been made available to the public by the LVC. Since the public release of the LIGO and Virgo data, groups other than the LVC have also performed analyses searching for GW signals [START_REF] Nitz | 1-OGC: The first open gravitationalwave catalog of binary mergers from analysis of public Advanced LIGO data[END_REF][START_REF] Magee | Sub-threshold Binary Neutron Star Search in Advanced LIGO's First Observing Run[END_REF][START_REF] Venumadhav | New search pipeline for compact binary mergers: Results for binary black holes in the first observing run of Advanced LIGO[END_REF][START_REF] Zackay | Highly spinning and aligned binary black hole merger in the Advanced LIGO first observing run[END_REF][START_REF] Venumadhav | New binary black hole mergers in the second observing run of Advanced LIGO and Advanced Virgo[END_REF][START_REF] Nitz | 2-OGC: Open Gravitational-wave Catalog of binary mergers from analysis of public Advanced LIGO and Virgo data[END_REF][START_REF] Zackay | Detecting gravitational waves with disparate detector responses: Two new binary black hole mergers[END_REF][START_REF] Harvey | Search for Gravitational Waves from High-Mass-Ratio Compact-Binary Mergers of Stellar Mass and Subsolar Mass Black Holes[END_REF][START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF][START_REF] Nitz | Search for Gravitational Waves from the Coalescence of Subsolar-Mass Binaries in the First Half of Advanced LIGO and Virgo's Third Observing Run[END_REF][START_REF] Nitz | 4-OGC: Catalog of gravitational waves from compact-binary mergers[END_REF][START_REF] Olsen | New binary black hole mergers in the LIGO-Virgo O3a data[END_REF][START_REF] Nitz | Broad search for gravitational waves from subsolar-mass binaries through LIGO and Virgo's third observing run[END_REF] and reported additional candidate events in some cases.

GW events between 1 April 2019 15:00 UTC and 1 October 2019 15:00 UTC (O3a) that passed a false alarm rate (FAR) threshold of 2 per year were presented in GWTC-2. Here, we present GWTC-2.1, a deep catalog that includes 1201 candidates passing a low-significance FAR threshold of 2 per day. Although most of the candidates in this catalog are noise events, they can be used for multimessenger searches by comparing against other astronomical surveys. Temporal and spatial coincidences between candidates in distinct astrophysical channels could lead to multimessenger discoveries [START_REF] Smith | The astrophysical multimessenger observatory network (amon)[END_REF][START_REF] Burns | A Fermi Gamma-ray Burst Monitor Search for Electromagnetic Signals Coincident with Gravitational-Wave Candidates in Advanced LIGO's First Observing Run[END_REF]. Multimessenger observations could enhance our understanding of the physical processes associated with such systems. Previous GW searches, both from the LVC [START_REF]Trigger Data to Accompany "GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF] and independent groups [START_REF] Magee | Sub-threshold Binary Neutron Star Search in Advanced LIGO's First Observing Run[END_REF][START_REF] Venumadhav | New binary black hole mergers in the second observing run of Advanced LIGO and Advanced Virgo[END_REF][START_REF] Nitz | 2-OGC: Open Gravitational-wave Catalog of binary mergers from analysis of public Advanced LIGO and Virgo data[END_REF][START_REF]Trigger Data to Accompany "GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Nitz | Potential Gravitational-wave and Gammaray Multi-messenger Candidate from 2015 October 30[END_REF], including the 3-OGC analysis of public data from O1 to O3a [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF], have released subthreshold candidates. It is computationally a Deceased, August 2020.

unfeasible to determine detailed source properties of the large set of subthreshold GW candidates, therefore we identify a subset of compact binary coalescence (CBC) candidates that have a probability of astrophysical origin p astro [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF][START_REF] Abbott | The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF][START_REF] Abbott | Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF] greater than 0.5, and calculate the source properties of these events. This probability p astro uses both the signal rate in addition to the noise rate in order to determine the significance of events. There are 44 such candidate events, 36 of which have already been reported in GWTC-2 and their source properties have been described in detail [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. We present the source properties with a consistent set of state-of-the-art waveform models for all of these candidates, discussing the properties of the 8 new events that have a p astro greater than 0.5 in detail in the body of the paper, and our results for the previously reported candidates in Appendix A. A subset of the 8 additional events have been found in the LVC search of O3a data [START_REF] Abbott | Search for Lensing Signatures in the Gravitational-Wave Observations from the First Half of LIGO-Virgo's Third Observing Run[END_REF] for faint gravitationally lensed counterpart images [START_REF] Alvin | Finding diamonds in the rough: Targeted Subthreshold Search for Strongly-lensed Gravitational-wave Events[END_REF][START_REF] Mcisaac | Search for strongly lensed counterpart images of binary black hole mergers in the first two LIGO observing runs[END_REF], and in the independent 3-OGC [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF] analysis. While the 8 new events presented here have a non-negligible probability of being from noise, some of these have astrophysically interesting source properties under the default prior. Two of the new candidates presented here have a primary component mass in the pair instability gap [START_REF] Woosley | Pulsational Pair-instability Supernovae[END_REF][START_REF] Woosley | The Evolution of Massive Helium Stars, Including Mass Loss[END_REF][START_REF] Stevenson | The Impact of Pair-instability Mass Loss on the Binary Black Hole Mass Distribution[END_REF][START_REF] Farmer | Mind the Gap: The Location of the Lower Edge of the Pair-instability Supernova Black Hole Mass Gap[END_REF][START_REF] Farmer | Constraints from Gravitationalwave Detections of Binary Black Hole Mergers on the 12 C(α, γ) 16 O Rate[END_REF][START_REF] Mapelli | Impact of the Rotation and Compactness of Progenitors on the Mass of Black Holes[END_REF][START_REF] Marchant | The impact of stellar rotation on the black hole mass-gap from pairinstability supernovae[END_REF][START_REF] Costa | Formation of GW190521 from stellar evolution: the impact of the hydrogen-rich envelope, dredge-up, and 12 C(α, γ) 16 O rate on the pair-instability black hole mass gap[END_REF][START_REF] Farrell | Is GW190521 the merger of black holes from the first stellar generations?[END_REF], and one of those shows support for high spin and unequal masses. We also find a new candidate whose masses are consistent with a neutron star-black hole binary (NSBH), although as in the case of GW190814 [START_REF] Abbott | GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object[END_REF], we cannot rule out the possibility that the secondary component of the candidate could be a low-mass black hole.

In this work, all the analyses make use of the final version of the strain data with improved calibration and noise subtraction, which includes non-linear subtraction around the 60 Hz frequency of the US power grid [START_REF] Vajente | Machine-learning nonstationary noise out of gravitational-wave detectors[END_REF][START_REF] Tiwari | Regression of Environmental Noise in LIGO Data[END_REF]. The data used in this work have been released to the public [START_REF]The o3a data release[END_REF][START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Data Quality Products for GW Searches[END_REF][START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Glitch modelling for events[END_REF]. We use three matched-filter pipelines for candidate identification: GstLAL [START_REF] Sachdev | The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs[END_REF][START_REF] Hanna | Fast evaluation of multi-detector consistency for real-time gravitational wave searches[END_REF][START_REF] Messick | Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data[END_REF], PyCBC [START_REF] Allen | FIND-CHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries[END_REF][START_REF] Allen | χ 2 time-frequency discriminator for gravitational wave detection[END_REF][START_REF] Dal | Implementing a search for aligned-spin neutron star-black hole systems with advanced ground based gravitational wave detectors[END_REF][START_REF] Usman | The PyCBC search for gravitational waves from compact binary coalescence[END_REF][START_REF] Nitz | Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search[END_REF], and MBTA [START_REF] Aubin | The MBTA pipeline for detecting compact binary coalescences in the third LIGO-Virgo observing run[END_REF]. MBTA is reporting results from an archival search for the first time. Previously, in GWTC-2, only the GstLAL matched-filter pipeline included Virgo data; now all three pipelines analyze the data from all three detectors. For inferring the source properties, we use waveform models that include effects of spin-induced precession of the binary orbit, contributions from both the dominant and sub-dominant spherical harmonic modes, and tidal effects as appropriate [START_REF] Pratten | Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes[END_REF][START_REF] Pratten | Setting the cornerstone for a family of models for gravitational waves from compact binaries: The dominant harmonic for nonprecessing quasicircular black holes[END_REF][START_REF] García-Quirós | Multimode frequency-domain model for the gravitational wave signal from nonprecessing black-hole binaries[END_REF][START_REF] García-Quirós | Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids[END_REF][START_REF] Ossokine | Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation[END_REF][START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF][START_REF] Cotesta | Enriching the Symphony of Gravitational Waves from Binary Black Holes by Tuning Higher Harmonics[END_REF][START_REF] Dietrich | Closed-form tidal approximants for binary neutron star gravitational waveforms constructed from high-resolution numerical relativity simulations[END_REF][START_REF] Dietrich | Matter imprints in waveform models for neutron star binaries: Tidal and self-spin effects[END_REF].

The paper is structured as follows: Sec. II describes the instruments and the data that are analyzed by the searches, including methods on calibration, data quality, and glitch mitigation. Sec. III describes the methods used by the search pipelines. Sec. IV describes the events in GWTC-2.1, comparison to GWTC-2, sensitivity of the search pipelines used, and inferred rates of BNSs and BBHs. Sec. V describes the methods used for estimating the source parameters of the GW candidates and results, and in Sec. VI, we discuss the astrophysically interesting events and their implications. In Sec. VII we describe the data products being released alongside this catalog and our conclusions. Finally, in Appendix A, we provide the source properties of events with p astro greater than 0.5 that have previously been described in GWTC-1 and GWTC-2. Companion results from the second half of the third observing run (O3b) are presented in the third Gravitational-Wave Transient Catalog, GWTC-3 [START_REF] Abbott | GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run[END_REF].

II. INSTRUMENTS AND DATA

The Advanced LIGO [START_REF] Aasi | Advanced LIGO[END_REF] and Advanced Virgo [START_REF] Acernese | Advanced Virgo: a second-generation interferometric gravitational wave detector[END_REF] instruments are kilometer-scale laser interferometers. The two LIGO detectors are located in Hanford, Washington and Livingston, Louisiana in the United States, and the Virgo detector near Pisa in Italy. The advanced generation of interferometers began operations in 2015, and observing periods have alternated with commissioning periods since then [START_REF] Abbott | Prospects for observing and localizing gravitationalwave transients with Advanced LIGO, Advanced Virgo and KAGRA[END_REF]. In the time between O2 and the O3, all three detectors underwent significant upgrades that substantially increased their sensitivity [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF][START_REF] Buikema | Sensitivity and Performance of the Advanced LIGO Detectors in the Third Observing Run[END_REF].

Major instrumentation upgrades on the LIGO detectors included: replacement of main lasers to increase beam stability, replacement of test masses to lower scattering and absorption losses, installation of acoustic mode dampers to mitigate parametric instabilities [START_REF] Biscans | Suppressing parametric instabilities in LIGO using low-noise acoustic mode dampers[END_REF], installation of a squeezed vacuum source to reduce quantum noise [START_REF] Tse | Quantum-Enhanced Advanced LIGO Detectors in the Era of Gravitational-Wave Astronomy[END_REF], addressing issues with scattered light [START_REF] Soni | Reducing scattered light in LIGO's third observing run[END_REF], and implementation of improved feedback control systems for the instruments. Compared to the O2 run, the Hanford BNS range [START_REF] Allen | FIND-CHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries[END_REF][START_REF] Chen | Distance measures in gravitational-wave astrophysics and cosmology[END_REF] increased by 64% (from 66 Mpc to 108 Mpc), and for Livingston by 53% (from 88 Mpc to 135 Mpc).

For Virgo, major upgrades included: replacement of the steel wire suspensions of the four test masses with fused-silica fibers [START_REF] Aisa | The Advanced Virgo monolithic fused silica suspension[END_REF], modification of the vacuum system to avoid dust contamination of the lowest suspension stage, replacement of the main laser to increase power, installation of a squeezed vacuum source to reduce quantum noise [START_REF] Acernese | Increasing the Astrophysical Reach of the Advanced Virgo Detector via the Application of Squeezed Vacuum States of Light[END_REF], improvements in beam stability [START_REF] Blom | Vertical and Horizontal Seismic Iso-lation Performance of the Advanced Virgo External Injection Bench Seismic Attenuation System[END_REF], and addressing issues with scattered light. Compared to the O2 run, the Virgo BNS range increased by 73% (from 26 Mpc to 45 Mpc).

The processing of the data recorded by the LIGO and Virgo detectors includes several steps that occur both in near-real time to allow for the broadcasting of pub-lic alerts, and in higher latency to shape the final data set and update the catalogs of GW events. Raw data calibration and the subtraction of noise from known instrumental sources, documented in Sec. II A, occur first and the GW strain data, reconstructed independently in each detector, are then jointly processed. Significant GW candidates are vetted with several data quality tests as a part of the standard analysis procedure. This procedure is described in Sec. II B.

A. Calibration and noise subtraction

The strain data used for astrophysical analyses is derived from the optical power variations at the output ports of the interferometers. Calibration of the raw photodetector signal to GW strain requires a detailed understanding and modeling of the control system and optomechanical response of the interferometers throughout an observing run. This allows for accurate and reliable calibration of the strain and also for quantifying its systematic and statistical uncertainty. The detailed procedure for the calibration and the determination of the systematic and statistical uncertainty of the LIGO and Virgo detectors for O3 can be found in [START_REF] Sun | Characterization of systematic error in Advanced LIGO calibration[END_REF][START_REF] Acernese | Calibration of Advanced Virgo and reconstruction of detector strain h(t) during the Observing Run O3[END_REF][START_REF] Estevez | The Advanced Virgo Photon Calibrators[END_REF].

There are usually two calibrations applied to the data; a low-latency calibration and, if needed, an offline calibration. The low-latency (online) estimate of the strain uses the best models of the detector at the time of recording. However, over the course of any observing run, data drop-outs due to computer failures, incomplete modeling of the detector, and unknown residual systematic errors are often identified. The offline calibration incorporates the necessary corrections and improvements, producing a better calibrated strain with better known systematic uncertainty.

In addition, numerous noise sources and calibration lines that limit detectors' sensitivity are measured and linearly subtracted from the data [START_REF] Vajente | Machine-learning nonstationary noise out of gravitational-wave detectors[END_REF][START_REF] Davis | Improving the Sensitivity of Advanced LIGO Using Noise Subtraction[END_REF][START_REF] Viets | Subtracting Narrow-band Noise from LIGO Strain Data in the Third Observing Run[END_REF][START_REF] Estevez | Online h(t) reconstruction for Virgo O3 data: start of O3[END_REF]. This subtraction is performed online to generate the LIGO and Virgo low-latency strain data, and it is also performed when regenerating the LIGO offline strain data. Additionally, noise due to non-stationary coupling of the power mains with the LIGO detectors was subtracted from the offline data [START_REF] Vajente | Machine-learning nonstationary noise out of gravitational-wave detectors[END_REF]. As an example of noise subtraction, Fig. 1 shows the improvement in the noise levels around the 60 Hz mains line in the Hanford detector, after non-linear noise subtraction was applied to the strain time series. Taking as a figure of merit the BNS range of the detectors [START_REF] Allen | FIND-CHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries[END_REF][START_REF] Chen | Distance measures in gravitational-wave astrophysics and cosmology[END_REF], the subtraction results in a median range increase of 0.9 Mpc for Hanford and 0.2 Mpc for Livingston.

In GWTC-2, search pipelines and parameter estimation analyses used a mix of low-latency and offline calibrated frames. In contrast to this, all searches and analyses presented in this paper use strain data with the best available calibration and noise subtraction for each detector. For LIGO, this corresponds to the offline re- calibrated data with 60 Hz non-linear subtraction. For Virgo, the online strain data stream was good enough to be used offline, except for the last two weeks of O3a which were reprocessed to improve subtraction of control and laser frequency noise [START_REF] Rolland | Reprocessing of h(t) for the last two weeks of O3a[END_REF]. The strain data used in this work are publicly accessible through the Gravitational Wave Open Science Center (GWOSC) [START_REF]The o3a data release[END_REF].

In addition, the LIGO offline data are accompanied with a much improved systematic and statistical error estimate compared to the online data. The probability distribution of the calibration uncertainty estimate for LIGO in O3a is characterized in [START_REF] Sun | Characterization of systematic error in Advanced LIGO calibration[END_REF], with the systematic error over the detectors' bandwidth being under 3% in magnitude and under 2 • in phase. The uncertainty in the Virgo strain data in O3a had a maximum systematic error over the detector's bandwidth under 5% in magnitude and under 2 • in phase [START_REF] Acernese | Calibration of Advanced Virgo and reconstruction of detector strain h(t) during the Observing Run O3[END_REF]. Parameter estimation takes into account calibration uncertainties, as described in Sec. V. Given the size of calibration uncertainties in O3, there is no evidence that they have a significant impact on the inference of source parameters [START_REF] Payne | Gravitational-wave astronomy with a physical calibration model[END_REF][START_REF] Vitale | Physical approach to the marginalization of LIGO calibration uncertainties[END_REF].

B. Data quality, event validation & glitch mitigation

LIGO and Virgo data quality is continuously monitored during an observing run both on site and remotely, as reported in [START_REF] Davis | LIGO Detector Characterization in the Second and Third Observing Runs[END_REF][START_REF] Acernese | Virgo Detector Characterization and Data Quality during the O3 run[END_REF]. This can include, for example, internal detector summary pages which detail the status of the detectors and interferometer subsystems [START_REF] Macleod | [END_REF][START_REF] Hemming | Virgo Interferometer Monitor (VIM) Web User Interface (WUI) User Guide[END_REF]. Feedback from GW searches also gives an indication of the impact of data quality on the sensitivity of a search. To exclude identified instances of poor data quality from the searches and produce the results in Sec. III, we used the same methods and data products as reported for GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. The data quality products used in this work are publicly available [START_REF]The o3a data release[END_REF][START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Data Quality Products for GW Searches[END_REF].

