Yuri Bedjanian
email: yuri.bedjanian@cnrs-orleans.fr

Rate Constant of the BrO + BrO Reaction over the Temperature Range 220 -950 K

Keywords: BrO, self-reaction, rate coefficient, temperature dependence

Rate constant of the BrO + BrO reaction over the temperature range 220-950 K

Yuri Bedjanian

INTRODUCTION

The BrO radical is the major form of active bromine-containing species in the atmosphere and is involved in several catalytic cycles of ozone destruction. [START_REF] Bedjanian | Kinetics of halogen oxide radicals in the stratosphere[END_REF] The BrO + BrO reaction is slow compared to the reactions of these radicals with other atmospheric species (e.g. ClO, HO 2 , NO) due to relatively low concentrations of BrO in the atmosphere, and, as a result, is of limited importance in the atmospheric chemistry. Although this reaction is not of direct atmospheric significance, the information on its kinetics and products is important in laboratory studies of BrO chemistry and, for example, in studies of the reactions of oxygen atoms, which may employ detection of small concentrations of O-atoms via their conversion to BrO in reaction with Br 2 . [START_REF] Morin | Reaction of O( 3 P) with C 2 H 4 : yield of the reaction products as a function of temperature[END_REF][START_REF] Bedjanian | Reaction of O( 3 P) with C 3 H 6 : yield of the reaction products as a function of temperature[END_REF][START_REF] Morin | Rate Constants of the reactions of O( 3 P) atoms with ethene and propene over the temperature range 230-900 K[END_REF] The kinetics of the self-reaction of BrO BrO + BrO  Br + Br + O 2 (1a)

BrO + BrO  Br 2 + O 2 (1b) BrO + BrO (+M)  Br 2 O 2 (+M) (1c)
has been studied very extensively in the past. [START_REF] Clyne | Kinetic studies for diatomic free radicals using mass spectrometry. Part 3.-Elementary reactions involving BrO X2Π radicals[END_REF][START_REF] Jaffe | Bromine photosensitized decomposition of ozone[END_REF][START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF][START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF][START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF][START_REF] Barnes | Kinetic studies of the reactions of IO, BrO, and ClO with dimethylsulfide[END_REF][START_REF] Lançar | Rate constant and products of the BrO + BrO reaction at 298 K[END_REF][START_REF] Bridier | Flash photolysis kinetic study of reactions of the BrO radical with BrO and HO 2[END_REF][START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Rowley | A novel flash photolysis/UV absorption system employing charge-coupled device (CCD) detection: A study of the BrO + BrO reaction at 298 K[END_REF][START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF][START_REF] Laszlo | Kinetic studies of the reactions of BrO and IO radicals[END_REF][START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] All the available temperature dependent measurements indicate a negative temperature dependence of the total rate constant (k 1 = k 1a + k 1b + k 1c ); however, the absolute values of k 1 differ by a factor of 1.6. [START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF][START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF][START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] Current evaluations of the kinetics [START_REF] Burkholder | Chemical kinetics and photochemical data for use in atmospheric studies[END_REF][START_REF] Atkinson | Evaluated kinetic and photochemical data for atmospheric chemistry: Volume III -gas phase reactions of inorganic halogens[END_REF] recommend rate constants based on the largest of the measured values of k 1 . [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] The temperature dependence of the reaction pathway (1b) is even more uncertain. The existing temperature-dependent kinetic data [START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF][START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] are sparse and scattered and are further complicated by an apparent pressure dependence of the rate constant observed at low temperatures and high pressures. [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] As a result, it is not currently possible to make a reliable recommendation of the rate constant k 1b and, in general, for the partitioning of the products of the BrO + BrO reaction as a function of temperature.

The objective of the present work was to determine the total rate constant of the BrO + BrO reaction, k 1 , and the partial rate constant of the channel (1b), k 1b , over an extended temperature range (220 -950 K for the total rate constant) in order to better specify these quantities in comparison with previous experimental data.

EXPERIMENTAL

The rate constants of the title reaction were measured at a total pressure of nearly 2 Torr of He in a discharge flow reactor combined with a modulated molecular beam mass spectrometer. [START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF][START_REF] Bedjanian | Kinetic study of the reactions of BrO radicals with HO 2 and DO 2[END_REF] Two flow reactors were used. The first one (Figure S1, Supporting Information), used at low temperatures (220 -318 K), consisted of a Pyrex tube (45 cm length and 2.4 cm i.d.) with a jacket for the thermostated liquid circulation (ethanol). The inner surface of the reactor as well as of the movable injector of O and Br atoms was coated with halocarbon wax (HW) in order to minimize their heterogeneous loss. The second flow reactor, operating at high temperatures (T = 296 -950 K), consisted of an electrically heated Quartz tube (45 cm length and 2.5 cm i.d.) with water-cooled attachments (Figure S2, Supporting Information). [START_REF] Morin | Experimental study of the reactions of OH radicals with propane, n-pentane, and n-heptane over a wide temperature range[END_REF] Two methods were used to produce BrO radicals. In the first one, BrO was formed in reaction of oxygen atoms with excess Br 2 :

O + Br 2  BrO + Br (2)
k 2 = 9.8510 -16 T 1.41 exp(543/T) cm 3 molecule -1 s -1 over T = 220-950 K. [START_REF] Bedjanian | Rate constants of the reactions of O( 3 P) atoms with Br 2 and NO 2 over the temperature range 220-950 K[END_REF] Second method employed reaction of Br atoms with ozone,

Br + O 3  BrO + O 2 (3)
k 3 = 1.610 -11 exp(-780/T) cm 3 molecule -1 s -1 over T = 195-422 K. [START_REF] Burkholder | Chemical kinetics and photochemical data for use in atmospheric studies[END_REF] Oxygen and bromine atoms were generated from the microwave discharge in O 2 /He (Figure S1) and Br 2 /He mixtures (Figure S2), respectively. Absolute concentrations of BrO radicals were determined using their chemical conversion to NO 2 through reaction (4) in an excess of NO with subsequent detection of the NO 2 formed ([BrO] 0 = [NO 2 ] formed ): [START_REF] Burkholder | Chemical kinetics and photochemical data for use in atmospheric studies[END_REF] Another method of the absolute calibration of BrO signals used reaction (3) in an excess of ozone. In this case, the concentration of BrO was related to the fraction of Br ), 95/97 (BrO + ).

BrO + NO  Br + NO 2 (4) k 4 = 8.810 -12 exp(260/T) cm 3 molecule -1 s -1 (T = 224-425K)

RESULTS AND DISCUSSION

Measurements of k 1

The total rate constant of the title reaction was determined from the kinetics of BrO consumption in the temperature range 220-950 K and 2.0-2.2 Torr total pressure of He. S3 (Supporting Information). The BrO decays were processed using a simple kinetic mechanism:

BrO + BrO  products (1)
BrO + wall  loss (5)

Reaction 5 corresponds to the heterogeneous loss of BrO radicals on the wall of the flow reactor (k w ). In the frame of the two step mechanism (reactions 1 and 5), the rate of BrO consumption is:

d[BrO]/dt = -2k 1 [BrO] 2 -k w [BrO]
An analytical solution of this differential equation leads to the following expression for the temporal profiles of BrO radicals:

BrO BrO 0 BrO 0 BrO 0 (I)
At each temperature, the rate constant of reaction (1)

Measurements of k 1b

A similar approach was employed for the measurements of the rate constant k 1b of the Br 2 +O 2 forming pathway of the BrO self-reaction:

BrO + BrO  Br + Br + O 2 (1a) BrO + BrO  Br 2 + O 2 (1b)
In this case, BrO radicals were generated through reaction of Br atoms with ozone,

Br + O 3  BrO + O 2 (3)

Comparison with previous measurements

Reaction (1) was quite intensively studied in the past. All previous work can be divided into three categories: measurements of the overall rate constant (k 1 ), measurements of the channel-specific rate constant, k 1b , and measurements of k 1a /k 1 , the branching to the main (1a) channel.

Total rate constant k 1

Results of previous direct room-temperature measurements of k 1 are summarized in Table 3. potentially be somewhat overestimated. The results of the UV absorption studies depend directly on the values of the absorption cross section of BrO ( BrO ) at the monitoring wavelength, generally 338.5 nm. In this context, it should be noted that fairly close values of  BrO were used in the measurements of k 1 shown in Table 3: 1.48, [START_REF] Rowley | A novel flash photolysis/UV absorption system employing charge-coupled device (CCD) detection: A study of the BrO + BrO reaction at 298 K[END_REF] 1.55, [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] 1.41 [START_REF] Laszlo | Kinetic studies of the reactions of BrO and IO radicals[END_REF] and 1.63×10 -17 cm 2 molecule -1 . [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] Sander and Watson 7 have measured and used  BrO (339nm) = 1.14×10 -17 cm 2 molecule -1 . Current evaluations of kinetic data tend to scale k 1 data (10% increase) from earlier FP/UV studies to the highest UV absorption cross section reported by Gilles et al., [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] although Gilles et al. [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] estimated 10% uncertainty on the absorption cross section measured in their study. In addition, this scaling is not always justified considering that the cross section depends on spectral transition and instrumental resolution.

Not included in

Consequently, the use of  BrO determined with apparatus employed in the measurements of k 1 [START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF][START_REF] Laszlo | Kinetic studies of the reactions of BrO and IO radicals[END_REF] seems to be preferable. Finally, considering the present results and the above analysis of the previous data, we would recommend k 1 = (2.7±0.6)×10 -12 cm 3 molecule -1 s -1 at T = 298K

from the present study.

The results of direct measurements of the temperature dependence of the overall rate constant of reaction (1) are shown in Figure 4. One data point of Turnipseed et al. [START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF] (k 1 = (4.57±1.7)×10 -12 cm 3 molecule -1 s -1 at T = 253K) was excluded. Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] observed pressure dependence of k 1 at T ≤ 250 K (increase with increasing pressure) which was attributed to the formation of a stabilized BrOOBr dimer in the termolecular channel 1c,

BrO + BrO (+M)  Br 2 O 2 (+M) (1c)
competing with the bimolecular channels of reaction (1). The values of k 1 obtained at lowest Looking at Figure 4, one can note that all the available temperature dependent k 1 data exhibit a small negative temperature dependence and the absolute values of k 1 from different studies (except those of Gilles et al. [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] and of Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] at T < 250K) are in excellent agreement. In the most extended temperature dependent study of Gilles et al. [START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] the following Arrhenius expression was reported: k 1 = (1.70±0.45)10 -12 exp(215±50/T) cm 3 molecule -1 s -1 (T = 204-388K). Current recommendations of k 1 for use in atmospheric modelling are based primarily on this expression. [START_REF] Burkholder | Chemical kinetics and photochemical data for use in atmospheric studies[END_REF][START_REF] Atkinson | Evaluated kinetic and photochemical data for atmospheric chemistry: Volume III -gas phase reactions of inorganic halogens[END_REF] The k 1 data from the present work can be represented as k 1 = (1.32±0.09)10 -12 exp(182±22/T) cm 3 molecule -1 s -1 (T = 220-950K, with quoted 2 uncertainties). Taking the average activation energy factor from two studies, E/R = -200 K, in combination with k 1 = (2.7±0.6)×10 -12 cm 3 molecule -1 s -1 at T = 298K (as discussed above), we would recommend the following Arrhenius expression,

k 1 = 1.410 -12 exp(200/T) cm 3 molecule -1 s -1
(solid blue line in Fig. 4) in the temperature range (200 -950) K and with conservative uncertainty of 25% at all temperatures (dashed blue lines in Figure 4).

Rate constant k 1b

Previous direct near room-temperature measurements of k 1b are summarized in Table 4. The value of k 1b from the present study is in good agreement (within 10%) with those reported by Sander and Watson, [START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF] Turnipseed et al. [START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF] and Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] The value obtained by Cox et al. [START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF] using a molecular modulation technique, k 1b = (6.6 ± 2.0) × 10 -13 cm 3 molecule -1 s -1 , is much greater compared with all other measurements, which all lie within a factor of 1.6 and overlap within reported experimental uncertainties. The average of the studies listed in cm 3 molecule -1 s -1 , seems to be an appropriate value to recommend based on currently available data.

All data from direct temperature dependent measurements of k 1b are shown in Figure 5.

A virtually temperature independent value of k 1b = (2.83±0.35)10 -13 exp(34±36/T) cm 3 molecule -1 s -1 (T = 220-450K, with 2 uncertainties) was measured in the present study. A similar very small temperature dependence of k 1b was observed by Cox et al., [START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF] although the absolute values of the rate constant are a factor of 2 higher than in the present work.

Mauldin et al. [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] and Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] observed a pressure dependence of k 1b (an increase with increasing pressure) at T = 220K and T = 238, 220K, respectively. The data of Mauldin et al. [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] and Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] connected by vertical lines. In our opinion, the existing data on the impact of pressure on kinetics of reaction (1) at low temperatures should be viewed with some caution. Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] attributed the observed pressure dependence of the BrO+BrO reaction to the formation of a stabilized BrOOBr dimer in the termolecular channel (1c), while in the study of Mauldin et al. [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] it was attributed to the Br 2 +O 2 forming channel (1b). Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] noted that an excessively large negative temperature coefficient for the recombination reaction (1c), estimated in their study at low temperatures, indicates a problem with either the data or its analysis. Another point is that the results from two pressure dependence studies differ significantly (see Figure 5). Clearly, additional kinetic and direct product studies (solid blue line in Figure 5), can be recommended (at least, at low pressures) from the present study in the temperature range (220 -450) K and with conservative uncertainty of 25% (dashed blue lines in Figure 5). One can note that this expression differs significantly from current recommendations: k 1b = 0.2810 -13 exp(860/T) [START_REF] Burkholder | Chemical kinetics and photochemical data for use in atmospheric studies[END_REF] and k 1b = 0.2910 -13 exp(840/T) cm 3 molecule -1 s -1 (dotted line in Figure 5). 20