Once a GW event has been identified by the search pipelines, we check the quality of data around the time of the event. We followed the same procedures outlined in [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] to validate the data quality around each new GW candidate reported in this paper. The aim of these validation procedures is to identify any instrumental or environmental noise that may impact the estimation of GW signal parameters. As summarized for GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], in some cases short-duration noise transients, or glitches [START_REF] Davis | LIGO Detector Characterization in the Second and Third Observing Runs[END_REF][START_REF] Abbott | Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914[END_REF][START_REF] Nuttall | Characterizing transient noise in the LIGO detectors[END_REF][START_REF] Soni | Discovering features in gravitational-wave data through detector characterization, citizen science and machine learning[END_REF], can be subtracted from the data [START_REF] Cornish | Bayeswave: Bayesian inference for gravitational wave bursts and instrument glitches[END_REF][START_REF] Bécsy | Parameter estimation for gravitational-wave bursts with the BayesWave pipeline[END_REF][START_REF] Pankow | Mitigation of the instrumental noise transient in gravitational-wave data surrounding GW170817[END_REF][START_REF] Neil | BayesWave analysis pipeline in the era of gravitational wave observations[END_REF]. When this is not possible, analyses use tailored configurations, for example, a modified low-frequency cutoff, to exclude data that could be corrupted by the presence of a nearby glitch. The full list of candidate events using candidate-specific glitch mitigation, along with the mitigation configuration, is found in Table I. These data, for the events where the glitch-mitigated data was used for the parameter estimation analysis in Sec. V, are publicly accessible [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Glitch modelling for events[END_REF]. No candidates in this catalog have clear evidence of instrumental origin identified through data quality validation studies.

III. CANDIDATE IDENTIFICATION

GW data is analyzed to search for candidates in two stages: first in low-latency in order to generate public alerts that subsequently trigger follow-up astronomical observations, and then in higher latency in the form of an offline analysis of the archival strain data, which is used to create GW catalogs. Five pipelines were used in real time to analyze O3 data: a minimally modeled generic transient search (coherent WaveBurst [START_REF] Klimenko | A wavelet method for detection of gravitational wave bursts[END_REF][START_REF] Klimenko | Constraint likelihood analysis for a network of gravitational wave detectors[END_REF][START_REF] Klimenko | Constraint likelihood method: Generalization for colored noise[END_REF][START_REF] Klimenko | Localization of gravitational wave sources with networks of advanced detectors[END_REF][START_REF] Klimenko | Method for detection and reconstruction of gravitational wave transients with networks of advanced detectors[END_REF]), and four matched-filter [START_REF] Allen | FIND-CHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries[END_REF][START_REF] Allen | χ 2 time-frequency discriminator for gravitational wave detection[END_REF] pipelines (GstLAL [START_REF] Sachdev | The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs[END_REF][START_REF] Hanna | Fast evaluation of multi-detector consistency for real-time gravitational wave searches[END_REF][START_REF] Messick | Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data[END_REF], MBTA [START_REF] Aubin | The MBTA pipeline for detecting compact binary coalescences in the third LIGO-Virgo observing run[END_REF], PyCBC [START_REF] Dal | Implementing a search for aligned-spin neutron star-black hole systems with advanced ground based gravitational wave detectors[END_REF][START_REF] Usman | The PyCBC search for gravitational waves from compact binary coalescence[END_REF][START_REF] Nitz | Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search[END_REF][START_REF] Gareth | Extending the PyCBC search for gravitational waves from compact binary mergers to a global network[END_REF], and SPIIR [START_REF] Chu | Low-latency detection and localization of gravitational waves from compact binary coalescences[END_REF]). Collectively, they identified 56 unretracted candidates during O3, 33 of which were found in O3a. GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] presented 39 events identified by coherent WaveBurst, GstLAL, and PyCBC in the first offline search over O3a.

We present here results from a refined offline search of O3a. The search employs three matched-filter pipelines: GstLAL, PyCBC, and MBTA [START_REF] Aubin | The MBTA pipeline for detecting compact binary coalescences in the third LIGO-Virgo observing run[END_REF], marking the first time that MBTA results from archival data are presented and included in a GW catalog. All three pipelines analyze the data from all three detectors. While GWTC-2 imposed a FAR ceiling of 2 per year on candidates, here we release a deep list of GW candidates with a FAR smaller than 2 per day [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Candidate Data Release[END_REF]. In addition, we identify the 44 CBC candidates with an estimated p astro greater than 0.5 (Table II). There are also 2 candidates with p astro below 0.5 that do meet the FAR criterion used in GWTC-2; these are presented as marginal candidates. This GW catalog contains the largest number of candidates with p astro greater than 0.5 to date.

In Sec. III A, we first lay out a general description of matched filter searches and in Sec. III B, we describe the methods employed by the three CBC searches used in this work. We describe the search results in the following Sec. IV.

A. Matched-filter searches

The matched-filter method relies on having a model of the signal, as a function of the physical parameters. The parameters include those that are intrinsic to the source: two individual component masses m 1 , m 2 and two dimensionless spin vectors χ 1 , χ 2 (related to each component's spin angular momentum S i by χ i = c S i /(Gm 2 i )), and seven extrinsic parameters that provide the orientation and position of the source in relation to the Earth: the luminosity distance D L , two-dimensional sky position (right ascension α and declination δ), inclination between total angular momentum and line-of-sight θ JN , time of merger t c , a reference phase φ, and polarization angle ψ. The search pipelines create a template bank [START_REF] Owen | Matched filtering of gravitational waves from inspiraling compact binaries: Computational cost and template placement[END_REF][START_REF] Harry | A Stochastic template placement algorithm for gravitational wave data analysis[END_REF][START_REF] Privitera | Improving the sensitivity of a search for coalescing binary black holes with nonprecessing spins in gravitational wave data[END_REF] of GW waveforms covering the desired intrinsic parameter space, and use these to filter against the data and produce signal-to-noise ratio (SNR) time series. The component masses describing template waveforms are affected by source redshift z as

m det i = (1 + z)m i .
For each set of intrinsic parameters, extrinsic parameters affecting the signal's amplitude and phase may be maximized over analytically [START_REF] Allen | FIND-CHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries[END_REF], if the signal can be approximated as a pure quadrupole mode, i.e. ( , |m|) = (2, 2). In particular, for this search, the templates use only the dominant quadrupole mode and assume quasicircular orbits with component spins aligned with the total orbital angular momentum. Peaks in the resulting SNR time series are stored as triggers. GW candidates are formed by imposing consistency in time and in template intrinsic parameters between triggers in different detectors; in addition, GstLAL also considers noncoincident triggers as candidates [START_REF] Sachdev | The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs[END_REF].

When considering a single template in a single detector with stationary, Gaussian noise, the matched filter SNR is an optimal statistic for ranking candidates. However, additional terms are needed to optimize sensitivity in searches of real data covering a wide signal parameter space. To account for the multi-detector network, the distribution of signals over relative times, phases and amplitudes between detectors is considered [START_REF] Hanna | Fast evaluation of multi-detector consistency for real-time gravitational wave searches[END_REF][START_REF] Nitz | Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search[END_REF]. Since detector noise is not stationary or Gaussian, signalconsistency tests such as chi-squared [START_REF] Allen | χ 2 time-frequency discriminator for gravitational wave detection[END_REF] are calculated and used to rank candidates.

The distribution of noise triggers may vary strongly over the template masses and spins; we then model its variation empirically, as a function of combinations of parameters that are typically well-constrained by GW measurements. The binary's chirp mass [START_REF] Blanchet | Gravitational radiation damping of compact binary systems to second postNewtonian order[END_REF],

M = (m 1 m 2 ) 3/5 (m 1 + m 2 ) 1/5 , (1)
determines to lowest order the phase evolution during the inspiral, and is typically better constrained than the component masses. At higher orders, the binary phase evolution is affected by the mass ratio q = m 2 /m 1 (where m 2 ≤ m 1 ) and by the effective inspiral spin χ eff , defined as [START_REF] Ajith | Inspiral-merger-ringdown waveforms for black-hole binaries with non-precessing spins[END_REF]

χ eff = (m 1 χ 1 + m 2 χ 2 ) • LN M , (2)
where M = m 1 + m 2 is the total mass and LN is the unit vector along the Newtonian orbital angular momentum. Finally, the ranking of events by the search pipelines may account for an assumed prior distribution of signals over masses and spins [START_REF] Dent | Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters[END_REF][START_REF] Kin | From simulations to signals: Analyzing gravitational waves from compact binary coalescences[END_REF]. The significance of each candidate event is quantified by its FAR, the estimated rate of events due to noise with equal or higher ranking statistic value. The FAR is calculated by each search pipeline by constructing a set of background samples designed to have the same distribution over ranking statistic as search events in the absence of binary merger GW signals.

By considering also the expected distribution of GW signal events recovered by a given search, we may derive an estimate of the relative probabilities of noise (terrestrial) origin p terr , and signal (astrophysical) origin p astro [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF][START_REF] Abbott | The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF][START_REF] Abbott | Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF]. For the bulk of released events, detailed estimates of source parameters are not calculated. Therefore, based only on the matched-filter search results we also estimate the probability for each event to belong to three possible astrophysical binary source classes, labeled BNS, NSBH and BBH. The classes are defined by binary component masses: BNS corresponds to {m 1 , m 2 } < 3 M , NSBH to m 1 > 3 M , m 2 < 3 M , and BBH to {m 1 , m 2 } > 3 M . For MBTA, a 2.5 M cut is used instead of 3 M , with a gap to 5 M for BBH. These definitions are chosen for simplicity: they do not imply that every binary component within a given mass range is necessarily a neutron star (NS) or a black hole (BH). Such inference would ultimately require measurement of the effects of NS matter on observed signals, which is beyond the capabilities of the search pipelines. The probabilities for an event to belong to each class (p BNS , p NSBH , p BBH , and p terr ) are calculated from the template masses and spins recovered by the searches, under the assumption that events from each class occur as independent Poisson processes. The calculation also requires the choice of a prior on the event counts in each category [START_REF] Abbott | Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF]. GstLAL used a uniform prior for the BNS and NSBH categories, and a Poisson-Jeffreys prior for the BBH category; MBTA used a uniform prior for the BNS category, and a Poisson-Jeffreys prior for the NSBH and BBH categories; and PyCBC used a Poisson-Jeffreys prior for all three categories. Given the number of candidates, the prior choice does not significantly impact the BBH results. Implementation details differ between pipelines, as summarized below; the resulting probability estimates are listed in Tables II andIII.

While the p astro values given here represent our best estimates of the origin of candidates using the information available from search pipelines, they are subject to statistical (random) and systematic errors, as well as in some cases clearly differing for a given candidate between different pipelines. One such uncertainty arises from methods used to rank events between pipelines, including tests for noise artifacts: such tests, such as chi-squared statistics, will in general add (different) random variations to the ranking of a given event, in addition to their differing power in distinguishing signals from artifacts. For single-detector candidates, there is an additional inherent uncertainty in estimating the rate of comparable noise events, which may only be bounded to (less than) 1 per observing time. An inherent source of potential systematic error also lies in the search ranking statistic used in the calculation of p astro : such statistics are optimized to detect a specific (usually broad) distribution of signals over binary intrinsic parameters. The resulting p astro estimates may be biased if this distribution deviates significantly from the (unknown) true signal distribution. The risk of such bias is largest for regions of parameter space containing few, or zero, confirmed detections. For all these reasons, our current p astro values may be revised in the future, particularly as and when current uncertainties in the true signal rate and distributions are eventually reduced.

We next review specific methods used by individual matched-filter pipelines.

B. Search pipelines

In this section we describe the pipelines that were used to identify the candidates presented in GWTC-2.1.

GstLAL

The GstLAL analysis used in this search is largely similar to the one used in the previous analysis [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] and uses the same log-likelihood ratio L as the ranking statistic. Improvements have been made to the input data products generated by iDQ, the statistical inference framework to autonomously detect non-Gaussian noise artifacts in strain data based on auxiliary witness sensors [START_REF] Essick | iDQ: Statistical inference of non-gaussian noise with auxiliary degrees of freedom in gravitational-wave detectors[END_REF][START_REF] Godwin | Incorporation of Statistical Data Quality Information into the GstLAL Search Analysis[END_REF]. This iDQ timeseries is used to compute one of the terms in the log-likelihood ratio within the GstLAL analysis, that informs the search of the presence of non-Gaussian noise in close proximity to a GW candidate. Compared to GWTC-2, the timeseries generated by iDQ was reprocessed offline, having access to an expanded set of auxiliary witness sensors and trained with an acausal binning scheme [START_REF] Essick | iDQ: Statistical inference of non-gaussian noise with auxiliary degrees of freedom in gravitational-wave detectors[END_REF]. As a result, the generated iDQ timeseries performs better in identifying noise artifacts in strain data. In addition, for GWTC-2 the iDQ term was only used when ranking singledetector triggers, whereas now it is used for both coincident and single-detector triggers. Because of changes in the iDQ term, the empirically determined penalty for single-detector candidates had to be retuned compared to GWTC-2, and was increased to a penalty of ∆L = -12 from ∆L = -10. The single-detector event penalty is determined by comparing the recovery of simulated signals in single detector versus combinations of detectors and the sensitive volume-time for each configuration.

For the GstLAL analysis, p terr and p astro shown in Tables II and III are estimated following the multicomponent population analysis [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF][START_REF] Shasvath | A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model[END_REF]. The response of each GstLAL template to each astrophysical source class, computed semi-analytically [START_REF] Kin | From simulations to signals: Analyzing gravitational waves from compact binary coalescences[END_REF], is used in estimating these probabilities. The volume-time sensitivity of the pipeline used in this calculation is estimated based on simulated sources injected into the pipeline and is rescaled to the astrophysical distribution [START_REF] Tiwari | Estimation of the sensitive volume for gravitational-wave source populations using weighted monte carlo integration[END_REF]. The volume-time ratios are used to combine triggers from various observation runs and perform a multicomponent analysis yielding p astro and merger rates [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF][START_REF] Shasvath | A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model[END_REF] inferred from O1 to O3a. The astrophysical distribution assumed in this analysis uses a log-uniform distribution for the source component masses, the component spins aligned with the orbital angular momentum, and a uniform distribution for the component spin magnitudes. The BH masses in BBHs and NSBHs are distributed between 3 M and 300 M with aligned component spins distributed in the range [-0.99, 0.99]. The NS masses in NSBHs and BNSs are distributed between 1 M and 3 M . In NSBHs, the NS spins are assumed to be aligned and distributed in the range [-0.4, 0.4], whereas, in BNSs the NSs are assumed to have small spins in the range [-0.05, 0.05]. These choices match previous analyses [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF].

MBTA

The Multi-Band Template Analysis (MBTA) pipeline [START_REF] Aubin | The MBTA pipeline for detecting compact binary coalescences in the third LIGO-Virgo observing run[END_REF] is based on matched filtering, relying on coincidences between triggers observed in different detectors. The version used for the offline search is close to the online version which contributed to the LVC public alerts [115]. The archival-search version benefits from offline-specific improvements, with a background estimate made over a longer duration, and with a reranking of the candidates using information collected not just before but also after the candidate.

The parameter space covered by this analysis ranges from 1 M to 195 M for the primary (more massive) component, with total masses up to 200 M ; or from 1 M to 100 M for the primary when the mass of the secondary is between 1 M and 2 M . Component spins are aligned with the total angular momentum and are limited to 0.05 for objects below 2 M , and going up to 0.997 for objects above 2 M . The waveform used for the search is SpinTaylorT4 [START_REF] Buonanno | Detecting gravitational waves from precessing binaries of spinning compact objects: Adiabatic limit[END_REF][START_REF] Buonanno | Erratum: Quasiphysical family of gravity-wave templates for precessing binaries of spinning compact objects: Application to double-spin precessing binaries[END_REF][START_REF] Buonanno | Comparison of post-Newtonian templates for compact binary inspiral signals in gravitational-wave detectors[END_REF] if both binary masses are lighter than 2 M , and SEOBNRv4 [START_REF] Bohé | Improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors[END_REF] if the mass of one of the components is above 2 M . The total number of templates in the bank used is 727,992. The SNR threshold for recording triggers in each detector is 4.5, or 4.8 if one of the components is above 2 M .

The FAR is calculated for each coincident event by forming random coincidences among single detector background triggers. This computation is performed independently for three large regions of the parameter space bounded by a 2 M limit for the mass of each component. These three regions are allowed to contribute equally to the background, while within each of them we sum the background contributions from all the templates.

The p BNS , p NSBH , p BBH , and derived p astro quantities are computed as the fraction of recovered simulated events, representative of an astrophysical population, to this foreground plus background estimate provided by the pipeline [START_REF] Andres | Assessing the compact-binary merger candidates reported by the MBTA pipeline in the LIGO-Virgo O3 run: probability of astrophysical origin, classification, and associated uncertainties[END_REF]. The parameterizations of the populations are described in Sec. IV D, with the Power Law + Peak model used for BBH [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF]. The rate of each type of source is adjusted using a multicomponent population analysis [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF]. To follow the population and background evolution across the parameter space, 165 subregions are used. This finer resolution has the benefit of revealing events in population-rich areas, even if the overall background rate for their ranking statistic value is larger than few per year, as in the case of the high mass BBH event GW190916 200658 presented in Table II.