Branching ratio k 1a /k 1

The branching ratio between the two bimolecular channels of reaction (1) at room temperature has been determined in multiple studies through the measurements of quantum yields for Br 2 -photosensitized decomposition of ozone [START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF][START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Rowley | A novel flash photolysis/UV absorption system employing charge-coupled device (CCD) detection: A study of the BrO + BrO reaction at 298 K[END_REF] or direct measurements, generally, of k 1b and k 1 . [START_REF] Sander | Kinetics and mechanism of the disproportionation of bromine oxide (BrO) radicals[END_REF][START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF][START_REF] Lançar | Rate constant and products of the BrO + BrO reaction at 298 K[END_REF][START_REF] Rowley | A novel flash photolysis/UV absorption system employing charge-coupled device (CCD) detection: A study of the BrO + BrO reaction at 298 K[END_REF][START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF] In a previous study from this group, [START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF] the production of Br atoms in reaction channel (1a) was observed and quantified. The concentration of Br atoms was monitored as a function of the consumed concentration of BrO, which allowed the determination of the branching ratio for the Br atom forming channel (1a): [START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF] All previous measurements (reporting photosensitized decomposition of ozone [START_REF] Jaffe | Bromine photosensitized decomposition of ozone[END_REF][START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF][START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] and calculated using reported values of k 1a and k 1 [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] or k 1b and k 1 (this work). One can note very good agreement between the results from different studies around room temperature. The branching ratio data from the present low pressure study (between 0.89 and 0.85 in the temperature range 220-450K) exhibit a very small negative temperature dependence, k 1a /k 1 = 0.8×exp(25/T), although it could be considered as temperature independent within the experimental uncertainty. This contrasts with the results from studies at high pressures, which report a significant decrease in k 1a /k 1 at lower temperatures. Mauldin et al. [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] determined the branching ratio to be 0.84 at 298 K and 0.68 at 220 K, independent of pressure, and observed an additional absorption feature with a peak absorption at 312 nm which was tentatively attributed to Br 2 O 2 . In contrast, the values of k 1a /k 1 (calculated with the rate constant data reported for k 1a and k 1 by Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] ) display a very pronounced pressure dependence: decreasing from 0.65 to 0.47 (shown in Figure 5 for two extreme pressures connected by vertical line) and from 0.33 to 0.09 (not shown in Figure 5) upon increasing the total pressure from 105 to 778 Torr at T = 235 and 220K, respectively. It should be noted that the values of k 1a reported by Harwood et al. [START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] could be highly uncertain since k 1a , as reported in their paper, was effectively determined from the difference in the BrO decay rates in the presence and absence of ozone, and results in the presence of ozone (k 1b + k 1c [M]) were obtained in terms of a mechanism including a competition, at low temperatures, between collisional stabilization and unimolecular dissociation of an excited BrOOBr* intermediate. In any case, it is clear that both high pressure studies [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] demonstrate a decrease of k 1a /k 1 at low temperatures (pressure dependent or not), which contrasts with the present work realized at low pressure. In addition, Mauldin et al., [START_REF] Mauldin | Kinetics and mechanism of the self-reaction of the bromine oxide radical[END_REF] using the values of the branching ratio k 1a /k 1 = 0.68 and k 1b obtained at 220 K in their study, calculated k 1 increasing from (2.0 ± 0.4)×10 -12 at 100 Torr to (10) In the framework of this mechanism, the effect of pressure on the kinetics and products of reaction (1) is determined by the possible stabilization of the excited intermediate BrOOBr* in reaction (8) and the fate of the formed BrOOBr, specifically, its stability and the partitioning of the products of its decomposition in reactions (9a) and (9b), which can be different from that of BrOOBr* (reactions (7a) and (7b)). The experimental data available on reaction (1) at low temperatures, where the impact of total pressure is expected to be more pronounced, are rather limited. It is clear that further detailed experimental studies of the BrO+BrO reaction at low temperatures and as a function of pressure are required to confirm the pressure dependence of the overall kinetics and distribution of the reaction products and to better elucidate the reaction mechanism.

k 1a /k 1 = [Br]/[BrO] = 0.84 ± 0.03.
k 1a /

CONCLUSION

In this work, using a discharge-flow reactor combined with mass spectrometry, we have

TABLES LEGENDS

2 +

 2 2 dissociated in the microwave discharge: [BrO] = [Br] 0 = 2[Br 2 ]. The results of the measurements of the absolute concentrations of BrO by the two methods were consistent within 10%. Ozone was produced by an ozonizer (Trailigaz) and was collected in a liquid nitrogen trap before dilution with helium and storage at room temperature in a calibrated volume flask. The absolute concentrations of all stable species (NO 2 , Br 2 , O 3 ) in the reactor were calculated from their flow rates obtained by monitoring the pressure drop of a known volume of a manometrically prepared mixture of each substance in He. All species were detected by mass spectrometry at their parent peaks: m/z= 46 (NO

  Figure S5 (Supporting Information). A procedure similar to that used for the determination of k 1 was applied to the treatment of the observed BrO decays. At each temperature, the

(Figure 4 .

 4 Figure 4. The pressure dependence of k 1 is in contradiction, at least, with the present work and that of Sander and Watson 7 who found k 1 to be independent of pressure in the range 50-475 Torr. An excellent agreement of the present k 1 data, measured at nearly 2 Torr total pressure of He, with the work of Sander and Watson 7 seems to support the pressure independence of k 1 . In addition, the absolute value of k 1 = (1.80±0.26)×10 -12 cm 3 molecule -1 s -1 measured by Harwood et al. at T = 222K and P = 103 Torr is significantly lower than k 1 = (3.10±0.46)×10 -12 cm 3 molecule -1 s -1 measured in this work at T = 220K and a total pressure as low as 2 Torr.

  at low temperatures, k 1b + k 1c [M], are shown in Figure 5 only at the extremes of the pressure range used (74-552 Torr and 103-778 Torr, respectively),

  of the BrO+ BrO reaction at low temperatures and as a function of pressure are needed in order to better understand the reaction mechanism. Considering the temperature dependence of k 1b observed in the present work and the average value of k 1b = (3.6±0.7)×10 - 13 cm 3 molecule -1 s -1 at T = 298K, the following Arrhenius expression, k 1b = 3.210 -13 exp(34/T) cm 3 molecule -1 s -1

  k 1 in the range 0.84-0.88) are in agreement that k 1a /k 1 = 0.85 ± 0.03 at T = 298K. The corresponding value from the present work calculated as (k 1 -k 1b )/k 1 = 0.87 ± 0.04 agrees well with the previous data. All the results of temperature dependent measurements of k 1a /k 1 are shown in Fig. 6. The data shown in Figure 6 are those measured through Br 2 -

( 3 .

 3 1 ± 0.3)×10 -12 cm 3 molecule -1 s -1 at 400 Torr. The value of k 1 at 100 Torr is significantly lower than k 1 = (3.1 ± 0.5)×10 -12 cm 3 molecule -1 s -1 measured in the present work at T = 220 K and 2

  measured the rate constant of the self-reaction of the BrO radical (an important intermediate in atmospheric chemistry) as a function of temperature over an extended temperature range, 220-950 K, and total pressure of about 2 Torr. The temperature dependence of the overall rate constant of this reaction was found to be consistent with most previous measurements at T = 220-400 K and was extended to higher temperatures (T = 950 K). Direct detection of the reaction product, Br 2 , in the presence of high concentrations of ozone showed that the consumption of BrO radicals under such conditions was exclusively due to the BrO + BrO  Br 2 + O 2 reaction and the rate constant for this specific channel was determined at T = 220-450 K. Comparison of the present low pressure data with previous measurements at higher pressures reveals some disagreements at low temperatures and highlights the need for further detailed experimental studies of the reaction at low temperatures and as a function of pressure.