PyCBC

In previous LVC searches [START_REF] Abbott | Binary Black Hole Mergers in the first Advanced LIGO Observing Run[END_REF][START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF][START_REF] Abbott | All-sky search for short gravitational-wave bursts in the first Advanced LIGO run[END_REF], the offline Py-CBC [START_REF] Usman | The PyCBC search for gravitational waves from compact binary coalescence[END_REF][START_REF] Nitz | gwastro/pycbc: PyCBC Release v1[END_REF] pipeline has analyzed data only from the two LIGO detectors. In this analysis, PyCBC was extended to search data from the three-detector LIGO-Virgo network, along with updates to the event ranking statistic [START_REF] Gareth | Extending the PyCBC search for gravitational waves from compact binary mergers to a global network[END_REF] and the p astro calculation and a new method to estimate source class probability [START_REF] Dal Canton | Real-time Search for Compact Binary Mergers in Advanced LIGO and Virgo's Third Observing Run Using PyCBC Live[END_REF].

The PyCBC search uses the same template bank as in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], constructed using a hybrid geometricrandom algorithm outlined in [START_REF] Roy | Hybrid geometric-random template-placement algorithm for gravitational wave searches from compact binary coalescences[END_REF][START_REF] Roy | Effectual template banks for upcoming compact binary searches in Advanced-LIGO and Virgo data[END_REF]. Peaks in SNR time series exceeding a threshold of 4 constitute singledetector triggers. Two-detector coincident events are formed from triggers with the same component masses and spins with a physically allowed time difference between detectors, allowing for timing errors. Threedetector triple coincidences require triggers in all pairs of detectors to pass this consistency test.

The detection statistic is given by the logarithm of the ratio of estimated signal event rate density to noise event rate density. We model the noise distribution in each detector as a decreasing exponential of the matched-filter SNR, reweighted based on a chi-squared signal-glitch discriminator [START_REF] Allen | χ 2 time-frequency discriminator for gravitational wave detection[END_REF][START_REF] Harvey | Distinguishing short duration noise transients in LIGO data to improve the PyCBC search for gravitational waves from high mass binary black hole mergers[END_REF], with parameters that depend on the template intrinsic parameters. The signal distribution includes terms accounting for dependence on relative times of arrival, phases and amplitudes between detectors, as well as relative sensitivities of the participating detectors [START_REF] Nitz | Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search[END_REF]. We estimate the FAR separately for each combination of detectors via time-shifted analyses [START_REF] Usman | The PyCBC search for gravitational waves from compact binary coalescence[END_REF][START_REF] Capano | Systematic errors in estimation of gravitational-wave candidate significance[END_REF]. The significance for each candidate event is then found through addition of the FARs at the candidate's ranking statistic value over all active detector combinations [START_REF] Gareth | Extending the PyCBC search for gravitational waves from compact binary mergers to a global network[END_REF].

In addition to the generic PyCBC search, which covers the full parameter space [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] including a range of possible signal types, we also conduct a focused PyCBC BBH search [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF][START_REF] Nitz | 2-OGC: Open Gravitational-wave Catalog of binary mergers from analysis of public Advanced LIGO and Virgo data[END_REF], capable of uncovering fainter BBH mergers by imposing a prior form for the signal distribution over the template bank [START_REF] Dent | Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters[END_REF]. This search is targeted at systems with mass ratios from 1 to 1/3, primary component masses from 5 M to 350 M , and aligned, equal component spins from χ = -0.998 to 0.998.

The inference of p astro and p terr for each candidate event employs a Poisson mixture model of signal and noise events [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF][START_REF] Abbott | The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF][START_REF] Abbott | Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914[END_REF]. Here, the distribution of signal events is estimated via a set of simulated signals analyzed by the pipeline, and the rate and distribution of noise events are estimated from time-shifted analyses [START_REF] Usman | The PyCBC search for gravitational waves from compact binary coalescence[END_REF]. In GWTC-2 the calculation was only performed on potential BBH events with template chirp mass above 4.35 M (which corresponds to equal 5 M component masses).

Here, we include potential BNS and NSBH events by performing independent calculations over ranges of template chirp mass below 2.18 M (corresponding to equal 2.5 M components), and between 2.18 M -4.35 M , respectively. Although the implied signal distribution over template chirp mass does not correspond to any specific astrophysical model, it is adequate for assignment of p astro given the current knowledge of BNS and NSBH merger populations. Systematic biases in p astro calculation may arise if the (unknown) true mass distribution is different from that assumed. The calculation is also extended relative to previous analyses to account for different possible coincident combinations of detectors [START_REF] Dent | Technical note: Extending the PyCBC pastro calculation to a global network[END_REF]. The results given here are obtained from events occurring during O3a only, except for the BNS region where prior information of 1 highly significant detection was applied to represent GW170817 [START_REF] Abbott | GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral[END_REF].

The estimation method for binary source class probabilities [START_REF] Dal Canton | Real-time Search for Compact Binary Mergers in Advanced LIGO and Virgo's Third Observing Run Using PyCBC Live[END_REF] uses the binary chirp mass as input, and assumes a uniform density of candidate signals over the plane of component masses {m 1 , m 2 }. Here we take the classes to be defined by boundaries between different types of binary component at 3 M . To estimate source chirp mass, we correct the search template masses for cosmological redshift, using an estimate of the luminosity distance derived from the search SNRs and the corresponding templates' sensitivity. We then derive the relative probabilities of each source class and enforce that the sum of astrophysical source probabilities is equal to p astro .

IV. SEARCH RESULTS

We recover 1201 candidates that have FAR less than 2 per day in any of the search pipelines. These events and their estimated source probabilities are shown in Fig. 2. The candidates are shown in decreasing order of p astro . The total sum of p astro represents the Poisson rate of sources that pass the FAR threshold of 2 per day in each source class per O3a experiment, as estimated by the search pipelines. We find that this corresponds to between 24.95-44.50 signals in the BBH class, 0.66-3.80 signals in the NSBH class, and 0.22-0.81 signals in the BNS class in O3a. The range represents the difference in the search pipelines. We do not consider the PyCBC-BBH analysis in the estimate of the number of signals in the BNS class provided here, as the analysis does not search over the BNS parameter space. Names are marked for the candidate events with p BNS or p NSBH greater than 20%. The dashed vertical line shows the least significant event with p astro greater than 0.5. An estimate of the rate of sources in the subthreshold candidate list per O3a experiment is obtained by the contribution to the sum from events with p astro less than 0.5. This corresponds to between 2.55-12.40 signals in the BBH class, 0.36-2.39 signals in the NSBH class, and 0.02-0.49 signals in the BNS class in the subthreshold candidates in O3a.

We find 44 high probability CBC candidates that have p astro greater than 0.5. These events are listed in Table II. This list includes 8 new candidates that were not present in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. These are marked in bold in Table II. Out of the 44 candidates, 4 were found with significant SNR only in one of the detectors by the GstLAL search, which is the only pipeline that looked for GW signals in single-detector data. These are listed with a dagger ( † ) next to the FAR in Table II. For the majority of events listed in Table II, p astro ≈ p BBH ; the exceptions are listed in Table III, which provides the list of candidates that have p BNS or p NSBH greater than 0.01.

A. New high probability candidates

We recover all the events found in GWTC-2 as having p astro above 0.5, with the exception of three:

GW190424 180648, GW190426 152155, and GW190909 114149.

Since the rate of BBH events detectable by the LIGO-Virgo detectors is greater than the rate of detectable BNS or NSBH events, the p astro for events in the BBH class is higher than that of the events in the BNS or NSBH class at a fixed FAR. Therefore, in switching to a p astro threshold from a FAR threshold, one can expect to add BBH events while dropping some low-mass events.

All the 8 new candidates with p astro greater than 0.5 are classified as BBHs, that is, p BBH is greater than p NSBH and p BNS .

Only one new candidate, GW190725 174728, has a non-negligible probability in a source class other than BBH, with non-zero p NSBH (Table III). Out of the 8 candidates, only two (GW190725 174728 and GW190916 200658) are assigned p astro > 0.5 by more than one pipeline. Differences between pipelines are expected, due to the effects of random noise fluctuations on the different ranking statistics used, and due to different assumed signal distributions and other choices. In principle, a more accurate assessment of the candidates' origins could be obtained by considering information from all pipelines; however, this is not currently implemented as a quantitative measure. One of the events, GW190917 114630, is identified as a BBH by the GstLAL pipeline, with p BBH = 0.77 (Table II). However, when its source properties are inferred by follow-up pipelines, the mass parameters are found to be consistent with NSBH systems. Had it been classified as an NSBH to begin with by the search pipeline, the resulting p astro would not have made the threshold of 0.5. There is also non-stationary noise in the LIGO Livingston detector at the time of this event, but we have no evidence that the FAR of the event is misestimated. Out of the 8 new candidates, 5 candidates (GW190426 190642, GW190725 174728, GW190805 211137, GW190916 200658, and GW190925 232845) were identified in the LVC search for gravitationally lensed candidates in O3a data [START_REF] Abbott | Search for Lensing Signatures in the Gravitational-Wave Observations from the First Half of LIGO-Virgo's Third Observing Run[END_REF] Above-threshold GW candidate list. We find 44 events that have pastro in at least one of the searches as greater than 0.5. Bold-faced names indicate the events that were not previously reported in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. The candidates marked with an asterisk were first published in 3-OGC [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF]. The second column denotes the observing instruments. Candidate events in GWTC-2.1 which do not meet the pastro threshold but were at the same time as above-threshold events are given in italics. The PyCBC and PyCBC-BBH network SNRs do not include detectors with SNRs below 4; these events are marked with double dagger ( ‡ ) next to their network SNR. The 4 events marked with a dagger ( † ) next to their FARs were found only in one detector by the GstLAL search. All four were detected using the data from LIGO Livingston. For the single-detector candidate events, the FAR estimate involves extrapolation. All single-detector candidate events in this list according to the FAR assigned to them are rarer than the background data of about 6 months collected in this analysis. Therefore, a conservative bound on the FAR for candidates denoted by † is ∼ 2 yr -1 . GstLAL FARs have been capped at 1 × 10 -5 yr -1 to be consistent with the limiting FARs from other pipelines. Dashes indicate that a pipeline did not find the event with a FAR smaller than the subthreshold FAR threshold of 2 per day. 1.00 0.00 0.00 1.00 1.00 0.00 0.00 1.00 0.93 0.07 0.00 1.00 0.93 0.07 1.00 GW190720 000836

1.00 0.00 0.00 1.00 1.00 0.00 0.00 1.00 0.95 0.05 0.00 1.00 1.00 0.00 1.00 GW190725 174728 0.59 0.00 0.00 0.59 ----0.79 0.17 0.00 0.96 0.58 0.24 0.82 GW190728 064510

1.00 0.00 0.00 1.00 1.00 0.00 0.00 1.00 0.97 0.03 0.00 1.00 0.97 0.03 1.00 GW190814 0.93 0.07 0.00 1.00 0.19 0.81 0.00 1.00 0.54 0.46 0.00 1.00 ---GW190924 021846 0.92 0.07 0.00 0.99 1.00 0.00 0.00 1.00 0.44 0.56 0.00 1.00 0.44 0.56 1.00 GW190930 133541 0.87 0.00 0.00 0.87 0.76 0.00 0.00 0.76 0.93 0.07 0.00 1.00 0.85 0.15 1.00 independently identified and presented in 3-OGC [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF].

The source properties of all 8 candidates are discussed in Sec. V D.

B. GWTC-2 candidates with pastro < 0.5

The three events in GWTC-2 that have a p astro smaller than 0.5 in GWTC-2.1 analyses are:

GW190424 180648: This event was found by Gst-LAL as a single detector BBH event in Livingston. However, the data surrounding this event recorded periodic glitching from a camera shutter and iDQ (Sec. III B 1) heavily downranked the timespan surrounding this event [START_REF] Godwin | Incorporation of Statistical Data Quality Information into the GstLAL Search Analysis[END_REF]. Figure 4 in [START_REF] Godwin | Incorporation of Statistical Data Quality Information into the GstLAL Search Analysis[END_REF] shows both the inspiral track and the surrounding glitches in the timefrequency spectrogram surrounding this event and the response of iDQ. While the down-ranking due to iDQ for this particular event remains largely the same between GWTC-2 and GWTC-2.1, the retuning of the singles penalty (Sec. III B 1) in GstLAL for GWTC-2.1 caused the significance of the event to go down. Consequently, in GWTC-2.1, this event does not meet either the FAR threshold of 2 per year or the p astro threshold of 0.5.

GW190426 152155: This event is in the marginalsignificance candidate list for GWTC-2.1 (Table IV); the FAR is similar to the one in GWTC-2 and still passed the threshold of 2 per year considered in the previous catalog. However, based on the masses recovered by the pipeline, it is assigned to the NSBH class with p NSBH = 0.14. The low p astro in the NSBH class is due to the fact that the inferred rate of detectable NSBHs is lower than that of detectable BBHs.

GW190909 114149: This candidate BBH event was found as a coincident event in Hanford and Livingston detectors by GstLAL. It is recovered now with smaller SNR in the Hanford detector and is therefore ranked lower.

C. Marginal-significance candidates

The two GW candidates that satisfy the FAR criteria used by GWTC-2, but do not have p astro greater than 0.5 are listed as marginal candidates in Table IV. Both these events were detected by GstLAL with a small FAR, and were assigned to the NSBH class with p astro and p NSBH smaller than 0.5. Since the rate of detectable signals in the NSBH class is smaller than that in the BBH class, the p astro for these are smaller than they would be in the BBH class at the same FAR.

D. Search sensitivity

As in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], we quantify the sensitivity of the search via a campaign of simulated signals injected into the O3a data and analyzed by the search pipelines. We use a BBH signal distribution adjusted over that used for GWTC-2 to give more even coverage of the inferred distribution from [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF], changing specifically the distributions over binary mass ratio and redshift. In addition to the BBH set, we also inject BNS and NSBH sets of simulated signals into the data. The sets are generated in two stages: first, points are sampled out to the maximum redshift considered for each set, then the samples are reduced to sets of potentially detectable signals by imposing that the expected LIGO Hanford-LIGO Livingston network SNR, calculated using a representative noise power spectral density (PSD), be above a threshold of 6. Although this threshold is below the matched-filter SNRs of events we consider as high-significance candidates, for detection thresholds corresponding to FARs significantly higher than 2 per year (the value used in GWTC-2), the cut may remove a non-negligible fraction of potentially detectable signals, due to random fluctuations in matched-filter SNR. The results of this simulation campaign for all the search pipelines have been made available [START_REF]GWTC-2.1: Deep extended-catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Sensitivity of search pipelines to simulated signals[END_REF].

Name

Inst. MBTA GstLAL PyCBC FAR (yr -1 ) SNR max pastro FAR (yr -1 ) SNR max pastro FAR (yr The BNS signals are generated using the SpinTaylorT4 waveform model [START_REF] Buonanno | Detecting gravitational waves from precessing binaries of spinning compact objects: Adiabatic limit[END_REF][START_REF] Buonanno | Comparison of post-Newtonian templates for compact binary inspiral signals in gravitational-wave detectors[END_REF], while the BBH and NSBH sets are generated using the SEOBNRv4PHM model [START_REF] Ossokine | Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation[END_REF][START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF]. For simulated signals with redshifted total mass below 9 M , the SEOBNRv4P model without higher-order multipole emission was used, as higher-order multipoles would lie above the data sampling Nyquist frequency. The component spin magnitudes |χ| are distributed uniformly up to a maximum of 0.4 for NS components and 0.998 for BBH, with isotropically distributed orientations.

The signal distributions over sky direction and binary orientation are isotropic. The distributions over redshift are proportional to the comoving volume element dV c /dz, multiplied by a factor (1 + z) -1 accounting for time dilation, and by a factor (1 + z) κ modeling possible evolution of the comoving merger rate density with redshift (as in Appendix E of [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF]). A summary of the distributions of the three injection sets is given in Table V.

Given the merger distribution used for each injection set, the sensitivity of each search over the O3 data is quantified by relating the expected number of detections, at a specified significance threshold, to the local astrophysical merger rate as N det = VR(z = 0), where V is an effective sensitive hypervolume with units of volume×time. This effective hypervolume is estimated by counting the number of injected signals that are detected at the given threshold, here a FAR of 2 per year.

In addition to assumed merger distributions that follow those used for the injection sets, we also provide V for a fiducial BBH population model representative of those found to have high posterior probability in our population analysis of GWTC-2 [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF]. We choose the Power Law + Peak model (defined in Appendix B.2 of [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF]) with parameters α = 2.5, β = 1.5, m min = 5 M , m max = 80 M , λ peak = 0.1, µ m = 34 M , σ m = 5 M , δ m = 3.5 M , setting the redshift evolution to κ = 0. The sensitivity for this BBH population is evaluated via importance sampling [START_REF] Tiwari | Estimation of the sensitive volume for gravitational-wave source populations using weighted monte carlo integration[END_REF][START_REF]GWTC-2 Data Release: Sensitivity of Matched Filter Searches to Binary Black Hole Merger Populations[END_REF] implemented via GW-Population [START_REF] Talbot | Parallelized Inference for Gravitational-Wave Astronomy[END_REF]. The effective hypervolume for each search and signal population is given in Table V.

E. Rates of BBH and BNS events

The rates of BBH and BNS binary mergers in the local Universe were estimated in a companion paper [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF] to GWTC-2, using the count of detected events with FAR below 1 per year, combined with estimates of search sensitivity to the respective populations. The BBH rate estimate was marginalized over uncertainties in the parameters of the population models used, while the BNS rate estimate assumed a population uniform in component masses between 1 M and 2.5 M . The merger rate of NSBHs was recently calculated following the discovery of GW200105 162426 and GW200115 042309 [START_REF] Abbott | Observation of Gravitational Waves from Two Neutron Star-Black Hole Coalescences[END_REF], and we do not update it here.

Here, we present complementary BBH and BNS rate estimates based solely on the matched filter search pipeline outputs, with methods that allow us to incorporate a large number of likely noise (background) events [START_REF] Farr | Counting And Confusion: Bayesian Rate Estimation With Multiple Populations[END_REF] and thus avoid potential bias due to an arbitrary choice of significance threshold. Such methods allow for both foreground (signal) and background event distributions with a priori unknown rates, considered as independent Poisson processes. Furthermore, for the GstLAL pipeline we employ a multicomponent mixture analysis [START_REF] Shasvath | A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model[END_REF] to estimate the rates of events in several astrophysical classes (BNS, NSBH, and BBH) and terrestrial. Every trigger is assigned probabilities of membership in each class, as described in Sec. III B 1. For the MBTA and PyCBC rate estimates, only the BBH class is considered.