17

 17

a

  DF/MS: discharge flow reactor/mass spectrometry; FP/UV: flash photolysis/UV absorption; MM/UV: molecular modulation/UV absorbtion. b T = 303 K. c T = 304 K.

FIGURE 1

 1 FIGURE 1 Temporal profiles of BrO radicals observed at T = 220 (a) and 950 K (b) with different initial concentrations of the radicals. Solid lines correspond to the fit to the experimental data using Equation (I). Partially shown error bars represent maximum uncertainty of 5% on the measurements of relative concentrations of BrO.

FIGURE 2 FIGURE 3

 23 FIGURE 2 Temporal profiles of BrO radicals observed at T = 300K with different initial concentrations of the radicals and in the presence of ozone in the reactor. Solid lines correspond to the fit to the experimental data using Equation (II). Partially shown error bars represent maximum uncertainty of 5% on the measurements of relative concentrations of BrO

FIGURE 4

 4 FIGURE 4Summary of the direct temperature dependent measurements of k 1 . The error bars correspond to estimated 15% uncertainty on the measurements of k 1 in the present work; uncertainties on previous measurements are given as reported in respective studies.

FIGURE 5

 5 FIGURE5 Summary of the direct temperature dependent measurements of k 1b . The error bars correspond to estimated 15% uncertainty on the measurements of k 1b in the present work; uncertainties on previous measurements are given as reported in respective studies.

FIGURE 6

 6 FIGURE 6Summary of the temperature dependent measurements of the branching ratio k 1a /k 1 .

Table 3

 3 reported by Bridier et al.[START_REF] Bridier | Flash photolysis kinetic study of reactions of the BrO radical with BrO and HO 2[END_REF] from a FP/UV study, wherein the rate constant was extracted from the simulation of BrO profiles upon Br 2 photolysis in Br 2 /O 3 mixtures (with [Br]/[O 3 ] = 0.013-1.5) and using k 1b /k 1 = 0.16. Although the results from different studies vary by up to a factor of 1.6, they overlap within reported experimental uncertainties. It can be noted that uncertainties given for some values of k 1 in Table3refer only to the statistical precision. This is the case, for example, for the highest value of k 1 = (3.51±0.35)×10 -12 cm 3 molecule -1 s -1 , reported by Gilles et al.,[START_REF] Gilles | Kinetics of the IO Radical. 2. Reaction of IO with BrO[END_REF] for which the authors estimated an additional systematic uncertainty of 20% and an additional 10% uncertainty on absorption cross section of BrO. The value of k 1 from the present study is in better agreement with the lower of the previous values of k 1 , in the range (2.2-2.8)×10-12

is the value of k 1 = (3.1±0.4)×10 -12 cm 3 molecule -1 s -1 , which is an indirect measurement cm 3 molecule -1 s -1 . All previous work can be divided into two groups: those realized with mass spectrometric detection of BrO in discharge flow reactors and with monitoring UV absorption of BrO in flash photolysis systems. In previous DF/MS studies of Clyne and Watson 5 (k w not reported), Turnipseed et al.

[START_REF] Turnipseed | Kinetics of the BrO + BrO reaction[END_REF]

(k w not reported), Lançar et al.

[START_REF] Lançar | Rate constant and products of the BrO + BrO reaction at 298 K[END_REF]

(k w reported to be negligible) and Barnes et al.

[START_REF] Barnes | Kinetic studies of the reactions of IO, BrO, and ClO with dimethylsulfide[END_REF]

(k w = 4.8±3.8 s -1 ) the contribution of the wall loss of BrO to consumption of the radicals was not taken into account, i.e. the reported values of k 1 can

Table 4 (

 4 with the exception of k 1b data from Cox et al.[START_REF] Cox | Absorption coefficients and kinetics of the BrO radical using molecular modulation[END_REF] and also from Lançar et al.[START_REF] Lançar | Rate constant and products of the BrO + BrO reaction at 298 K[END_REF] and Rowley et al.,[START_REF] Rowley | A novel flash photolysis/UV absorption system employing charge-coupled device (CCD) detection: A study of the BrO + BrO reaction at 298 K[END_REF] re-measured in later studies by the same groups),[START_REF] Bedjanian | Kinetics and mechanism of the IO+BrO reaction[END_REF][START_REF] Harwood | Kinetics and mechanism of the BrO selfreaction: temperature-and pressure-dependent studies[END_REF] k 1b = (3.6 ± 0.7) × 10 -13

  Torr total pressure, which is in conflict with predicted positive pressure dependence of the total rate constant.

	The probable mechanism of the BrO + BrO reaction was repeatedly discussed in
	previous studies:
	BrO + BrO 	BrOOBr*	(6,-6)
	BrOOBr* 	BrOO + Br	(7a)
	BrOOBr* 	Br 2 + O 2	(7b)
	BrOOBr* + M		BrOOBr + M	(8,-8)
	BrOOBr 	BrOO + Br	(9a)
	BrOOBr 	Br 2 + O 2	(9b)
	BrOO		Br + O 2

TABLE 1

 1 Summary of the measurements of the total rate constant (k 1 ) of the reaction BrO + BrO  products

TABLE 2

 2 Summary of the measurements of the rate constant k 1b of the reaction BrO + BrO  Br 2 + O 2

TABLE 3

 3 Summary of the direct measurements of the total rate constant of the reaction BrO+BrO at T = 298.

TABLE 4

 4 Summary of the direct measurements of k 1b at T = 298 TABLES

TABLE 1

 1 Summary of the measurements of the total rate constant (k 1 ) of the reaction BrO + BrO  products

	T (K)	No./exp. a	[BrO] 0	b	k w	c	k 1	d
	220	8	1.12-11.4	8.44	3.10
	238	9	1.18-15.5	5.13	2.97
	260	10	0.98-13.7	4.78	2.62
	286	9	1.19-19.2	4.13	2.4
	296	10	1.72-16.0	5.06	2.25
	297	10	1.11-13.3	3.21	2.56
	318	11	0.81-17.1	6.13	2.38
	334	10	1.72-19.2	5.94	2.20
	385	9	1.74-14.6	7.13	2.08
	450	8	1.54-13.4	7.34	1.92
	550	9	0.81-13.3	3.13	1.87
	695	11	0.78-12.9	1.77	1.74
	950	9	0.89-13.6	0.51	1.63

a Number of kinetic runs. b Units of 10 12 molecule cm -3 . c Units of s -1 . d Units of 10 -12 cm 3 molecule -1 s -1 , estimated uncertainty on k 1 is nearly 15%.