The merger rate estimate then arises from the number of search events assigned to each class, divided by the estimated search sensitivity obtained via injection campaigns re-weighted to an astrophysical population model [START_REF] Tiwari | Estimation of the sensitive volume for gravitational-wave source populations using weighted monte carlo integration[END_REF], as discussed in the previous section. The population models used here to quantify search sensitivity are in general different from those used to obtain source classification probabilities, described in Sec. III A.

In both the BBH and BNS cases, as for other rate interval estimates derived from search results [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF], a Poisson-Jeffreys (∝ R -1/2 ) prior was used. The choice of prior has little influence on estimated BBH rate due to the large count of signals, but it has a nontrivial effect on the BNS rate estimate as compared to, for instance, a uniform prior.

BBH merger rate estimates are provided by the Gst- [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF], and BNS and NSBH populations following the injected distributions. We give estimates for each search pipeline independently at a FAR threshold of 2 per year, and for all pipelines combined, i.e. counting all injections detected in at least one pipeline at the given threshold.

LAL, PyCBC-BBH and MBTA pipelines. The astrophysical population assumed for measuring search sensitivities is given by the Power Law + Peak model of [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF] with fiducial parameters as in Sec. IV D. The resulting merger rates are 25.0 +7.2 -6.1 Gpc -3 yr -1 for GstLAL, 26.0 +8.2 -6.8 Gpc -3 yr -1 for PyCBC-BBH and 25.6 +9. 6 -7.8 Gpc -3 yr -1 for MBTA. These estimates are fully consistent with the estimate of 23.9 +14.3 -8.6 Gpc -3 yr -1 as derived in [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF] using only significant (FAR< 1 yr -1 ) events, and allowing for uncertainties in the population model parameters. Following [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF], we have not included the effect of calibration uncertainties in our rate estimates. A full quantitative analysis of such uncertainties would require accounting for possible frequency-and time-dependent amplitude systematic errors [START_REF] Sun | Characterization of systematic error in Advanced LIGO calibration[END_REF]; these are typically ∼ 3% or less, corresponding to a 10% sensitive volume uncertainty which remains subdominant to the Poisson uncertainty in the signal counts [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF].

Since the only significant event consistent with BNS merger in O3a, GW190425, was observed in a single detector, it is present only in the GstLAL search results. Hence, we quote a BNS merger rate estimate only from the GstLAL pipeline, as we expect this to be more informative than estimates from pipelines that did not consider single-detector triggers. For measuring the search sensitivity to BNS mergers, we use the injected population described above in Sec. IV D, yielding an estimated merger rate 286 +510 -237 Gpc -3 yr -1 . This estimate is fully consistent within uncertainties with the simpler estimate of 320 +490 -240 Gpc -3 yr -1 derived using a fixed threshold in expected SNR to determine sensitivity to simulated signals [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF].

V. ESTIMATION OF SOURCE PARAMETERS

The physical parameters ϑ describing each GW source binary, corresponding to individual entries from the list of events in Table II, are inferred directly from the data d and represented as a posterior probability distribution p( ϑ|d). This probability distribution is evaluated through Bayes' theorem as

p( ϑ|d) ∝ p(d| ϑ)π( ϑ) , (3)
with p(d| ϑ) being the likelihood of d given a set of source parameters ϑ, and π( ϑ) being the prior probability distribution assumed for those parameters. The likelihood itself describes the assumptions of the underlying stochastic process generating the noise present in d from a given detector. This noise is assumed to be Gaussian, stationary and uncorrelated between pairs of detectors [START_REF] Benjamin | A guide to LIGO-Virgo detector noise and extraction of transient gravitational-wave signals[END_REF][START_REF] Christopher | Parameter estimation for binary neutron-star coalescences with realistic noise during the Advanced LIGO era[END_REF], as further discussed in Sec. II B. This yields a Gaussian likelihood [START_REF] Cutler | Gravitational waves from merging compact binaries: How accurately can one extract the binary's parameters from the inspiral wave form?[END_REF][START_REF] Veitch | Parameter estimation for compact binaries with ground-based gravitational-wave observations using the lalinference software library[END_REF], which for the i th detector used in a given analysis takes the form

p(d i | ϑ) ∝ exp - 1 2 d i -h i M ( ϑ) d i -h i M ( ϑ) , (4)
with d i representing the data from this instrument.

h i M ( ϑ)
is the binary waveform model h( ϑ) calculated for ϑ after being projected onto the detector and adjusted to account for the uncertainty present in the offline calibration (as described in Sec. II) of d i [START_REF] Abbott | Properties of the Binary Black Hole Merger GW150914[END_REF]. The final likelihood is evaluated coherently across the network of available detectors and is obtained by multiplication of the likelihoods in each detector. The term from Eq. ( 4) in angle brackets, a|b , represents a noise-weighted inner product [START_REF] Cutler | Gravitational waves from merging compact binaries: How accurately can one extract the binary's parameters from the inspiral wave form?[END_REF][START_REF] Finn | Detection, measurement and gravitational radiation[END_REF]. In addition to d i and h i M ( ϑ), evaluating this inner product requires specification of the bandwidth to be used in the analysis as well as the PSD characterizing the noise process. The low-frequency cutoff used in our analysis is set at f low = 20 Hz. Time-domain waveform models are generated starting at a frequency f start such that the ( , |m|) = (3, 3) spherical harmonic mode of the binary inspiral signal, as estimated from a set of preliminary analyses [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], is present at f low . The highfrequency cutoff f high is selected for each analysis as f high = α roll-off f Nyquist such that the ringdown frequency of the ( , |m|) = (3, 3) spherical harmonic mode, inferred from waveforms taken from the same set of preliminary analyses as mentioned above [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], occurs below f high .

The parameter α roll-off in this expression is a scale factor chosen in order to minimize the frequency roll-off effects caused by the application of a tapering window to the time-domain data [START_REF] Romero-Shaw | Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue[END_REF]. The Nyquist frequency f Nyquist is then selected as the smallest power-of-two-valued frequency which together with α roll-off = 0.875 satisfies the constraint on f high specified above. Similarly, the duration of data d used in each analysis is determined from a requirement that the waveforms from previous analyses [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] as evaluated from f low = 20 Hz and rounding up to the next power-of-two number of seconds, are contained in the selected data segment. The PSD for each event is inferred directly from the same data that is to be used in the likelihood, through the parametrized model implemented in BayesWave [START_REF] Littenberg | Bayesian inference for spectral estimation of gravitational wave detector noise[END_REF][START_REF] Chatziioannou | Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers[END_REF]. From the inferred posterior distribution of PSDs, the median value at each frequency is then used in the final analysis [START_REF] Chatziioannou | Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers[END_REF][START_REF] Biscoveanu | Quantifying the Effect of Power Spectral Density Uncertainty on Gravitational-Wave Parameter Estimation for Compact Binary Sources[END_REF].

A GW signal emitted from a binary containing two BHs can be fully characterized by ϑ containing a set of fifteen parameters, as introduced in Sec. III A, if the binary orbit is assumed to have negligible eccentricity. 1The mass and spin of the post-merger remnant BH, together with the peak GW luminosity, are calculated from the initial binary parameters using fits to numerical relativity (NR) [START_REF] Abbott | GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2[END_REF][START_REF] Hofmann | The final spin from binary black holes in quasicircular orbits[END_REF][START_REF] Jiménez-Forteza | Hierarchical data-driven approach to fitting numerical relativity data for nonprecessing binary black holes with an application to final spin and radiated energy[END_REF][START_REF] Healy | Remnant of binary black-hole mergers: New simulations and peak luminosity studies[END_REF][START_REF] Nathan | Determining the final spin of a binary black hole system including in-plane spins: Method and checks of accuracy[END_REF][START_REF] Keitel | The most powerful astrophysical events: Gravitational-wave peak luminosity of binary black holes as predicted by numerical relativity[END_REF].

For binaries expected to contain at least one NS, the time-evolution of the binary orbit is modified by the presence of matter and quantified in terms of the dimensionless quadrupole tidal deformability Λ 1,2 , adding one more parameter for each NS. In addition to the quadrupole tidal effects, other matter effects are parameterized in terms of Λ 1,2 using equation of state (EoS)-insensitive relations [START_REF] Yagi | Approximate Universal Relations for Neutron Stars and Quark Stars[END_REF]. When a GW event is assumed to contain one or more neutron star, we do not report final masses or spins for the remnant object.

A. Waveform models

The binary properties of the observed GW events are characterized through matching against a set of waveform models. For the events identified as BBHs, with both components inferred to have masses above 3M , we use the independently developed IMRPhenomXPHM [START_REF] Pratten | Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes[END_REF][START_REF] Pratten | Setting the cornerstone for a family of models for gravitational waves from compact binaries: The dominant harmonic for nonprecessing quasicircular black holes[END_REF][START_REF] García-Quirós | Multimode frequency-domain model for the gravitational wave signal from nonprecessing black-hole binaries[END_REF][START_REF] García-Quirós | Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids[END_REF] and SEOBNRv4PHM [START_REF] Ossokine | Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation[END_REF][START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF] models. Both waveform models capture effects from spin-induced precession of the binary orbit, as well as contributions from both the dominant and sub-dominant multipole moments of the emitted gravitational radiation.

IMRPhenomXPHM [START_REF] Pratten | Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes[END_REF] describes the GW signal from precessing non-eccentric BBHs and is part of the fourth generation of phenomenological frequency domain models. Precession is implemented via a twisting-up procedure, as for its predecessors IMRPhenomPv2 [START_REF] Hannam | Simple Model of Complete Precessing Black-Hole-Binary Gravitational Waveforms[END_REF][START_REF] Bohé | Phe-nomPv2 -technical notes for the LAL implementation[END_REF] and IMRPhenomPv3HM [START_REF] Khan | Phenomenological model for the gravitational-wave signal from precessing binary black holes with two-spin effects[END_REF][START_REF] Khan | Including higher order multipoles in gravitational-wave models for precessing binary black holes[END_REF]. For this, an alignedspin model defined in the co-precessing frame is mapped through a suitable frame rotation to approximate the multipolar emission of a precessing system in the inertial frame. The stationary phase approximation is used to obtain closed form expressions in the frequency domain [START_REF] Ramos-Buades | Validity of common modeling approximations for precessing binary black holes with higher-order modes[END_REF]. The description for the precession dynamics is derived using a multiple scale analysis of the post-Newtonian (PN) equations of motion [START_REF] Chatziioannou | Constructing Gravitational Waves from Generic Spin-Precessing Compact Binary Inspirals[END_REF]. The underlying aligned spin model for IMRPhenomX-PHM is IMRPhenomXHM [START_REF] Pratten | Setting the cornerstone for a family of models for gravitational waves from compact binaries: The dominant harmonic for nonprecessing quasicircular black holes[END_REF][START_REF] García-Quirós | Multimode frequency-domain model for the gravitational wave signal from nonprecessing black-hole binaries[END_REF][START_REF] García-Quirós | Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids[END_REF], which calibrates the ( , |m|) = (2, 2), (2, 1), [START_REF] Abbott | Observation of Gravitational Waves from a Binary Black Hole Merger[END_REF][START_REF] Acernese | Advanced Virgo: a second-generation interferometric gravitational wave detector[END_REF], [START_REF] Abbott | Observation of Gravitational Waves from a Binary Black Hole Merger[END_REF][START_REF] Abbott | Observation of Gravitational Waves from a Binary Black Hole Merger[END_REF] and (4,4) spherical harmonic modes to hybrid waveforms constructed from NR waveforms and information from the PN and effective-one-body (EOB) descriptions for the inspiral. IMRPhenomXHM represents the amplitudes and phases of spherical or spheroidal harmonic modes in terms of piecewise closed form expressions, with coefficients that vary across the compact binary parameter space, which results in extreme compression of the waveform information and computational efficiency.

SEOBNRv4PHM comes from another waveform family that is primarily based on the EOB formalism where the relativistic two-body problem is mapped to motion of a single body in an effective metric. In this framework, analytical information from several sources, such as PN theory and the test-particle limit, is combined in a resummed form. This is complemented with insights from NR simulations that accurately model the strong-field regime and incorporated into the EOB waveforms via a calibration procedure. We use the SEOB-NRv4PHM [START_REF] Ossokine | Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation[END_REF][START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF] model, which includes precession and modes beyond the dominant quadrupole. This model is based on the aligned-spin model SEOBNRv4HM [START_REF] Cotesta | Enriching the Symphony of Gravitational Waves from Binary Black Holes by Tuning Higher Harmonics[END_REF] and is calibrated to NR in that regime. It features full twospin treatment of the precession equations and relies on a twisting-up procedure to map aligned spin waveforms in the co-precessing frame to the precessing waveforms in the inertial frame [START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF].

For GW190917 114630, the less massive component is indicated to lie below 3M and hence to have a strong likelihood of being a NS instead of a BH. Following the discussion for GW190814 [START_REF] Abbott | GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object[END_REF], the nature of the less massive compact object in GW190917 114630 cannot be discerned from the GW data at present. This is primarily dependent on the unequal masses [START_REF] Foucart | First direct comparison of nondisrupting neutron star-black hole and binary black hole merger simulations[END_REF][START_REF] Kumar | Measuring neutron star tidal deformability with Advanced LIGO: a Bayesian analysis of neutron star -black hole binary observations[END_REF][START_REF] Huang | Statistical and systematic uncertainties in extracting the source properties of neutron star -black hole binaries with gravitational waves[END_REF] which will lead the merger of the binary to occur before an eventual NS component could have been tidally disrupted for any realistic NS EoS [START_REF] Foucart | First direct comparison of nondisrupting neutron star-black hole and binary black hole merger simulations[END_REF]. The lack of an observable NS disruption thus removes the potential for the observed signal to contain any additional information above a pointparticle baseline. For this reason, we present results for GW190917 114630 and GW190814 based on the BBH waveform models discussed above.

For GW190425, the only O3a event in this catalog classified as a BNS, we follow the analysis presented in [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF][START_REF] Abbott | GW190425: Observation of a Compact Binary Coalescence with Total Mass ∼ 3.4M[END_REF] and report findings using the IMRPhe-nomP NRTidal waveform model [START_REF] Dietrich | Closed-form tidal approximants for binary neutron star gravitational waveforms constructed from high-resolution numerical relativity simulations[END_REF][START_REF] Dietrich | Matter imprints in waveform models for neutron star binaries: Tidal and self-spin effects[END_REF] which is based upon the BBH model IMRPhenomPv2 [START_REF] Hannam | Simple Model of Complete Precessing Black-Hole-Binary Gravitational Waveforms[END_REF][START_REF] Husa | Frequency-domain gravitational waves from non-precessing black-hole binaries. I. New numerical waveforms and anatomy of the signal[END_REF][START_REF] Khan | Frequency-domain gravitational waves from non-precessing black-hole binaries. II. A phenomenological model for the advanced detector era[END_REF] with the addition of EoS dependent self-spin effects and contributions from tidal interactions tuned against NR and tidal EOB models. In order to reduce computational cost for the analysis of GW190425, a reducedorder-quadrature method was applied to the IMRPhe-nomP NRTidal model used [START_REF] Smith | Fast and accurate inference on gravitational waves from precessing compact binaries[END_REF][START_REF] Baylor | Imrphenompv2 nrtidal gw190425 narrow mc[END_REF].

B. Sampling methods

To represent the continuous posterior probability density functions in ϑ, we draw discrete samples from those distributions using three different methods. For analyses using IMRPhenomXPHM and IMRPhenomP NRTidal we use the Bilby inference package [START_REF] Romero-Shaw | Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue[END_REF][START_REF] Ashton | BILBY: A user-friendly Bayesian inference library for gravitational-wave astronomy[END_REF], together with the nested sampling [START_REF] Skilling | Nested sampling for general bayesian computation[END_REF] method implemented in the Dynesty sampler [START_REF] Speagle | DYNESTY: a dynamic nested sampling package for estimating Bayesian posteriors and evidences[END_REF], or the Markov-chain Monte Carlo sampler implemented in the LALInference package [START_REF] Veitch | Parameter estimation for compact binaries with ground-based gravitational-wave observations using the lalinference software library[END_REF][START_REF] Rover | Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data[END_REF][START_REF] Marc Van Der Sluys | Parameter estimation of spinning binary inspirals using Markov-chain Monte Carlo[END_REF][START_REF]LIGO Algorithm Library[END_REF]. For analyses using SEOBNRv4PHM, we use the RIFT package [START_REF] Pankow | Novel scheme for rapid parallel parameter estimation of gravitational waves from compact binary coalescences[END_REF][START_REF] Lange | Parameter estimation method that directly compares gravitational wave observations to numerical relativity[END_REF][START_REF] Wysocki | Accelerating parameter inference with graphics processing units[END_REF] which, due to a hybrid exploration of the parameter space split into intrinsic (masses and spins) and extrinsic parameters, is better suited for use with this more computationally expensive waveform model. The results from both analyses are collected and presented in a common format using the PE-Summary package [START_REF] Hoy | PESummary: the code agnostic Parameter Estimation Summary page builder[END_REF][START_REF] Hoy | pesummary[END_REF].

C. Priors

The prior probability on ϑ is defined similar to GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] as uniform in spin magnitudes and redshifted component masses (specified in the geocenter rest frame), and isotropic in spin orientations, sky location and orientation of the binary orbit. We also assume uncorrelated and uniform prior probabilities for the tidal deformability parameters of the NSs in GW190425. The prior on the luminosity distance follows a distribution uniform in comoving volume, using a flat ΛCDM cosmology with Hubble constant H 0 = 67.90 km s -1 Mpc -1 and matter density Ω m = 0.3065 [START_REF] Ade | Planck 2015 results. XIII. Cosmological parameters[END_REF]. Masses reported in Sec. V D are defined in the rest frame of the original binary, and computed by dividing the redshifted masses by (1 + z), with z calculated from the same cosmological model. For GW190425 we perform two separate analyses, differing in the spin magnitudes they allow with a low-spin (| χ 1 | < 0.05) and a high-spin (| χ 1 | < 0.89), consistent with the choices made in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] for this binary.

All analyses account for uncertainties in the reported strain calibration [START_REF] Sun | Characterization of systematic error in Advanced LIGO calibration[END_REF][START_REF] Cahillane | Calibration uncertainty for Advanced LIGO's first and second observing runs[END_REF]. The calibration uncertainties are described as frequency-dependent splines, defined separately for the strain amplitude and phase [START_REF] Farr | Modelling Calibration Errors In CBC Waveforms[END_REF]. The coefficients at the spline nodes are allowed to vary alongside the binary signal parameters according to a Gaussian prior distribution set by the measured uncertainty at each node [START_REF] Abbott | Properties of the Binary Black Hole Merger GW150914[END_REF]. For analyses performed with the LALInference or Bilby inference packages, calibration uncertainties are marginalized over through direct sampling of the spline coefficients whereas RIFT analyses implement a likelihood reweighting method through importance sampling over an initial analysis where perfect calibration is assumed [START_REF] Payne | Gravitational-wave astronomy with a physical calibration model[END_REF].

D. Source properties

In this subsection we report the inferred source properties of the 8 new events reported in Table II. The source properties for the BBH events from the first and second observation runs, reported in GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF], together with the remaining 36 events from Table II are reported in Appendix A. For the vast majority of the events reported both in this section and in Appendix A, the quoted source properties are taken from a set of posterior samples constructed from the two IMRPhenomXPHM and SEOBNRv4PHM analyses with each given equal weight. For a subset of events (GW151226, GW190413 052954, GW190413 134308, GW190421 213856, GW190426 190642, GW190521, GW190602 175927, GW190719 215514, GW190725 174728, GW190803 022701, GW190814, GW190828 063405, GW190828 065509, GW190917 114630, GW190926 050336 and GW190929 012149) the respective SEOBNRv4PHM analyses were incomplete at the time of journal submission, hence we report results from the IMRPhe-nomXPHM only for these events.

A selection of the one-dimensional marginal posterior distributions are shown in Fig. 3, with two-dimensional projections on the M -q and M-χ eff planes in Fig. 4 and Fig. 5 respectively. A more detailed set of results are presented in Table VI in the form of median and 90% credible intervals for the one-dimensional marginal posterior distributions for all 8 events. The complete multidimensional posterior distributions are available as part of the public data release accompanying this paper [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Parameter Estimation Data Release[END_REF], as detailed further in Sec. VII. Median and 90% symmetric credible intervals for the one-dimensional marginal posterior distributions on selected source parameters for the 8 events that are new to this catalog with pastro > 0.5, highlighted in bold in Table II. The columns show source total mass M , chirp mass M and component masses mi, dimensionless effective inspiral spin χ eff , luminosity distance DL, redshift z, final mass M f , final spin χ f , sky localization ∆Ω and the network matched-filter SNR. The sky localization is the area of the 90% credible region. All quoted results are calculated from a set of posterior samples drawn with equal weight from the IMRPhenomXPHM and SEOBNRv4PHM analyses, with the exception of the SNRs that are taken from the IMRPhenomXPHM analysis alone (as RIFT, which was used for the SEOBNRv4PHM analysis, does not output that quantity). Additionally, following Sec. V D, the results presented for GW190426 190642, GW190725 174728, GW190917 114630 and GW190926 050336 are taken from an analysis using the IMRPhenomXPHM model only. A subset of the one-dimensional posterior distributions are visualized in Fig. 3. Two-dimensional projections of the 90% credible regions in the M -q and M-χ eff planes are shown in Fig. 4 and Fig. 5. 3. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 8 events that are new to this catalog with pastro > 0.5, highlighted in bold in Table II. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in Table VI.

Event M (M ) M (M ) m1 (M ) m2 (M ) χ eff DL (Gpc) z M f (M ) χ f ∆Ω (deg 2 ) SNR GW190403

Masses

The masses inferred for the 8 events presented in this section are generally comparable to, or higher, than the binaries reported in GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], as shown in Fig. 4. We find that the most massive BBH in GWTC-2.1 is GW190426 190642 with a total mass of 182.3 +40.2 -35.7 M and a remnant mass of 172.9 +37.7 -33.6 M ; it probably supersedes the previous most massive BBH GW190521 2 with total mass of 153.1 +42.2 -16.2 M and a remnant mass of 147.4 +40.0 -16.0 M as reported in Appendix A 2. Both GW190426 190642 and GW190403 051519 join GW190519 153544, GW190521, GW190602 175927 and GW190706 222641 in a population of BBHs with over 50% posterior support for total mass M > 100M [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF].

While the majority of the new events show a preference for mass ratios near unity, following the trend already observed in GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], both GW190403 051519 and GW190917 114630 recover posteriors with median q ∼ 1/5 with q = 0.23 +0. 60 -0.12 and q = 0.21 +0.32 -0.09 respectively. As shown in Fig. 4, this constraint for unequal masses is robust at the 90% credible level for both GW190403 051519 and GW190917 114630. Although the contour indicating the 90% credible region for GW190403 051519 includes support at q ∼ 0 in Fig. 4, this is an artefact of the bounded kernel density estimation used to construct the contours, and for this event there are no samples at the prior boundary of q = 0.05.

Spins

The best measured spin parameter for CBCs with observable inspiral signals tends to be the effective inspiral spin χ eff [START_REF] Pürrer | Can we measure individual black-hole spins from gravitational-wave observations?[END_REF][START_REF] Vitale | Parameter estimation for heavy binary-black holes with networks of second-generation gravitationalwave detectors[END_REF][START_REF] Ken | Gravitational-wave astrophysics with effectivespin measurements: asymmetries and selection biases[END_REF], introduced in Eq. ( 2), which is approximately conserved under spin-induced precession of the binary orbit [START_REF] Blanchet | Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries[END_REF][START_REF] Racine | Analysis of spin precession in binary black hole systems including quadrupolemonopole interaction[END_REF][START_REF] Michael Kesden | Effective potentials and morphological transitions for binary black-hole spin precession[END_REF][START_REF] Gerosa | Multitimescale analysis of phase transitions in precessing black-hole binaries[END_REF]. Consequently, the angles between the spin-vectors and the orbital angular momentum at a formally infinite separation are well defined [START_REF] Gerosa | Multitimescale analysis of phase transitions in precessing black-hole binaries[END_REF]. We therefore report χ eff , as well as the spin tilt angles themselves, at this fiducial reference point of infinite binary separation, or equivalently at an infinite time before the binary merger. The spins are evolved to infinite separation [START_REF] Nathan | Inferring spin tilts at formation from gravitational wave observations of binary black holes: Interfacing precession-averaged and orbit-averaged spin evolution[END_REF] using a precession-averaged evolution scheme [START_REF] Chatziioannou | Constructing Gravitational Waves from Generic Spin-Precessing Compact Binary Inspirals[END_REF][START_REF] Gerosa | Multitimescale analysis of phase transitions in precessing black-hole binaries[END_REF] where the orbital angular momentum is computed using higher-order PN expressions.

The posterior distributions for χ eff for all 8 events are shown in Fig. 3 and Fig. 5. Again, the majority of the binaries are consistent with containing two non-spinning BHs with only GW190403 051519 and GW190805 211137 recovering a non-zero χ eff at 90% credibility. Both binaries report predominantly positive χ eff , further strengthening the pattern of a surplus of events with χ eff > 0 relative to those with χ eff < 0 reported in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] and investigated further in a companion paper [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF].

Similar to the compact objects reported in GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], the majority of the compact-object spins reported in GWTC-2.1 have magnitudes consistent with zero. Two of the new events show evidence for large BH spins. In the case of GW190403 051519, 82% of the posterior probability lies in a region where at least one of the component spin magnitudes is above 0.8 whereas for GW190805 211137 this holds for 59% of the posterior probability.

For binaries with very unequal masses, measurements of χ eff can translate into strong measurement constraints of χ 1 , the spin magnitude of the more massive object, whose spin angular momentum dominates over the secondary. This is the case for GW190403 051519, whose primary dimensionless spin is measured to be χ 1 = 0.89 +0.09 -0.31 . This represents the most nearly-extremal spin observed using GWs. Similarly, GW190805 211137 is recovered with χ 1 = 0.75 +0.22 -0.59 and GW190917 114630 with χ 1 = 0.23 +0. 63 -0.21 . Both GW190403 051519 and GW190805 211137 are recovered as strongly preferring large χ 1 , with the inferred posterior distributions railing against the extremal BH-spin bound at χ 1 = 1. Hence, we also report the one-sided 90% lower bounds of χ 1 > 0.69 for GW190403 051519 and χ 1 > 0.29 for GW190805 211137. The posterior distributions for the spin magnitudes and tilt angles for these three events are shown in Fig. 6.

Three-Dimensional Localization

As the 8 new events are all detected at relatively modest SNRs, together with several identifications as highmass BBHs, the inferred luminosity distances D L are generally larger than the binaries from GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. GW190403 051519 is identified as probably the most distant event, with a recovered D L = 8.28 +6. 72 -4.29 Gpc corresponding to a redshift z = 1.18 +0. 73 -0.53 approximately twice as distant as the most distant events that were reported in GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] as also shown in Appendix A 2. In addition GW190426 190642, GW190805 211137, GW190916 200658 and GW190926 050336 all have inferred distances comparable to, or larger than, GW190413 134308, further highlighting the access to the distant Universe provided in GWTC-2.1.

Another effect of the modest SNR of the new events is their comparatively poor localization on the sky. The best localized event is GW190805 211137 with a 90% credible region of ∆Ω = 1600 deg 2 . The credible intervals for the inferred distances and sky areas are shown in Table VI. The inferred localizations for all events are available as part of the accompanying data release to this paper, detailed further in Sec. VII.

Waveform comparisons -Model systematics

The use of both the IMRPhenomXPHM [START_REF] Pratten | Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes[END_REF][START_REF] Pratten | Setting the cornerstone for a family of models for gravitational waves from compact binaries: The dominant harmonic for nonprecessing quasicircular black holes[END_REF][START_REF] García-Quirós | Multimode frequency-domain model for the gravitational wave signal from nonprecessing black-hole binaries[END_REF][START_REF] García-Quirós | Accelerating the evaluation of inspiral-merger-ringdown waveforms with adapted grids[END_REF] and SEOBNRv4PHM [START_REF] Ossokine | Multipolar Effective-One-Body Waveforms for Precessing Binary Black Holes: Construction and Validation[END_REF][START_REF] Babak | Validating the effective-one-body model of spinning, precessing binary black holes against nu-merical relativity[END_REF][START_REF] Pan | Inspiralmerger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism[END_REF] models in the analyses of these events are motivated by the need to capture, and account for, potential differences in the inferred source parameters caused by the different methods used in the constructions of the models themselves. The vast majority of the posterior distributions reported in this section are constructed by combining an equal number of samples drawn from each of the IMRPhenomXPHM and SEOB-NRv4PHM analyses [START_REF] Abbott | Properties of the Binary Black Hole Merger GW150914[END_REF]. For the majority of the 8 new events, the differences between the two single-model analyses, as well as to the combined-model results, are found to be comparable to the impact of model systematics effects identified in GWTC-2 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] being generally subdominant to the statistical uncertainty caused by the noisy data. For GW190403 051519 there are, however, slight differences identified between the IMRPhenomX-PHM and SEOBNRv4PHM analyses, most noticeably in the shape and structure of the marginal posterior distribution of some of the recovered mass and spin parameters. In these cases, the differences between analyses using either the IMRPhenomXPHM or SEOBNRv4PHM models are dominating over the other systematic uncertainties of the analysis, such as the estimation of the noise PSD. A deeper investigation into the broader impact of these model systematic effects, and their impact on the inferred source parameters for the population of GW events presented here, is left for a future study.

Comparison to 3-OGC

Out of the 8 new events presented in this section, GW190725 174728, GW190916 200658, GW190925 232845 and GW190926 050336 were also independently identified and analyzed as part of 3-OGC [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF] using the PyCBC Inference package [START_REF] Biwer | PyCBC Inference: A Python-based parameter estimation toolkit for compact binary coalescence signals[END_REF] and the IMRPhenomXPHM waveform model. We compare the inferred source properties for these events as presented in 3-OGC [START_REF] Nitz | 3-OGC: Catalog of gravitational waves from compact-binary mergers[END_REF] and, to minimize potential model systematic effects, the IMRPhenomXPHM analysis performed for GWTC-2.1 presented here. Overall, we find a broad agreement between the two analyses. While there are differences found in the two sets of posterior distributions, they appear consistent within expectations from the differing choices of the analysis configurations and the assumed prior distributions between the two analyses for low SNR signals [START_REF] Huang | Source properties of the lowest signal-to-noise-ratio binary black hole detections[END_REF].

VI. ASTROPHYSICAL IMPLICATIONS

Our analysis reports 8 new candidates with p astro > 0.5 in at least one pipeline. None of these candidates have p astro equal to 1 (Table II). Four of them were found only by a single analysis, and none were detected by all the pipelines (Table II). As discussed above in Sec. III A, p astro values are subject to statistical uncertainties, and are also subject to uncertainties arising from the true rate and distribution of signals. Such uncertainties are larger for events which, if astrophysical, fall within populations with few or zero significant detections. Here, we highlight such uncertainties for specific candidates, and discuss possible astrophysical implications under the hypothesis that the candidates do originate from compact object mergers.

Parameter estimation indicates that two of the new candidates, GW190403 051519 and GW190426 190642, if astrophysical, have sources with a large total mass ( 100 M , Table VI). Both were found only by the PyCBC-BBH analysis with a low SNR and relatively low p astro . They were also not recovered as significant events in the focused search of O3 data for intermediate-mass BH binaries [START_REF] Abbott | Search for intermediate-mass black hole binaries in the third observing run of Advanced LIGO and Advanced Virgo[END_REF]. Since there is only one significant de-tection to date of a comparable BBH system, GW190521 [START_REF] Abbott | GW190521: A Binary Black Hole Merger with a Total Mass of 150 M[END_REF][START_REF] Abbott | Properties and astrophysical implications of the 150 M binary black hole merger GW190521[END_REF], the calculation of p astro for these candidates is subject to significant potential systematic error. These events are confidently above the break mass in the broken power law mass distribution model, at 39.7 +20.3 -9.1 M , or the Gaussian in the Power Law + Peak model at 33.1 +4.0 -5.6 M [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF][START_REF] Fishbach | Where Are LIGO's Big Black Holes?[END_REF][START_REF] Talbot | Measuring the Binary Black Hole Mass Spectrum with an Astrophysically Motivated Parameterization[END_REF]. The estimated primary component masses, assuming astrophysical origin, are both above the lower edge of the pair-instability mass gap m low [START_REF] Wang | Black Hole Mass Function of Coalescing Binary Black Hole Systems: Is There a Pulsational Pair Instability Mass Cutoff?[END_REF][START_REF] Li | A Flexible Gaussian Process Reconstruction Method and the Mass Function of the Coalescing Binary Black Hole Systems[END_REF][START_REF] Edelman | Poking Holes: Looking for Gaps in LIGO/Virgo's Black Hole Population[END_REF][START_REF] Baxter | Find the Gap: Black Hole Population Analysis with an Astrophysically Motivated Mass Function[END_REF], even considering the large uncertainties about its value (≈ 40-70M , [START_REF] Woosley | Pulsational Pair-instability Supernovae[END_REF][START_REF] Woosley | The Evolution of Massive Helium Stars, Including Mass Loss[END_REF][START_REF] Stevenson | The Impact of Pair-instability Mass Loss on the Binary Black Hole Mass Distribution[END_REF][START_REF] Farmer | Mind the Gap: The Location of the Lower Edge of the Pair-instability Supernova Black Hole Mass Gap[END_REF][START_REF] Farmer | Constraints from Gravitationalwave Detections of Binary Black Hole Mergers on the 12 C(α, γ) 16 O Rate[END_REF][START_REF] Mapelli | Impact of the Rotation and Compactness of Progenitors on the Mass of Black Holes[END_REF][START_REF] Marchant | The impact of stellar rotation on the black hole mass-gap from pairinstability supernovae[END_REF][START_REF] Costa | Formation of GW190521 from stellar evolution: the impact of the hydrogen-rich envelope, dredge-up, and 12 C(α, γ) 16 O rate on the pair-instability black hole mass gap[END_REF][START_REF] Farrell | Is GW190521 the merger of black holes from the first stellar generations?[END_REF]). Adopting a rather conservative estimate of m low = 65M , the primary component of GW190403 051519 (m 1 = 85.0 +27.8 -33.0 M ) has a probability 0.16 of being below m low with our standard mass prior, while the primary and secondary components of GW190426 190642 (m 1 = 105.5 +45. 3 -24.1 M and m 2 = 76.0 +26.2 -36.5 M ) are below m low with probabilities of 0.00078 and 0.30, respectively. The upper edge of the mass gap is even more uncertain, with theoretical predictions suggesting m up ≈ 120 M [START_REF] Spera | Very massive stars, pair-instability supernovae and intermediate-mass black holes with the sevn code[END_REF][START_REF] Renzo | Predictions for the hydrogen-free ejecta of pulsational pair-instability supernovae[END_REF]. The primary mass component of GW190403 051519 (GW190426 190642) has a probability 0.02 (0.25) of being above this value of m up . Thus, if astrophysical, GW190403 051519 and GW190426 190642 lie in the same group with GW190521: their primary components might be either inside or above the mass gap. Moreover, the estimated final mass of the merger remnant of GW190426 190642 (M f = 172.9 +37.7 -33.6 M ) is in the intermediate-mass black hole regime (10 2 -10 5 M ).