TABLE 2

 2 Summary of the measurements of the rate constant k 1b of the reaction BrO + BrO  Br 2 + O 2

	T (K)	No./exp. a	[BrO] 0	b	k w	c	k 1b	d
	220	7	3.09-24.2	3.67	0.335
	238	8	2.68-39.6	3.51	0.31
	260	10	1.50-30.8	1.42	0.319
	286	13	1.84-30.9	0.59	0.317
	300	13	1.29-40.2	1.15	0.317
	318	12	2.07-30.2	0.0001	0.335
	335	14	0.77-36.2	1.01	0.326
	385	15	0.46-33.2	1.16	0.305
	450	14	0.48-27.8	0.22	0.292

a Number of kinetic runs. b Units of 10 12 molecule cm -3 . c Units of s -1 . d Units of 10 -12 cm 3 molecule -1 s -1 , estimated uncertainty on k 1b is nearly 15%.

TABLE 3

 3 Summary of the direct measurements of the total rate constant of the reaction BrO+BrO at T = 298.

	k 1 a (10 -12 cm 3 molecule -1 s -1 )	Method a	Reference
	2.17±0.68	FP/UV	Sander and Watson 7
	2.98±0.42	FP/UV	Rowley et al. 14
	3.51±0.35	FP/UV	Gilles et al. 15
	2.8±0.5	FP/UV	Laszlo et al. 16
	2.90±0.28	FP/UV	Harwood et al. 18
	3.20±0.65	DF/MS	Clyne and Watson 5
	2.45±0.26 b	DF/MS	Turnipseed et al. 9
	3.2±0.5	DF/MS	Lançar et al. 11
	2.7±0.5	DF/MS	Barnes et al. 10
	2.75±0.35	DF/MS	Bedjanian et al. 17
	2.43±0.36	DF/MS	This work

a DF/MS: discharge flow reactor/mass spectrometry; FP/UV: flash photolysis/UV absorption. b T = 304 K.

TABLE 4

 4 Summary of the direct measurements of k 1b at T = 298 k 1b (10 -13 cm 3 molecule -1 s -1 )

	Method a	Reference

ACKNOWLEDGMENTS

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Information section at the end of the article.


Kristin Showalter Sotzen
email: kristin.sotzen@jhuapl.edu

Kevin B Stevenson

David K Sing

Brian M Kilpatrick

Hannah R Wakeford

Joseph C Filippazzo

Nikole K Lewis

Sarah M Hörst

Mercedes López-Morales

Gregory W Henry

Lars A Buchhave

David Ehrenreich

Jonathan D Fraine

Antonio García Muñoz

Rahul Jayaraman

Panayotis Lavvas

Alain Lecavelier

Etangs

Mark S Marley

Nikolay Nikolov

Alexander D Rathcke

Jorge Sanz-Forcada

Typeset using L A T E X twocolumn style in AASTeX62 Transmission Spectroscopy of WASP-79b from 0.6 to 5.0 µm

Keywords: methods -observational, atmospheres -planets and satellies, individual -WASP-79b

, we examine HST/WFC3 (1.125 -1.650 µm), Magellan/LDSS-3C (0.6 -1 µm) data, and Spitzer data (3.6 and 4.5 µm). Using data from all three instruments, we constrain the water abundance to be -2.20 ≤ log(H 2 O) ≤ -1.55. We present these results along with the results of an atmospheric retrieval analysis, which favor inclusion of FeH and H - in the atmospheric model. We also provide an updated ephemeris based on the Smalley, HST/WFC3, LDSS-3C, Spitzer, and TESS transit times. With the detectable water feature and its occupation of the clear/cloudy transition region of the temperature/gravity phase space, WASP-79b is a target of interest for the approved JWST Director's Discretionary Early Release Science (DD ERS) program, with ERS observations planned to be the first to execute in Cycle 1. Transiting exoplanets have been approved for 78.1 hours of data collection, and with the delay in the JWST launch, WASP-79b is now a target for the Panchromatic Transmission program. This program will observe WASP-79b for 42 hours in 4 different instrument modes, providing substantially more data by which to investigate this hot Jupiter.

INTRODUCTION

Based on studies of planets and moons within the solar system and spectral analyses of exoplanets, a persistent atmosphere is generally accompanied by clouds and/or hazes. Recent studies of hot Jupiters have revealed that many of the exoplanets observed in transmission have cloudy or hazy properties, with their spectra dominated by strong optical Rayleigh and/or Mie scattering from high-altitude aerosol particles (e.g., Sing et al. (2016); Stevenson et al. (2016a); Wakeford & Sing (2016); Lavvas & Koskinen (2017)). Clouds and hazes in exoplanetary atmospheres can have a significant impact on the detectable spectra for these worlds. In the optical range, small particles produce scattering that leads to steep slopes that progressively become shallower as the particle radius increases (see e.g., Lavvas & Koskinen (2017)). This scattering effectively dampens any features from the deeper atmosphere, including pressure-broadened alkali Na and K lines, and can mute or obscure expected water absorption features in the near-infrared (see e.g., Wakeford & Sing (2016)).

The majority of current exoplanet spectra are constructed from wavelengths in the optical and nearinfrared wavelengths, revealing information on the portion of transmission spectra for aerosols where only scattering features are seen. When interpreting these observations, the slope of spectra in the optical regime is proportional to the temperature of the atmosphere and can be indicative of specific species when small grain sizes are considered (Wakeford & Sing 2016). Additionally, absorption features in the near-and mid-infrared spectra can be identified as the vibrational modes of the major bond pairs in certain potential condensates, providing composition information (Wakeford & Sing 2016).

The survey analysis performed by Sing et al. (2016) of ten hot Jupiters found that planets with predominantly clear atmospheres show prominent alkali and H 2 O absorption, with infrared radii values commensurate or higher than the optical altitudes, while heavily hazy and cloudy planets have strong optical scattering slopes, narrow alkali lines, and H 2 O absorption that is partially or completely obscured.

Like many transiting exoplanets found using groundbased surveys, WASP-79b is a hot Jupiter with an extended atmosphere. Discovered in 2012 by Smalley et al using photometry from the WASP-South and TRAP-PIST telescopes, it was found to have a planetary mass of 0.90 ± 0.08 M Jup and a large radius estimate, ranging from 1.7 ± 0.11 R Jup using a main-sequence mass-radius constraint on the Markov Chain Monte Carlo (MCMC) process, to 2.1 ± 0.14 R Jup using a non-main sequence constraint (Smalley et al. 2012). While both radius estimates were large for the available hot Jupiter data in 2012, the estimate based on the non-main sequence constraint would have made WASP-79b the largest exoplanet discovered at the time (Smalley et al. 2012). With a mass estimate of approximately one M Jup and such a large radius estimate, WASP-79b's density is comparatively low, implying that its atmosphere is extended. In addition, the host star WASP-79 is a bright, quiet F-type star with consistent stellar activity, with variation in the baseline stellar flux within 0.1% (Section 2.3.4).

WASP-79b has a T eq ∼1800 K and a log g between 2.67 and 2.85 (Smalley et al. 2012), placing this planet in a transition region of the temperature/gravity phase space. On one side of this transition region, planets have been found to have muted water features due to clouds and hazes, while on the other side, planets have been found to have strong measured water features, implying clearer atmospheres (Stevenson 2016). Being in this transition region, WASP-79b provided an opportunity to further study this relationship between temperature, gravity, and the presence of atmospheric clouds and/or hazes. These studies are important for predictions of atmospheric feature obscuration, which inform target selection and observations for telescopes like the Hubble Space Telescope (HST).

Additionally, with its broad observing windows (Bean et al. 2018), WASP-79b presented an excellent candidate for a transmission spectroscopy study as well as a potential Early Release Science (ERS) candidate for the James Webb Space Telescope (JWST). It was therefore scheduled for follow-up observations using HST, the Magellan Large Dispersion Survey Spectrograph 3 (LDSS3), and the Spitzer Space Telescope to determine its value as a candidate for JWST observation, with broad wavelength coverage to evaluate its value as an ERS candidate.

In Sections 2.1, 2.2, 2.3, and 2.4, we describe observations, analysis methods, and results from TESS, HST, LDSS3, and Spitzer respectively. In Section 3, we discuss the atmospheric retrieval analysis and expectations for JWST observations, and in Section 4, we present our conclusions.

OBSERVATIONS

TESS Data

The Transiting Exoplanet Survey Satellite (TESS) observed 12 transits of WASP-79b in January and February of 2019. TESS provides data in the 0.6 -1.0 µm band, and the TESS light curve contains data covering 12 transits in Sectors 4 and 5. We fit the TESS WASP-79b 2-minute cadence transits using the Presearch Data Conditioning (PDC) light curve, which has been corrected for effects such as non-astrophysical variability and crowding [START_REF] Jenkins | Proc. SPIE[END_REF]. From the timeseries, we removed all of the points which were flagged with anomalies. The Barycentric TESS Julian Dates (BTJD) were converted to BJD TDB by adding 2,457,000 days. For each transit in the light curve, we extracted a 0.5 day window centered around the transits and fit each transit event individually. We fit the data using the 4-parameter non-linear limb-darkened transit model of Mandel & Agol (2002) and included a linear baseline time trend. We calculated the limb-darkening coefficients as in Sing (2010) using a Kurucz stellar model finding coefficients of c 1 = 0.5012, c 2 = 0.2630, c 3 = -0.1034, and c 4 = -0.0301. For each of the 12 transits, we fit for six free parameters consisting of the central transit time, planet-to-star radius ratio, linear baseline, cosi, and a/R * . The high-quality of the TESS transit light curves places tight constraints on the system parameters, and we find a weighted-average inclination of i=85.929±0.174 degrees and a/R * =7.292±0.080. These planetary parameters were used as fixed values in the HST, LDSS3, and Spitzer analyses. Fixing the system parameters with these values for use in the transmission spectra, we find a weighted-average value of R pl (TESS)/R star = 0.10675 ± 0.00014, which is in good agreement with the HST, Spitzer, and LDSS values.

HST/WFC3 Observations and Data Analysis

Observations

We analyzed WASP-79b WFC3 data from the Panchromatic Exoplanet Treasury (PanCET) program (HST GO-14767, P.I.s Sing & López-Morales). During its primary transit in March of 2017, HST observed WASP-79b in spatial scan mode, which slews the telescope during the exposure and moves the spectrum perpendicularly to the dispersion direction on the detector (Kreidberg et al. 2014). This mode allows for longer integration times by distributing the incoming energy over multiple pixels. The Wide Field Camera 3 (WFC3) instrument utilized its G141 GRISM to acquire spectra from 1.1 to 1.7 µm over 5 HST orbits, during which we collected 65 science frames using 138-second integrations. We provide an overview of the data analysis process below, and a detailed description of the process can be found in Stevenson et al. (2014).

Reduction, Extraction, and Calibration of Spectra

The Transit Reduction, Extraction, and Calibration Software (T-RECS) pipeline produces multi-wavelength, systematics-corrected light curves from which we derive wavelength-dependent transit depths with uncertainties (Stevenson et al. 2014). The bias correction is performed using a series of bias frames stacked to form a single master bias frame that is applied uniformly to all of the science frames. We extract a pixel window centered on the spectrum that includes pixels along the spatial direction that are used in the optimal spectral extraction as well as in the background subtraction (Stevenson et al. 2014). We modeled the spectroscopic flat field using the coefficients provided in the updated flat field file sedF F cube -both.f its.

Because the background for HST is consistent over time, areas outside of the spectrum can be used to interpolate the background values for the region within the spectrum by computing the median of each column. We perform 5σ outlier detection by stacking the images in time and evaluating each pixel along the time axis for outliers. To account for imprecision in the instrument pointing during data collection, each spectrum is crosscorrelated with the first spectrum to measure and correct for the pointing drift over time (Stevenson et al. 2014).

White Light Curve Fits

The raw transit light curves for WASP-79b exhibit ramp-like systematics comparable to those seen in previous WFC3 data. Following standard procedure for HST transit light curves, we did not include data from the first orbit in our analysis (Kreidberg et al. 2014). We corrected for systematics in the remaining orbits by modeling the systematics as a function of time, which includes an exponential ramp term fitted to each orbit, a linear trend term, and a quadratic term for limb-darkening.

We modeled the band-integrated light curve in order to identify and remove systematics, most of which are wavelength-independent with WFC3, and to establish the absolute transit depth when comparing transmission spectra from different instruments using non-overlapping wavelengths (Stevenson et al. 2014). We created this "white" light curve (WLC) by summing the flux values over the entire wavelength range. We used the Bayesian Information Criterion (BIC) to select the best systemat- Figure 2. WASP-79b white and spectroscopic light curves extracted from the HST/WFC3 data using the process described in Stevenson et al. (2014). The results are binned, normalized to the system flux, and vertically shifted for ease of comparison. The error bars represent 1σ uncertainties. The black lines show the best-fit models, and the wavelength range for each of the 15 channels is specified in µm (Stevenson et al. 2014).

ics model component, and our final analytic model for the HST/WFC3 data takes the form:

F (t) = F s T (t)L(t)H(t) (1)
where F (t) is the measured flux at time t; F s is the outof-transit system flux; T (t) is the primary-transit model component with unity out-of-transit flux (Mandel & Agol 2002); L(t) = a(t -t 0 ) + 1 is the time-dependent linear model component with a fixed offset, t 0 , and free parameter, a; and H(t) = 1 -exp(-a × P + b) + c × P fits the HST "hook" using a rising exponential with free parameters a, b, where c, and P represents the number of HST orbits since the beginning of the transit. The white light curve extraction for the HST/WFC3 data resulted in a transit depth of 1.1282% ± 0.0032% (see Figure 2).

Light Curve Fits

We use the Divide-White method described by Stevenson et al. (2014) to model the wavelength-dependent (i.e., spectroscopic) light curves, without making any prior assumptions about the form of the systematics, by utilizing information within the wavelength-independent (white) light curves. This can be done for an arbitrary number of wavelength bins, though ten to fifteen bins provides sufficient resolution to reveal features of interest while maintaining sufficient signal to noise in each bin.

To construct a spectrum, we are interested only in the relative transit depths of the different wavelength bins. We can therefore estimate uncertainties with our Differential Evolution Markov Chain Monte Carlo (DE-MCMC) algorithm, assuming fixed parameters for a/R* and cosi (Stevenson et al. 2014). For the HST, LDSS-3C (Section 2.3), and Spitzer (Section 2.4), we assumed a fixed a/R* of 7.2900 and a cosi of 0.070993, based on an analysis of the TESS data for WASP-79b (Section 2.1). The transit midpoint was carried as a free parameter and estimated in the WLC analyses and then fixed for the spectroscopic analyses, as it is wavelength-independent. Figure 2 shows results for the HST white light curve extraction as well as results for the 15 wavelength bins from the spectroscopic light curve extraction.