These features are suggestive of a dynamical formation channel, such as the hierarchical merger of smaller BHs [START_REF] Miller | Production of intermediate-mass black holes in globular clusters[END_REF][START_REF] Antonini | Merging Black Hole Binaries in Galactic Nuclei: Implications for Advanced-LIGO Detections[END_REF][START_REF] Gerosa | Are merging black holes born from stellar collapse or previous mergers?[END_REF][START_REF] Fishbach | Are LIGO's Black Holes Made from Smaller Black Holes?[END_REF][START_REF] Antonini | Black hole growth through hierarchical black hole mergers in dense star clusters: implications for gravitational wave detections[END_REF][START_REF] Carl | Black holes: The next generation-repeated mergers in dense star clusters and their gravitational-wave properties[END_REF][START_REF] Kimball | Black Hole Genealogy: Identifying Hierarchical Mergers with Gravitational Waves[END_REF][START_REF] Fragione | On the Origin of GW190521-like Events from Repeated Black Hole Mergers in Star Clusters[END_REF][START_REF] Doctor | Black Hole Coagulation: Modeling Hierarchical Mergers in Black Hole Populations[END_REF][START_REF] Palmese | GW190521 from the Merger of Ultradwarf Galaxies[END_REF][START_REF] Baibhav | The mass gap, the spin gap, and the origin of merging binary black holes[END_REF][START_REF] Mapelli | Hierarchical black hole mergers in young, globular and nuclear star clusters: the effect of metallicity, spin and cluster properties[END_REF] or repeated stellar collisions in dense star clusters [START_REF] Di Carlo | Merging black holes in young star clusters[END_REF][START_REF] Di Carlo | Binary black holes in the pair instability mass gap[END_REF][START_REF] Kremer | Populating the Upper Black Hole Mass Gap through Stellar Collisions in Young Star Clusters[END_REF][START_REF] Renzo | The Stellar Merger Scenario for Black Holes in the Pair-instability Gap[END_REF]. In active galactic nuclei, the dense gaseous disk surrounding the central BH also triggers the hierarchical assembly of BHs [START_REF] Mckernan | Intermediate mass black holes in AGN discs -I. Production and growth[END_REF][START_REF] Bartos | Rapid and Bright Stellar-mass Binary Black Hole Mergers in Active Galactic Nuclei[END_REF][START_REF] Nicholas | Assisted inspirals of stellar mass black holes embedded in AGN discs: solving the 'final au problem[END_REF][START_REF] Barry Mckernan | Constraining Stellar-mass Black Hole Mergers in AGN Disks Detectable with LIGO[END_REF][START_REF] Yang | Hierarchical Black Hole Mergers in Active Galactic Nuclei[END_REF][START_REF] Tagawa | Spin Evolution of Stellar-mass Black Hole Binaries in Active Galactic Nuclei[END_REF][START_REF] Tagawa | Massgap Mergers in Active Galactic Nuclei[END_REF]. Alternatively, extreme gas accretion from a dense gaseous disk [START_REF] Roupas | Generation of massive stellar black holes by rapid gas accretion in primordial dense clusters[END_REF][START_REF] Safarzadeh | Formation of GW190521 via Gas Accretion onto Population III Stellar Black Hole Remnants Born in Highredshift Minihalos[END_REF][START_REF] Rice | Growth of Stellarmass Black Holes in Dense Molecular Clouds and GW190521[END_REF] or from a stellar companion [START_REF] Van Son | Polluting the Pairinstability Mass Gap for Binary Black Holes through Super-Eddington Accretion in Isolated Binaries[END_REF] might assist the growth of BH mass above the pair-instability threshold. Finally, primordial BHs might also have masses in the pair-instability gap [START_REF] Clesse | GW190425, GW190521 and GW190814: Three candidate mergers of primordial black holes from the QCD epoch[END_REF][START_REF] De Luca | GW190521 Mass Gap Event and the Primordial Black Hole Scenario[END_REF]. However, even the formation of BHs in this mass range from stellar collapse cannot be excluded, given the large uncertainties in stellar-evolution models [START_REF] Farmer | Constraints from Gravitationalwave Detections of Binary Black Hole Mergers on the 12 C(α, γ) 16 O Rate[END_REF][START_REF] Costa | Formation of GW190521 from stellar evolution: the impact of the hydrogen-rich envelope, dredge-up, and 12 C(α, γ) 16 O rate on the pair-instability black hole mass gap[END_REF][START_REF] Farrell | Is GW190521 the merger of black holes from the first stellar generations?[END_REF][START_REF] Belczynski | Evolutionary roads leading to low effective spins, high black hole masses, and O1/O2 rates for LIGO/Virgo binary black holes[END_REF][START_REF] Croon | New physics and the black hole mass gap[END_REF][START_REF] Woosley | The Pair-Instability Mass Gap for Black Holes[END_REF]. For example, very massive ( 230 M ) extremely metal-poor (Z < 10 -4 ) stars might turn into BHs with mass above the pair-instability gap [START_REF] Madau | Massive black holes as Population III remnants[END_REF][START_REF] Woosley | The evolution and explosion of massive stars[END_REF][START_REF] Tanikawa | Population III binary black holes: effects of convective overshooting on formation of GW190521[END_REF][START_REF] Kinugawa | Formation of binary black holes similar to GW190521 with a total mass of ∼ 150 M from Population III binary star evolution[END_REF].

Parameter-estimation analysis indicates a large positive value of the effective inspiral spin χ eff = 0.68 +0.16 -0.43 and of the primary's spin magnitude χ 1 = 0.89 +0.09 -0.31 for GW190403 051519. From a theoretical perspective, BH spin magnitudes are highly uncertain [START_REF] Belczynski | Evolutionary roads leading to low effective spins, high black hole masses, and O1/O2 rates for LIGO/Virgo binary black holes[END_REF][START_REF] Bavera | The origin of spin in binary black holes. Predicting the distributions of the main observables of Advanced LIGO[END_REF], with some models [START_REF] Fuller | Slowing the spins of stellar cores[END_REF][START_REF] Fuller | Most Black Holes Are Born Very Slowly Rotating[END_REF] predicting very low spins (∼ 0.01) for single BHs because of efficient angular momentum transport in the stellar interior [START_REF] Spruit | Dynamo action by differential rotation in a stably stratified stellar interior[END_REF]. Observations of high-mass X-ray binaries in the local Universe indicate that BH spins can be nearly maximal [START_REF] Reynolds | Observational Constraints on Black Hole Spin[END_REF][START_REF] James | Cygnus X-1 contains a 21-solar mass black hole-Implications for massive star winds[END_REF], while the majority of mergers in GWTC-2 are associated with low values of χ eff , with a slight preference 4. Contours representing the 90% credible regions in the total mass M and mass ratio q plane for all events reported in this catalog. The events that are new to this catalog with pastro > 0.5, highlighted in bold in Table II, are highlighted in this figure following the same color scheme used in Fig. 3. The dashed lines act to separate regions where the primary and secondary binary component can have a mass below 3M .

q m 1 = 3 M m 2 = 3M GW190403 051519 GW190426 190642 GW190725 174728 GW190805 211137 GW190916 200658 GW190917 114630 GW190925 232845 GW190926 050336 FIG.
for positive values [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF]. Even if single stars form BHs with low spins [START_REF] Fuller | Most Black Holes Are Born Very Slowly Rotating[END_REF], BHs in binaries may still develop high spins because of mass transfer [START_REF] Qin | On the Origin of Black Hole Spin in High-mass X-Ray Binaries[END_REF], tidal interactions [START_REF] Bavera | The origin of spin in binary black holes. Predicting the distributions of the main observables of Advanced LIGO[END_REF][START_REF] Hotokezaka | Implications of the Low Binary Black Hole Aligned Spins Observed by LIGO[END_REF][START_REF] Qin | The spin of the second-born black hole in coalescing binary black holes[END_REF], or chemically homogeneous evolution [START_REF] Marchant | A new route towards merging massive black holes[END_REF][START_REF] Mandel | Merging binary black holes formed through chemically homogeneous evolution in short-period stellar binaries[END_REF]. Alternatively, BHs born from the merger of two smaller BHs are expected to have high natal spins (∼ 0.7-0.9, [START_REF] Hofmann | The final spin from binary black holes in quasicircular orbits[END_REF][START_REF] Jiménez-Forteza | Hierarchical data-driven approach to fitting numerical relativity data for nonprecessing binary black holes with an application to final spin and radiated energy[END_REF][START_REF] Nathan | Determining the final spin of a binary black hole system including in-plane spins: Method and checks of accuracy[END_REF]). This might suggest that the primary component of GW190403 051519 is a secondgeneration BH, which is also consistent with its large mass [START_REF] Gerosa | Are merging black holes born from stellar collapse or previous mergers?[END_REF][START_REF] Fishbach | Are LIGO's Black Holes Made from Smaller Black Holes?[END_REF][START_REF] Mapelli | Hierarchical black hole mergers in young, globular and nuclear star clusters: the effect of metallicity, spin and cluster properties[END_REF][START_REF] Kimball | What GW170729's Exceptional Mass and Spin Tells Us about Its Family Tree[END_REF][START_REF] Gerosa | Hierarchical mergers of stellar-mass black holes and their gravitationalwave signatures[END_REF]. However, the positive effective inspiral spin χ eff of GW190403 051519 indicates a significant alignment of the spin vectors of (any of) the two components with the orbital angular momentum vector of the BBH. Nearly aligned spins are preferentially associated with isolated binary evolution [START_REF] Kalogera | Spin-Orbit Misalignment in Close Binaries with Two Compact Objects[END_REF][START_REF] Gerosa | Spin orientations of merging black holes formed from the evolution of stellar binaries[END_REF], while dynamically formed binaries tend to have an isotropically distributed spin orientations [START_REF] Carl | Illuminating Black Hole Binary Formation Channels with Spins in Advanced LIGO[END_REF][START_REF] Farr | Distinguishing spin-aligned and isotropic black hole populations with gravitational waves[END_REF].

Finally, GW190403 051519 is associated with a comparatively small mass ratio q (Fig. 3). Such low values of the mass ratio are unusual in isolated binary evolution, especially for the chemically homogeneous evolution [START_REF] Marchant | A new route towards merging massive black holes[END_REF][START_REF] De Mink | The chemically homogeneous evolutionary channel for binary black hole mergers: rates and properties of gravitational-wave events detectable by advanced LIGO[END_REF] but also for the common-envelope scenario [START_REF] Belczynski | Evolutionary roads leading to low effective spins, high black hole masses, and O1/O2 rates for LIGO/Virgo binary black holes[END_REF][START_REF] Dominik | Double Compact Objects. I. The Significance of the Common Envelope on Merger Rates[END_REF][START_REF] Eldridge | BPASS predictions for binary black hole mergers[END_REF][START_REF] Giacobbo | The progenitors of compact-object binaries: impact of metallicity, common envelope and natal kicks[END_REF][START_REF] Coenraad | The effect of the metallicity-specific star formation history on double compact object mergers[END_REF]. In contrast, low mass ratios are expected if the primary and secondary components are a secondand a first-generation BH, respectively [START_REF] Carl | Black holes: The next generation-repeated mergers in dense star clusters and their gravitational-wave properties[END_REF][START_REF] Kimball | Black Hole Genealogy: Identifying Hierarchical Mergers with Gravitational Waves[END_REF][START_REF] Doctor | Black Hole Coagulation: Modeling Hierarchical Mergers in Black Hole Populations[END_REF], or if the primary BH is the result of a stellar merger in a young star cluster [START_REF] Di Carlo | Binary black holes in the pair instability mass gap[END_REF].

Four of the other new candidates (GW190805 211137, GW190916 200658, GW190925 232845, GW190926 050336) fall in the mass range of the bulk of GWTC-2 BBHs, while the secondary component of GW190725 174728 has a 0.18 probability of lying in the lower mass gap (∼ 2-5 M ). The existence of a lower mass gap was inferred from observations of Galactic X-ray binaries [START_REF] Bailyn | The Mass Distribution of Stellar Black Holes[END_REF][START_REF] Özel | The Black Hole Mass Distribution in the Galaxy[END_REF][START_REF] Farr | The Mass Distribution of Stellar-mass Black Holes[END_REF], but there are a few observations of BHs with mass ≈ 3-4 M in non-interacting binary systems [START_REF] Thompson | Response to Comment on "A noninteracting low-mass black holegiant star binary system[END_REF][START_REF] Jayasinghe | A unicorn in monoceros: the 3 M dark companion to the bright, nearby red giant V723 Mon is a non-interacting, mass-gap black hole candidate[END_REF] and microlensing surveys find no evidence for a mass gap between NSs and BHs [START_REF] Wyrzykowski | Black hole, neutron star and white dwarf candidates from microlensing with OGLE-III[END_REF][START_REF] Wyrzykowski | Constraining the masses of microlensing black holes and the mass gap with Gaia DR2[END_REF]. GWTC-2 BBH observations also suggest a dearth of systems between 2.6 M and 6 M [START_REF] Abbott | Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog[END_REF][START_REF] Fishbach | Does Matter Matter? Using the Mass Distribution to Distinguish Neutron Stars and Black Holes[END_REF]. The only confirmed GW event in GWTC-2 with a component in the lower mass gap is GW190814 [START_REF] Abbott | GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object[END_REF]. Numerical and theoretical models do not exclude the formation of compact objects in this mass range from a core-collapse supernova [START_REF] Fryer | Compact Remnant Mass Function: Dependence on the Explosion Mechanism and Metallicity[END_REF][START_REF] Limongi | Presupernova Evolution and Explosive Nucleosynthesis of Rotating Massive Stars in the Metallicity Range -3 ≤ [Fe/H] ≤ 0[END_REF][START_REF] Michael Zevin | Exploring the Lower Mass Gap and Unequal Mass Regime in Compact Binary Evolution[END_REF][START_REF] Mandel | Simple recipes for compact remnant masses and natal kicks[END_REF]. Other scenarios to explain the formation of binary compact objects in this mass range include mergers in multiple systems [START_REF] Gupta | Black holes in the low-mass gap: Implications for gravitational-wave observations[END_REF][START_REF] Liu | Hierarchical black hole mergers in multiple systems: constrain the formation of GW190412-, GW190814-, and GW190521-like events[END_REF][START_REF] Lu | On the formation of GW190814[END_REF][START_REF] Arca | Dynamical Formation of the GW190814 Merger[END_REF], primordial BHs [START_REF] Clesse | GW190425, GW190521 and GW190814: Three candidate mergers of primordial black holes from the QCD epoch[END_REF][START_REF] Vattis | Could the 2.6 M object in GW190814 be a primordial black hole?[END_REF] and mass accretion onto a neutron star [START_REF] Safarzadeh | A Common Origin for Low-mass Ratio Events Observed by LIGO and Virgo in the First Half of the Third Observing Run[END_REF].

Finally, GW190917 114630 has component masses consistent with an NSBH (m 1 = 9.7 +3. 4 -3.9 M , m 2 = 2.1 +1.1 -0.4 M ), but was identified only as a BBH candidate, with p NSBH = 0 and p BBH = 0.77, by the pipeline that detected it (GstLAL). Since GW190426 152155 is a marginal candidate in this catalog, due to its low p astro (Table IV), GW190917 114630 is the only highprobability candidate with mass components in the NSBH range. However, as discussed in Sec. IV A, had it been classified as an NSBH to begin with, its p astro measured by GstLAL would have been smaller due to the lower foreground rate of NSBHs as compared to BBHs in the detection pipelines, and not passed the threshold of 0.5 considered by the follow-up pipelines. As with the unusually high-mass BBH candidates, the assignment of p astro for NSBHs is subject to potential systematic error since no NSBH events have been confidently detected in the data set up to O3a used here, although see [START_REF] Abbott | GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run[END_REF][START_REF] Abbott | Observation of Gravitational Waves from Two Neutron Star-Black Hole Coalescences[END_REF] for NSBH discoveries in O3b. The masses and effective inspiral spin of this candidate are consistent with prior expectations for NSBH systems [START_REF] Dominik | Double Compact Objects. I. The Significance of the Common Envelope on Merger Rates[END_REF][START_REF] Belczynski | A Comprehensive Study of Binary Compact Objects as Gravitational Wave Sources: Evolutionary Channels, Rates, and Physical Properties[END_REF][START_REF] Eldridge | A consistent estimate for gravitational wave and electromagnetic transient rates[END_REF][START_REF] Mapelli | The properties of merging black holes and neutron stars across cosmic time[END_REF][START_REF] Rastello | Dynamics of black hole-neutron star binaries in young star clusters[END_REF][START_REF] Chattopadhyay | Modelling neutron star-black hole binaries: future pulsar surveys and gravitational wave detectors[END_REF][START_REF] Drozda | Black hole -neutron star mergers: the first mass gap and kilonovae[END_REF][START_REF] Floor | Impact of massive binary star and cosmic evolution on gravitational wave observations I: black hole-neutron star mergers[END_REF]. Inferring the impact on the overall population of binary compact objects of the new candidates, including those with non-negligible probability of noise origin, requires a more involved analysis which is beyond this scope of this work [START_REF] Gaebel | Digging the population of compact binary mergers out of the noise[END_REF][START_REF] Galaudage | Gravitational-wave inference in the catalog era: evolving priors and marginal events[END_REF].

VII. CONCLUSION

We have presented GWTC-2.1, which includes results from a refined search for CBCs in the first part of the third observing run of the Advanced LIGO and Advanced Virgo detectors. This is an extension to the previous GW catalog, GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF], over the same data, and provides a deeper list of GW candidates. The search we presented here was carried out using three matched-filter pipelines, MBTA, GstLAL, and PyCBC, and includes a list of candidates that have a FAR less than 2 per day in any of the pipelines. We provide detailed source properties of the 8 events that have p astro greater than 0.5 and were not present in GWTC-2. In addition, the source properties of previously reported events with p astro greater than 0.5 are presented in Appendix A.