The results of the HST/WFC3 analysis, which indicate the presence of water in WASP-79b's atmosphere, are discussed in later sections.

LDSS-3C Observations and Data Analysis

In order to obtain a more complete picture of WASP-79b's atmospheric structure and to assess the slope (if any) of the spectrum, we extended our analysis for this planet to the visible and near-infrared using data from the Low Dispersion Survey Spectrograph (LDSS) optical imaging spectrograph on the 6.5 m Magellan II (Clay) Telescope at Las Campanas Observatory (LCO) in Chile. We used the LDSS-3C VPH-red grism (bandpass 0.6 -1.0 µm), which extended our spectral analysis of WASP-79b into the visible wavelengths where we expected to encounter the effects of Rayleigh scattering due to aerosols.

Our reduction, calibration, white light curve fitting, and spectroscopic light curve fitting processes use the T-RECS analysis pipeline and match the processes described in detail in Stevenson et al. (2016a). We will therefore only discuss details pertaining to this specific observation set.

Observations, Reduction, and Calibration

We observed the primary transit of WASP-79b on the night of 2016 Dec 20 for nearly 8 hours (00:31 -08:14 UT, airmass = (1.1 -1.0 -1.8) (4)), collecting 1230 science frames using 7-second integrations. We utilized LDSS-3C's turbo read mode with low gain and applied 2x2 pixel binning to minimize readout times, overall achieving a duty cycle of 31%. The most recent upgrade of the instrument to LDSS-3C constituted an upgrade to a deep-well detector that eliminated the fringing issues seen previously (Stevenson et al. 2016b).

Our science masks utilized three, 12"-wide slits for observations of our target star (WASP-79, V = 10.1) and the two comparison stars (V = 10.8, 12.7). The brighter comparison star is a G dwarf star with a T eff of 5834 K. The spectra from the dimmer comparison star were too noisy to provide reliable atmospheric corrections, so we relied strictly on the brighter reference star. Unfortunately, the brighter reference star was sufficiently displaced from the target star on the detector (146.7 arcsec) that the resulting atmospheric corrections are not necessarily consistent. This results in relatively large error bars on the transit depth estimates for the LDSS-3C data.

White Light Curve Fits

As described in Stevenson et al. (2016a), we correct for the observed flux variations caused by fluctuations in Earth's atmosphere by dividing the WASP-79b light curve by the comparison star. We start by fitting the white light curve (0.625 -1.025 µm) to maximize the signal-to-noise ratio (SNR), using both transit and systematics model components. The first utilizes a Mandel & Agol (2002) transit model with selected free parameters and fixed quadratic limb-darkening parameters derived from stellar Kurucz models (Castelli & Kurucz 2004) assuming a stellar temperature of 6500 K and log g of 4.2. We found early in the analysis that there was a shift of the illuminated pixels on the detector in the middle of the transit that was caused by the telescope rotating as it passed through zenith (Figure 4). For the systematics component, we tested various combinations of linear and quadratic models in combination with rotation and intra-pixel functions to account for the aforementioned rotation and pixel shift to determine which combination of models provided the best fit, based on the BIC and χ 2 values. Our final analytical model takes the form:

F (t) = F s T (t)R(t)Q(t)I(t) (2)
where F (t) is the measured flux at time t; F s is the outof-transit system flux; T (t) is the primary-transit model component with unity out-of-transit flux; R(t) = 1+aA+ bcos(π/180×(θ(t)+θ 0 )) is the time-dependent instrument rotation model component with free parameters a, b, and θ 0 , where A = airmass; Q(t) uses a quadratic polynomial to fit a pixel response ramp in the data; and I(y) fits the pixel shift using a linear function in the dispersion direction. The white light curve for the Dec 2016 LDSS-3C data resulted in a transit depth of 1.1626% ± 0.0152%.

Light Curve Fits

As with the HST/WFC3 data, we apply the Divide -W hite technique (Stevenson et al. 2014) to remove the wavelength-independent systematics. To account for the wavelength-dependent systematics, each spectroscopic channel requires a rotation correction with airmass, a quadratic function in time, and an intra-pixel response shift correction. Due to unfavorable weather effects during the night of the LDSS-3C observation, the displaced reference star, and the telescope rotation, we found the data to be very noisy with significant numbers of outliers in most channels. To remove these outliers, we performed the following iterative outlier rejection process:

1. We ran the simulation with no masking or outlier rejection so that we could visually determine whether there were any sections of the data that should be removed entirely. Based on the results of this run and the weather information for the observation timeframe, we removed times 02:16:14 UT -02:47:25 UT and times 03:24:58 UT -04:11:56 UT for all channels. Additionally, based on the normalized flux values (see Figure 5), the 6540-6590 and 7570-7700 channels were masked to remove them from the light curve analysis, as they showed atmospheric absorption that could not be accounted for using the reference star, which was artificially increasing the transit depths in those channels. There were significant changes in the local humidity over the course of the night, particularly between ∼05:00 UTC and ∼08:00 UTC that may have contributed to the noise in the data. 2. We then ran two consecutive boxcar median masks with 3σ rejection on the photon flux data.

3. We re-ran the simulation on the results from step 2, and ran three consecutive 3σ outlier rejection masks on the residuals for the resulting transit models.

4. Finally, we re-ran the simulation on the results from step 3, masking the outliers identified in steps 2 and 3.

In addition to the expected drift in the dispersion direction of the LDSS-3C spectrum over the course of the observation, Diamond-Lowe et al. ( 2018) found a stretching of the spectrum equal to approximately 4 pixels for the target star and 2 pixels for the comparison star. To account for this effect, we calculated the stretch and the drift by optimizing a cubic spline fit of the target spectrum normalized to the reference spectrum. Figure 6 shows the calculated spectrum drift and stretch over time for both the target and reference stars, and it can be seen that the spectral drift was in excess of 1 pixel for both the target and reference stars.

The results of the spectroscopic light curve extraction for the LDSS-3C data are shown in Figure 7. Due to the large amount of noise in the data, we restricted the spectroscopic LDSS-3C analysis to 8 channels to increase the SNR.

Results

Because the opacity of the exoplanet atmosphere varies with wavelength, the apparent size of the planet, and therefore the depth of the transit, also varies with wavelength. Having performed the spectroscopic light curve extraction and the systematics normalization via the Divide-White method, we can construct a spectrum from the relative transit depths of the selected wavelength bins.

Figure 9 shows the relative transit depths of the WASP-79b HST data for 15 wavelength bins for the light curve extraction using the Divide-White normalization method. In this figure, the positive y-axis represents increasing transit depth, i.e., more absorption by the WASP-79b atmosphere. The resulting spectrum displays a noticeable peak centered at 1.4 µm, which represents a water feature. This feature is consistent with water features found in the spectra of other hot Jupiters (Sing et al. 2016), and an atmospheric retrieval corroborates this feature. The black lines show the best-fit models, and the wavelength range for each of the 8 channels is specified in µm (Stevenson et al. 2016a). The grey points represent the original data, and the colored points represent the data that were retained from the noise and outlier masking process.