Out of the 8 new candidates presented here, all events have masses consistent with BBH sources with the exception of GW190917 114630, whose source masses are consistent with being an NSBH (Sec. V D). If astrophysical, these events expand the scope of observed BBHs, with several binaries inferred at larger distances than previous detections and with both a new broader range of recovered BH masses and the addition of two binaries with significantly unequal masses. The primary components of two of the new candidates (GW190403 051519 and GW190426 190642) lie inside or, less likely, above the pair-instability mass gap. GW190403 051519 also shows support for high spin, unequal masses, and remnant mass in the intermediate-mass BH regime. These features are suggestive of dynamical formation, by hierarchical BH merger or by stellar collisions in dense stellar clusters or active galactic nuclei. However, we cannot exclude that GW190403 051519 and GW190426 190642 originated from isolated binary systems, because of the large uncertainties in the mass range of the pair-instability mass gap. Among the new candidates, GW190725 174728 shows some support for a secondary component mass in the lower mass gap (2-5M ). GW190917 114630, the 5. Contours representing the 90% credible regions in the plane of chirp mass M and effective inspiral spin χ eff for all events reported in this catalog. The events that are new to this catalog with pastro > 0.5, highlighted in bold in Table II, are highlighted in this figure following the same color scheme used in Fig. 3.

0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • 0.0 0.2 0.4 0.6 0.8 0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • GW190403 051519 c S1/(Gm 2 1 ) c S2/(Gm 2 2 ) 0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • 0.0 0.2 0.4 0.6 0.8 0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • GW190805 211137 c S1/(Gm 2 1 ) c S2/(Gm 2 2 ) 0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • 0.0 0.2 0.4 0.6 0.8 0 • 3 0 • 6 0 • 90 • 1 2 0 • 1 5 0 • 180 • GW190917 114630 c S1/(Gm 2 1 ) c S2/(Gm 2 2 )
FIG. 6. The dimensionless spin parameters χi = c Si/(Gm 2 i ) estimated for individual binary components of selected sources. The radial distance of a given pixel on the left (right) of each disk, away from the center of the circle, corresponds to | χ| for the more (less) massive compact object. Each pixel's angle from the vertical axis represents θLS, the angle between the spin vector S and the Newtonian orbital angular momentum. All pixels have equal prior probability with the shading denoting the relative posterior probability of the pixels, after marginalization over azimuthal angles. The events follow the same color scheme used in Fig. 3.

only candidate with component masses consistent with an NSBH was initially classified as a BBH by the search pipeline, and therefore the p astro assigned to it is subject to systematics due to uncertainty in classification.

The data products associated with GWTC-2.1 include candidate information from relevant search pipeline(s) and localizations for all events that pass a threshold of 2 per day in any search pipeline. The information from each search pipeline includes the template mass and spin parameters, the SNR time series, chi-squared values, the time and phase of coalescence in each detector, FAR, and p astro (Sec. III A). These data can be found at [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Candidate Data Release[END_REF]. The source localizations are computed using the rapid localization tool BAYESTAR [START_REF] Singer | Rapid Bayesian position reconstruction for gravitational-wave transients[END_REF][START_REF] Leo | Going the Distance: Mapping Host Galaxies of LIGO and Virgo Sources in Three Dimensions Using Local Cosmography and Targeted Follow-up[END_REF], which was also used to produce the localizations in near real time during the observing runs while sending out GW alerts. We also release the results of the search pipelines running over simulated signal sets classified as BNS, NSBH, and BBH [START_REF]GWTC-2.1: Deep extended-catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Sensitivity of search pipelines to simulated signals[END_REF] that were used to calculate the sensitivities shown in Table V. For candidates that have a p astro > 0.5, we perform follow-up parameter estimation and also release the posterior samples associated with these events. These are available via [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Parameter Estimation Data Release[END_REF]. Finally, the strain data for O3a used for the analyses in this paper are also available [START_REF]The o3a data release[END_REF].

The LIGO Scientific, Virgo and KAGRA Collaboration (LVK) have already announced the first observations from NSBHs [START_REF] Abbott | Observation of Gravitational Waves from Two Neutron Star-Black Hole Coalescences[END_REF] in the data from O3b, and the catalog that extends events up to O3b, GWTC-3 [START_REF] Abbott | GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run[END_REF], has been released. GWTC-3 adds 35 GW candidates with p astro greater than 0.5 from O3b. O3 marks the most sensitive GW data published upon so far. The LIGO, Virgo, and KAGRA [START_REF] Akutsu | KAGRA: 2.5 Generation Interferometric Gravitational Wave Detector[END_REF] detectors are currently offline and undergoing commissioning to enhance their sensitivities, and plan to all collect data simultaneously during the fourth observing run (O4) [START_REF] Abbott | Prospects for observing and localizing gravitationalwave transients with Advanced LIGO, Advanced Virgo and KAGRA[END_REF]. With further improvement in sensitivities and planning for pre-merger BNS detections [START_REF] Magee | First demonstration of early warning gravitational wave alerts[END_REF][START_REF] Nitz | Gravitational-wave Merger Forecasting: Scenarios for the Early Detection and Localization of Compactbinary Mergers with Ground-based Observatories[END_REF][START_REF] Sachdev | An Early-warning System for Electromagnetic Follow-up of Gravitationalwave Events[END_REF], O4 offers improved prospects for GW and multimessenger astronomy, and promises to build upon our current knowledge of binary populations. stages of the parameter-estimation analysis were managed with the Asimov library [298]. Plots were prepared with Matplotlib [START_REF] Hunter | Matplotlib: A 2D Graphics Environment[END_REF], seaborn [START_REF] Michael | seaborn: statistical data visualization[END_REF] and GWpy [START_REF] Macleod | [END_REF]. NumPy [START_REF] Harris | Array programming with NumPy[END_REF] and SciPy [START_REF] Virtanen | SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python[END_REF] were used in the preparation of the manuscript. In order to provide a self-consistent set of source properties, inferred using the state-of-the-art BBH waveform models described in Sec. V A, we have reanalyzed the 10 BBH events observed during O1 and O2, and reported in GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF]. We present results combining samples from analyses using both the IMRPhenomXPHM and SEOB-NRv4PHM, with the exception of GW151226 which, as mentioned earlier in Sec. V D, was analyzed using IMR-PhenomXPHM only. As the BNS models available at the time of GWTC-1 still can be considered state-of-the-art in the NS-physics they describe, we have elected to not reanalyze the BNS event GW170817 as part of this study. For the source properties of GW170817, we instead refer to GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF] and its accompanying data release [START_REF]Parameter estimation sample release for GWTC-1[END_REF].

The source properties for the 10 BBH events from the O1 and O2 are reported in Table VII, with a selection of the one-dimensional marginal posterior distributions shown in Fig. 7. The two-dimensional projections on the M -q and M-χ eff planes are shown as light-grey contours in Fig. 4 and Fig. 5 respectively. The full 15-dimensional posterior distributions are available as part of the public data release accompanying this paper [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Parameter Estimation Data Release[END_REF], as detailed further in Sec. VII.

Generally, the inferred source properties for these 10 BBHs are consistent with those presented in GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF], but there are some new features worth highlighting. Where most binaries have a nominal support for χ eff = 0, GW151226 was in GWTC-1 identified to exclude this value at > 90% probability [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF][START_REF] Abbott | GW151226: Observation of Gravitational Waves from a 22-Solar-Mass Binary Black Hole Coalescence[END_REF], a conclusion which is strengthened further as of the analysis presented here in GWTC-2.1. The other BBH in GWTC-1 with only marginal support for χ eff = 0, GW170729, is now found to include support for negative χ eff in its 90% credible interval while also simultaneously preferring BH components with more unequal masses relative to what was inferred in GWTC-1. Independent analyses of these 10 events with the IMR-PhenomXPHM model were previously presented in [START_REF] Mateu-Lucena | Adding harmonics to the interpretation of the black hole mergers of GWTC-1[END_REF], showing broad consistency with the results presented in this section.

Previously reported binaries from the first half of the third observing run

The high-significance events from O3a are reported in Table II. Out of these events, 36 were included in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF] with its accompanying data release [START_REF]GWTC-2 Data Release: Parameter Estimation Samples and Skymaps[END_REF]. Again, to ensure a self-consistent set of inferred source properties available for all CBC events observed by Advanced LIGO and Advanced Virgo, we provide a reanalysis of these 36 events using the BBH waveform models described in Sec. V A. We present results combining samples from analyses using both the IMRPhenomXPHM and SEOBNRv4PHM, with the exception of GW190413 052954, GW190413 134308, GW190421 213856, GW190521, GW190602 175927, GW190719 215514, GW190803 022701, GW190814, GW190828 063405, GW190828 065509 and GW190929 012149 which, as mentioned earlier in Sec. V D, were analysed using IMRPhenomXPHM only. As also described in Sec. V A, for the BNS event GW190425, the IMRPhenomP NRTidal waveform model [START_REF] Dietrich | Closed-form tidal approximants for binary neutron star gravitational waveforms constructed from high-resolution numerical relativity simulations[END_REF][START_REF] Dietrich | Matter imprints in waveform models for neutron star binaries: Tidal and self-spin effects[END_REF] was used. The analyses of these events also used the GW strain data described in Sec. II A, an additional improvement over the analyses presented in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. For the events listed in Table I all analyses made use of data which included glitch subtraction or a reduction in the bandwidth available for astrophysical inference.

The source properties for the 36 events from O3a are reported in Table VIII, with a selection of the onedimensional marginal posterior distributions shown in Fig. 8. The two-dimensional projections on the M -q and M-χ eff planes are shown as light-grey contours in Fig. 4 and Fig. 5 respectively. The full multi-dimensional posterior distributions are available as part of the public data release accompanying this paper [START_REF]GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run -Parameter Estimation Data Release[END_REF], as detailed further in Sec. VII.

Similar to the results presented in Sec. A 1, the vast majority of the inferred source properties for these 36 binaries are consistent with those presented in GWTC-2 [START_REF] Abbott | GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run[END_REF]. For a subset of binaries, their inferred masses have changed nominally with GW190706 222641 as of the GWTC-2.1 analysis preferring a higher total mass whereas both GW190521 and GW190929 012149 now are recovered as less massive than in GWTC-2. Additionally, GW190929 012149 as recovered in GWTC-2 had a comparatively broad and multimodal posterior distribution for its primary mass. The higher-mass mode is no longer present in the GWTC-2.1 analysis, which together with the secondary mass of GW190929 012149 remaining largely unchanged between the GWTC-2 and GWTC-2.1 analyses also leads to larger support for a more equalmass binary. GW190708 232457 on the other hand is now identified more predominantly with an unequal q distribution as compared to the broad support, with stronger preference for equal masses, reported in GWTC-2.

Independent results with the IMRPhenomXPHM model for many of these events were previously pre-

Event M (M ) M (M ) m1 (M ) m2 (M ) χ eff DL (Gpc) z M f (M ) χ f ∆Ω (deg 2 ) SNR GW150914
64.5 +3.7 -3.2 27.9 +1.7 -1.5 34.6 +4.4 -2.6 30.0 +2.9 -4.6 -0.04 +0.12 -0.14 0.47 +0.14 -0.16 0.10 +0.03 -0.03 61.5 +3.4 -2.9 0.68 Median and 90% symmetric credible intervals for the one-dimensional marginal posterior distributions on selected source parameters for the 10 BBH events observed during the O1 and O2. These binaries were reported in GWTC-1 [START_REF] Abbott | GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs[END_REF].

The columns show source total mass M , chirp mass M and component masses mi, dimensionless effective inspiral spin χ eff , luminosity distance DL, redshift z, final mass M f , final spin χ f , sky localization ∆Ω and the network matched-filter SNR.

The sky localization is the area of the 90% credible region. All quoted results are calculated from a set of posterior samples drawn with equal weight from the IMRPhenomXPHM and SEOBNRv4PHM analyses, with the exception of the SNRs that are taken from the IMRPhenomXPHM analysis alone (as RIFT, which was used for the SEOBNRv4PHM analysis, does not output that quantity). Additionally, following Sec. V D, the results presented for GW151226 are taken from an analysis using the IMRPhenomXPHM model only. A subset of the one-dimensional posterior distributions are visualized in Fig. 7. Two-dimensional projections of the 90% credible regions in the M -q and M-χ eff planes are shown in grey in Fig. 4 and Fig. 5.

sented in 3-OGC [START_REF] Nitz | 3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers[END_REF]; other groups have also presented results with either the IMRPhenomXPHM, SEOB-NRv4PHM or other precessing higher-mode models for, most prominently, the events GW190412 [START_REF] Islam | Improved analysis of GW190412 with a precessing numerical relativity surrogate waveform model[END_REF][START_REF] Colleoni | Towards the routine use of subdominant harmonics in gravitationalwave inference: Reanalysis of GW190412 with generation X waveform models[END_REF][START_REF] Michael Zevin | You Can't Always Get What You Want: The Impact of Prior Assumptions on Interpreting GW190412[END_REF][START_REF] Gamba | Effective-one-body waveforms for precessing coalescing compact binaries with post-Newtonian Twist[END_REF] and GW190521 [START_REF] Nitz | GW190521 may be an intermediate mass ratio inspiral[END_REF][START_REF] Capano | Observation of a multimode quasi-normal spectrum from a perturbed black hole[END_REF][START_REF] Estellés | A Detailed Analysis of GW190521 with Phenomenological Waveform Models[END_REF][START_REF] Olsen | Mapping the likelihood of GW190521 with diverse mass and spin priors[END_REF]. While there is general agreement for the overall inferred source properties from many of these studies, there are significant differences present between them. These differences can however, as also explicitly stated in the studies themselves, be predominantly attributed to different prior assumptions or analysis configurations across the spread of the individual studies, in addition to the variance induced by waveform differences. This further highlights the need for the clear and public dissemination of both the exact analysis configurations used and the generated datasets containing the source properties inferred in order to encourage reproducibility and further model comparisons, especially as more events are added to the population of observed CBCs. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 10 BBH events observed during O1 and O2. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in Table VII. 8. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 36 events from Table II that were not shown in Fig. 3. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in Table VIII.

FIG. 1 .

 1 FIG. 1. Comparison of the amplitude spectral density at Hanford around the 60 Hz mains line, between data with subtracted non-stationary noise and data with no subtraction. The data correspond to a typical one-hour observation-ready data stretch during O3a.

FIG. 2 .

 2 FIG.2. Cumulative sum of pBNS, pNSBH, pBBH as a function of the candidates that pass a FAR threshold of 2 per day. The events are shown in decreasing order of pastro. The sum of the source probabilities shown here represents the estimated Poisson rate of sources in each source class per O3a experiment by the different search pipelines. An estimate of the rate of sources in the subthreshold candidate list is obtained by the contribution to the sum from events with pastro less than 0.5. This estimate yields between 2.55-12.40 signals in the BBH class, 0.36-2.39 signals in the NSBH class, and 0.02-0.49 signals in the BNS class in the subthreshold candidates in O3a. The dashed vertical grey line shows where this threshold is for each pipeline. Names are marked for the candidate events with pBNS or pNSBH greater than 20%, since these are of particular interest for cross-correlation studies.

  FIG.3. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 8 events that are new to this catalog with pastro > 0.5, highlighted in bold in TableII. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in TableVI.

  FIG.5. Contours representing the 90% credible regions in the plane of chirp mass M and effective inspiral spin χ eff for all events reported in this catalog. The events that are new to this catalog with pastro > 0.5, highlighted in bold in TableII, are highlighted in this figure following the same color scheme used in Fig.3.

Appendix A: Estimation of source parameters 1 .

 1 Binary black holes from the first and second observing runs

  FIG.7. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 10 BBH events observed during O1 and O2. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in TableVII.

  FIG.8. Marginal posterior distributions on the primary mass m1, secondary mass m2, mass ratio q, effective inspiral spin χ eff and luminosity distance DL for the 36 events from Table II that were not shown in Fig.3. The vertical span for each region is constructed to be proportional to the one-dimensional marginal posterior at a given parameter value for the corresponding event. The posterior distributions are also represented numerically in terms of their one-dimensional median and 90% credible intervals in TableVIII.

TABLE I

 I

	Name	Mitigation
	GW190413 134308	L1 glitch subtraction, glitch-only
		model
	GW190425	L1 glitch subtraction, glitch-only
		model
	GW190503 185404	L1 glitch subtraction, glitch-only
		model
	GW190513 205428	L1 glitch subtraction, glitch-only
		model
	GW190514 065416	L1 glitch subtraction, glitch-only
		model
	GW190701 203306	L1 glitch subtraction, glitch+signal
		model
	GW190727 060333	L1 fmin: 50 Hz
	GW190814	L1 fmin: 30 Hz; H1 non-observing
		data used
	GW190924 021846	L1 glitch subtraction, glitch-only
		model

. List of candidate-specific data usage and mitigation methods for parameter estimates. Only candidate events for which mitigation of instrumental artifacts was performed are listed. The glitch subtraction methods used for these candidate events are detailed in Sec. II B. The minimum frequency is the lower limit of data used in analyses of GW source properties for the listed interferometer.

  ) SNR pastro FAR (yr -1 ) SNR pastro FAR (yr -1 ) SNR pastro FAR (yr -1 ) SNR pastro × 10 -5 14.4 1.00 < 1.0 × 10 -5 14.7 1.00 2.5 × 10 -4 13.1 ‡ 1.00 < 1.2 × 10 -4 13.7 ‡ 1.00 GW190412 HLV < 1.0 × 10 -5 18.2 1.00 < 1.0 × 10 -5 19.0 1.00 < 1.1 × 10 -4 17.4 ‡ 1.00 < 1.2 × 10 -4 17.9 ‡ 1.× 10 -5 13.7 1.00 < 1.0 × 10 -5 12.4 1.00 < 1.0 × 10 -4 13.2 ‡ 1.00 < 1.1 × 10 -4 13.2 ‡ 1.× 10 -5 13.0 1.00 6.8 × 10 -4 13.0 ‡ 1.00 < 7.0 × 10 -5 13.1 ‡ 1.00

	Name	Inst.	MBTA		GstLAL		PyCBC		PyCBC-BBH
	FAR (yr -1 GW190403 051519 HLV -	-	-	-	-	-	-	-	-	7.7	8.0 0.61
	GW190408 181802	HLV 8.7 00
	GW190413 052954	HLV	-	-	-	-	-	-	170	8.5 0.13	0.82	8.5 0.93
	GW190413 134308	HLV	0.34	10.3 0.99	39	10.1 0.04	21	9.3 ‡ 0.48	0.18	8.9 ‡ 0.99
	GW190421 213856	HL	1.2	9.7 0.99	0.0028	10.5 1.00	5.9	10.1 0.75	0.014	10.1 1.00
	GW190425	LV	-	-	-	0.034 †	12.9 0.78	-	-	-	-	-	-
	GW190426 190642 HLV	-	-	-	-	-	-	-	-	-	4.1	9.6 0.75
	GW190503 185404 GW190512 180714 GW190513 205428 GW190514 065416	HLV HLV HLV HL	0.013 0.038 0.11 -	0.038 11.7 0.99 < 1.0 × 10 -5 12.2 1.00 1.1 × 10 -4 12.4 ‡ 1.00 < 1.1 × 10 -4 12.4 ‡ 1.00 12.2 ‡ 1.00 0.0026 12.2 ‡ 1.00 12.8 1.00 < 1.0 × 10 -5 12.0 1.00 19 11.6 ‡ 0.49 0.044 11.8 ‡ 1.00 13.0 0.99 1.3 × 10 -5 12.3 1.00 --450 8.3 0.00 ---2.8 8.4 0.76
	GW190517 055101 GW190519 153544	HLV HLV 7.0 00 0.11 11.3 1.00 0.0045 10.8 1.00 0.0095 10.4 ‡ 1.00 3.5 × 10 -4 10.3 ‡ 1.00
	GW190521	HLV	0.042	13.0 0.96	0.20	13.3 0.79	0.44	13.7 ‡ 0.96	0.0013	13.6 ‡ 1.00
	GW190521 074359												0 1.00
	GW190527 092055	HL	-	-	-	0.23	8.7 0.85	-	-	-	19	8.4 0.33
	GW190602 175927 GW190620 030421	HLV 3.0 × 10 -4 12.6 1.00 < 1.0 × 10 -5 12.3 1.00 LV ---0.011 † 10.9 0.99	0.29 -	11.9 ‡ 0.98 --	0.013 -	11.9 ‡ 1.00 --
	GW190630 185205 GW190701 203306	LV HLV	-35	-11.3 0.87 -< 1.0 × 10 -5 15.2 1.00 0.0057 11.7 0.99	-0.064	-11.9 0.99 -	0.24 0.56	15.1 1.00 11.7 1.00
	GW190706 222641 GW190707 093326	HLV HL	0.0015 0.032	0.34 12.00 12.6 ‡ 1.00 11.9 1.00 5.0 × 10 -5 12.5 1.00 3.7 × 10 -4 11.7 ‡ 1.00
	GW190708 232457 GW190719 215514	LV HL	--	--	-3.1 × 10 -4 † 13.1 1.00 ----	--	--	--	-0.63	-8.0 0.92 -
	GW190720 000836	HLV	0.094	11.6 1.4 1.00
	GW190725 174728* HLV	3.1	9.8 0.59	-	-	-	0.46	9.1 ‡ 0.96	2.9	8.8 ‡ 0.82
	GW190727 060333	HLV	0.023	12.0 1.00 < 1.0 × 10 -5 12.1 1.00	0.0056	11.4 00
	GW190731 140936	HL	6.1	9.1 0.80	0.33	8.5 0.78	-	-	-	1.9	7.8 0.83
	GW190803 022701	HLV	77	9.0 0.96	0.073	9.1 0.94	81	8.7 ‡ 0.17	0.39	8.7 ‡ 0.97
	GW190805 211137 HLV	-	-	-	-	-	-	-	-	-	0.63	8.3 0.95
	GW190814 GW190828 063405	LV < 2.0 × 10 -4 20.4 1.00 < 1.0 × 10 -5 22.2 1.00	0.17	19.5 1.00	-	-	-00
	GW190828 065509 GW190910 112807	HLV LV	0.16 -	10.8 0.96 3.5 × 10 00 --0.0029 † 13.4 1.00 ------
	GW190915 235702 12.7 1.00 < 1.0 GW190916 200658* HLV 6.9 × 10 3 8.2 0.66 HLV 0.0055 12 GW190917 114630 HLV ---0.66	8.2 0.09 9.5 0.77	--	--	--	4.7 -	7.9 ‡ 0.64 --
	GW190924 021846 GW190925 232845* HV HLV	0.0049 100	11.9 0.99 < 1.0 × 10 -5 13.0 1.00 < 8.2 × 10 -5 12.4 ‡ 1.00 8.3 × 10 -5 12.5 ‡ 1.00 9.4 0.35 ---73 9.0 0.02 0.0072 9.9 0.99
	GW190926 050336* HLV	-	-	-	1.1	9.0 0.54	-	-	-	87	7.8 ‡ 0.09
	GW190929 012149	HLV	2.9	10.3 0.64	0.16	10.1 0.87	120	9.4 ‡ 0.14	14	8.5 ‡ 0.41
	GW190930 133541	HL	0.34	10.0 0.87	0.43	10.1 0.76	0.018	9.8 1.00	0.012	10.0 1.00
	TABLE II.
													, while
							4 candidates (GW190725 174728, GW190916 200658,
							GW190925 232845, and GW190926 050336) were also

HL < 1.0 × 10 -5 22.2 1.00 < 1.0 × 10 -5 24.4 1.00 < 1.8 × 10 -5 24.0 1.00 < 2.3 × 10 -5 24.6 1.00 < 1.0 × 10 -5 13.2 1.00 < 1.0 × 10 -5 13.0 1.00 < 1.9 × 10 -5 13.0 1.00 < 1.0 × 10 -5 11.5 1.00 1.4 × 10 -4 10.6 ‡ 1.00 < 7.8 × 10 -5 11.‡ 1.00 2.0 × 10 -4 11.1 ‡ 1.00 GW190728 064510 HLV 7.5 × 10 -4 13.1 1.00 < 1.0 × 10 -5 13.4 1.00 < 8.2 × 10 -5 13.0 ‡ 1.00 < 7.8 × 10 -5 13.0 ‡ 1.HLV < 1.0 × 10 -5 15.2 1.00 < 1.0 × 10 -5 16.3 1.00 < 8.5 × 10 -5 13.9 ‡ 1.00 < 7.0 × 10 -5 15.9 ‡ 1.-5 11.1 1.00 2.8 × 10 -4 10.5 ‡ 1.00 1.1 × 10 -4 10.5 ‡ 1.

TABLE III .

 III Source probabilities (pBBH, pBNS, pNSBH) for the high significance GW candidates listed in TableIIfor which pBNS or pNSBH is greater than 1%. For other events in TableII, pastro ≈ pBBH, and therefore we do not list them here. Results are provided from all three matched-filter pipelines. Dashes indicate that a pipeline did not find the event with a FAR smaller than the subthreshold FAR threshold of 2 per day. The classification provided here assumes a boundary of 3 M between NSs and BHs in the case of GstLAL and PyCBC, and 2.5 M in the case of MBTA.

TABLE IV .

 IV Marginal-significance GW event candidate list. There are 2 candidates that are found in at least one of the searches with a FAR less than 2 per year, but with a pastro smaller than 0.5 in all searches. The candidate in bold, GW190531 023648, is a new candidate identified in GWTC-2.1, not included in GWTC-2. The column max pastro shows the astrophysical class assigned with highest probability. Both candidates are detected by GstLAL with a small FAR, and are assigned to the NSBH class with pastro and pNSBH smaller than 0.5.

								-1 ) SNR max pastro
	GW190426 152155	HLV	32	9.8 pNSBH = 0.01	0.91	10.1 pNSBH = 0.14	43	8.8 pNSBH = 0.01
	GW190531 023648 HLV	8.1	9.8 pBNS = 0.05	0.41	10.0 pNSBH = 0.28	29	9.2 pNSBH = 0.01

TABLE V .

 V Measures of sensitivity for the search pipelines. We state the sensitive hypervolume V for each of four assumed signal populations: a BBH population following the injected distribution, a BBH population given by the Power Law + Peak model of

		mass distribution	Injection populations mass range spin (M ) range	Sensitive hypervolume V (Gpc 3 yr) max. GstLAL MBTA PyCBC PyCBC All evolution redshift redshift BBH
	BBH (INJ)	p(m1) ∝ m1 -2.35 p(m2|m1) ∝ m2	2 < m1 < 100 2 < m2 < 100	|χ1,2| < 0.998 κ = 1	1.9	0.258	0.196	0.194	0.234	0.308
	BBH (POP)	Power Law + Peak	(see text)	|χ1,2| < 0.998 κ = 0	1.9	1.22	0.885	0.914	1.20	1.44
	BNS	uniform	1 < m1 < 2.5 1 < m2 < 2.5	|χ1,2| < 0.4	κ = 0	0.15	0.00594 0.00631 0.00657	-	0.00781
	NSBH	p(m1) ∝ m1 -2.35 uniform	2.5 < m1 < 60 1 < m2 < 2.5	|χ1| < 0.998 |χ2| < 0.4	κ = 0	0.25	0.0174 0.0165 0.0181	-	0.0221

TABLE VI .

 VI

  +0.28 -0.21 1.00 +0.64 -0.49 0.20 +0.11 -0.09 37.1 +10.6 -4.6 0.69 +0.13 -0.13 1700 9.3 +0.3 +4.7 -3.6 21.1 +2.0 -1.5 28.7 +6.6 -4.2 20.8 +4.1 -4.7 -0.04 +0.15 -0.19 1.11 +0.39 -0.48 0.22 +0.07 -0.09 47.5 +4.5 -3.4 0.67 +0.06 -0.08 1000 13.8 +0.2

						+0.05 -0.05	250 26.0 +0.1 -0.2
	GW151012	38.8 +10.3 -4.7	15.6 +2.3 -1.5 24.8 +14.5 -6.3	13.6 +4.5 -4.9	0.12 -0.5
	GW151226	21.7 +8.3 -1.6	8.9 +0.3 -0.3 14.2 +11.1 -3.6	7.5 +2.4 -2.8	0.20 +0.23 -0.08 0.46 +0.16 -0.20 0.10 +0.03 -0.04 20.7 +8.6 -1.6 0.75 +0.12 -0.05	950 12.7 +0.3 -0.4
	GW170104	49.6 -0.3
	GW170608	18.5 +2.0 -0.6	7.9 +0.2 -0.2	10.6 +4.0 -1.4	7.8 +1.2 -1.9	0.05 +0.13 -0.05 0.34 +0.12 -0.13 0.07 +0.03 -0.03 17.7 +2.1 -0.6 0.69 +0.03 -0.03	380 15.3 +0.2 -0.3
	GW170729	84.4 +15.0 -10.9 34.6 +7.0 -5.7 54.7 +12.7 -12.8 30.2 +11.9 -10.2 0.29 +0.25 -0.33 2.49 +1.69 -1.23 0.44 +0.24 -0.19 80.3 +13.5 -10.2 0.78 +0.09 -0.22	830 10.7 +0.4 -0.5
	GW170809	58.5 +5.3 -3.9 24.8 +2.2 -1.6 34.1 +8.0 -5.3 24.2 +4.8 -5.3	0.07 +0.17 -0.17 1.07 +0.31 -0.38 0.21 +0.05 -0.07 55.7 +5.0 -3.6 0.71 +0.08 -0.08	260 12.8 +0.2 -0.3
	GW170814	56.0 +3.5 -3.0 24.1 +1.4 -1.2 30.9 +5.4 -3.3 24.9 +3.0 -4.0	0.08 +0.13 -0.12 0.61 +0.16 -0.23 0.13 +0.03 -0.05 53.2 +3.2 -2.7 0.72 +0.07 -0.06	92 17.7 +0.2 -0.3
	GW170818 GW170823	62.5 +5.3 -4.6 26.8 +2.3 -2.0 34.8 +6.5 -4.2 27.6 +4.1 -5.1 -0.06 +0.19 -0.22 1.08 +0.43 -0.41 0.21 +0.07 -0.07 59.7 +4.9 -4.2 0.68 +0.08 -0.08 67.0 +10.3 -7.2 28.6 +4.5 -3.3 38.3 +9.5 -6.2 29.0 +6.5 -7.8 0.05 +0.21 -0.22 1.97 +0.84 -0.93 0.36 +0.13 -0.15 63.9 +9.6 -6.8 0.71 +0.08 -0.10 1800 12.2 +0.2 35 12.0 +0.3 -0.4 -0.3

TABLE VII .

 VII

See TableE1in[START_REF] Romero-Shaw | Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue[END_REF] for precise definitions of all parameters used.

In GWTC-2, GW190521 was inferred to have a total mass of 163.9 +39.2 -23.5 M and remnant mass of 156.3 +36.8 -22.4 M [8]

ACKNOWLEDGMENTS

This material is based upon work supported by NSF's LIGO Laboratory which is a major facility fully funded by the National Science Foundation. The authors also gratefully acknowledge the support of the Science and Technology Facilities Council (STFC) of the United Kingdom, the Max-Planck-Society (MPS), and the State of Niedersachsen/Germany for support of the construction of Advanced LIGO and construction and operation of the GEO600 detector. Additional support for Advanced LIGO was provided by the Australian Research Council. The authors gratefully acknowledge the Italian Istituto Nazionale di Fisica Nucleare (INFN), the French Centre National de la Recherche Scientifique (CNRS) and the Netherlands Organization for Scientific Research, for the construction and operation of the Virgo detec-tor and the creation and support of the EGO consortium. The authors also gratefully acknowledge research support from these agencies as well as by the Council of Scientific and Industrial Research of India, the Department of Science and Technology, India, the Science & Engineering Research Board (SERB), India, the Ministry of Human Resource Development, India, the Spanish Agencia Estatal de Investigación, the Vicepresidència i Conselleria d'Innovació, Recerca i Turisme and the Conselleria d'Educació i Universitat del Govern de les Illes Balears, the Conselleria d'Innovació, Universitats, Ciència i Societat Digital de la Generalitat Valenciana and the CERCA Programme Generalitat de Catalunya, Spain, the National Science Centre of Poland and the Foundation for Polish Science (FNP), the Swiss National Science Foundation (SNSF), the Russian Foundation for Basic Research, the Russian Science Foundation, the European Commission, the European Regional Development Funds (ERDF), the Royal Society, the Scottish Funding Council, the Scottish Universities Physics Alliance, the Hungarian Scientific Research Fund (OTKA), the French Lyon Institute of Origins (LIO), the Belgian Fonds de la Recherche Scientifique (FRS-FNRS), Actions de Recherche Concertées (ARC) and Fonds Wetenschappelijk Onderzoek -Vlaanderen (FWO), Belgium, the Paris Île-de-France Region, the National Research, Development and Innovation Office Hungary (NKFIH), the National Research Foundation of Korea, the Natural Science and Engineering Research Council Canada, Canadian Foundation for Innovation (CFI), the Brazilian Ministry of Science, Technology, and Innovations, the International Center for Theoretical Physics South American Institute for Fundamental Research (ICTP-SAIFR), the Research Grants Council of Hong Kong, the National Natural Science Foundation of China (NSFC), the Leverhulme Trust, the Research Corporation, the Ministry of Science and Technology (MOST), Taiwan, the United States Department of Energy, and the Kavli Foundation. The authors gratefully acknowledge the support of the NSF, STFC, INFN and CNRS for provision of computational resources.

We would like to thank all of the essential workers who put their health at risk during the COVID-19 pandemic, without whom we would not have been able to complete this work.

Analyses in this catalog relied upon the LALSuite software library [170]. The detection of the signals and subsequent significance evaluations were performed with the GstLAL-based inspiral software pipeline [47][48][49]294], with the MBTA pipeline [55,295], and with the PyCBC [53,54,101,123] package. Estimates of the noise spectra and glitch models were obtained using BayesWave [92,95,296]. Source parameter estimation was performed with the Bilby library [140,165] using the Dynesty nested sampling package [297], the RIFT library [171][172][173] and the LALInference library [137]. PESummary was used to post-process and collate parameter-estimation results [174]. The various

-3.0 18.5 +1.9 -1.2 24.8 +5.4 -3.5 18.5 +3.3 -4.0 -0.03 +0.13 -0.17 1.54 +0.44 -0.62 0.29 +0.07 -0.11 41.4 +3.9 -2.9 0.67 The results for the BBHs are calculated from a set of posterior samples drawn with equal weight from the IMRPhenomXPHM and SEOBNRv4PHM analyses, with the exception of the SNRs that are taken from the IMRPhenomXPHM analysis alone (as RIFT, which was used for the SEOBNRv4PHM analysis, does not output that quantity). Additionally, following Sec. V D, the results for GW190413 052954, GW190413 134308, GW190421 213856, GW190521, GW190602 175927, GW190719 215514, GW190803 022701, GW190814, GW190828 063405, GW190828 065509 and GW190929 012149 are from analyses using the IMRPhenomXPHM model only. For GW190425, we report results from the high-spin (| χ1| < 0.89) analysis, and since the calculation of the BH remnant properties is only valid for BBH model input those properties are excluded for this BNS signal. A subset of the one-dimensional posterior distributions are visualized in Fig. 8. Two-dimensional projections of the 90% credible regions in the M -q and M-χ eff planes are shown in grey in Fig. 4 and Fig. 5.