Figure 10 shows the relative transit depths of the WASP-79b LDSS-3C data for 8 wavelength bins for the light curve extraction using the Divide-White normalization method. It should be noted that the transit depth estimate for the 0.65 µm channels is likely somewhat low due to detector cutoff at the blue edge. Rackham et al. (2017) also found decreased transit depths at bluer wavelengths for GJ 1214b, a sub-Neptune orbiting a M4.5 dwarf star, which they attribute to the presence of faculae on the unocculted stellar disk. However, observations of WASP-79 indicate that its stellar activity is low. We collected XMM-Newton observations of WASP-79 on 2017-07-18, with S/N=3.4. Its X-ray emission, L X = 5.7×10 28 erg/s (for a d=248 pc, c.f. GAIA DR2) yields a ratio log L X /L bol = -5.5, indicating a low activity level, as expected for an early F star (Sanz-Forcada et al. in prep.).

The TESS data baseline varies within 1σ < 0.1%, so these data do not show evidence of short-term stellar activity variations in WASP-79. Furthermore, photometric observations of WASP-79 with the Tennessee State University C14 Automated Imaging Telescope (AIT) at Fairborn Observatory (see, e.g., Sing et al. (2015) for a description of AIT operations) show no significant brightness variability within the years 2017, 2018, and 2019. Nor does the AIT see significant variability from year to year over the same interval to a limit of ∼0.005 mag, confirming the absence of longer-term activity variations. The photometric stability of WASP-79 suggests that the decreased transit depth at shorter wavelengths is not likely to be due to inhomogeneities in the stellar photosphere. Given the low resolution of the LDSS it is not obvious what is causing the positive slope in the spectrum at bluer wavelengths.

As discussed in Section 2.3.1, the atmospheric corrections likely do not fully account for the atmospheric dynamics during the observation, and the very deep transit depth at 0.95 µm is likely exaggerated by interference from H 2 O in Earth's atmosphere. To account for red noise in the data, the uncertainties in the LDSS transit depth estimates are multiplied by the maximum correlated noise factor for each light curve.

Transit data for WASP-79b from the HST Space Telescope Imaging Spectrograph (STIS) instrument are currently being analyzed. STIS provides data from 0.3 -1.0 µm, and these data should have smaller uncertainties than the LDSS-3C data, providing more insight into the atmospheric structure of this hot Jupiter.

Spitzer Data

Observations

The observations analyzed here are part of Program ID 13044 (PI: Drake Deming). The target was observed during transit with IRAC channel 1 (3.6 µm) and channel 2 (4.5 µm) (Fazio et al. 2004). The Astronomical Observing Requests (AOR) are 62173184 and 62173696 for channels 1 and 2 respectively. All of these observations were carried out in sub-array mode (32 × 32 pixels, 39" × 39") with a 30 minute peak-up observation preceding them. The use of a peak up observation allows the instrument to stabilize the image on the detector 'sweet spot' and decreases the likelihood of a ramp in the data [START_REF] Ingalls | Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series[END_REF]. The frame time for both observations was 2 seconds.

Methods

For each AOR we began with Basic Calibrated Data (BCD) available on the Spitzer Heritage Archive. Each BCD file contains a cube of 64 frames of 64 × 64 pixels. Each set of 64 images comes as a single FITS file with a time stamp corresponding to the start of the first image. We determine the time of each frame in the set by adding the appropriate multiple of the frame time to the time stamp of the first image. The photometric extraction was performed following the methods detailed in Kilpatrick et al. (2017) and Kilpatrick et al. (2019) utilizing both fixed and variable apertures across a range of sizes. Background subtraction and determination of the stellar centroid and noise pixel parameter were performed in each case.

Each transit fit was based on the model of Mandel & Agol (2002) implemented in Python by the BATMAN package (Kreidberg et al. 2015). We assumed an orbital eccentricity of zero and used the a/R* and cosi values derived from the TESS data from Sectors 4 and 5. Stellar limb darkening parameters were derived from ATLAS models and interpolated bi-linearly from tables presented in Sing (2010). We choose to use the quadratic form and fix coefficients to [0.04735, 0.15251] and [0.0604, 0.11834] for channels 1 and 2 respectively. The intrapixel sensitivity variation [START_REF] Ingalls | Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series[END_REF], the change in measured flux as a function of stellar centroid position and methods of correction, are well documented (e.g. Ingalls et al. 2016). Here, we employ the Nearest Neighbors method (NNBR), otherwise known as Gaussian Kernel Regression with data (Lewis et al. 2013;Kilpatrick et al. 2017).

For each AOR, the best fit values for all free parameters were initially determined using matrix inversion. The standard deviation of the normalized residuals (SDNR) times the β red factor (Gillon et al. 2010) was used as a metric for selecting the best fit out of the multiple apertures. The results from the best fit aperture were passed to a Markov Chain Monte Carlo implemented by emcee (Foreman-Mackey et al. 2013) to derive uncertainties of each free parameter. The uncertainty on each data point in the light curve is inflated by the β red factor to account for the unresolved correlated noise. We use a number of walkers at least twice the number of free parameters and run for 10 5 steps per walker before testing for convergence using Gelman Rubin statistics with a threshold for acceptance of 1.01 (Gelman & Rubin 1992). The initial 10% of steps for each walker are discarded to remove the 'burn-in' period.

Results

At 4.5 µm we find a transit depth of 1.1396 % ± 0.0103 %. The SDNR of this observation was 0.04875 with a β red factor of 1.09. At 3.6 µm we find a transit depth of 1.1224 % ± 0.0080 % with an SDNR of 0.005505 and β red factor of 1.41. We find the center of transit time to occur 0.009835 ± 0.0008 days (14.15 ± 1.15 minutes) later than the predicted transit time (Smalley et al. 2012) 1 and 0.009743 ± 0.00035 days (14.0 ± 0.5 minutes) in channel 2.

Table 1 provides the wavebands, normalized transit depths, and 1σ transit depth uncertainties for the previously-described data sets. Table 2 provides the transit ephemerides and uncertainties for the TESS, HST/WFC3, and LDSS-3C observations. We used these transit times in conjunction with the Smalley et al. (2012) ephemeris to re-compute a new ephemeris and period for WASP-79b.

Transmission Spectra Retrieval Analysis

We performed two atmospheric retrievals on the HST, LDSS, TESS, and Spitzer data using the ATMO code, which is described extensively in other works (Amundsen et al. 2014;Tremblin et al. 2015[START_REF] Tremblin | [END_REF]Tremblin et al. , 2017;;Drummond et al. 2016;Goyal et al. 2018;Mikal-Evans et al. 2019). We performed a chemical equilibrium retrieval as well as a free-chemistry retrieval with FeH and H -, as FeH is one of the few molecules likely to be found at these temperatures that has a maximum opacity at 1 µm [START_REF] Tennyson | Atoms[END_REF]. For the stellar mass and radius, we assumed the main sequence values published by Smalley et al. ( 2012) -R * = 1.64 R and M * = 1.56 M -since their radius is consistent with that in the Gaia Data Release 2. We used a Differential-evolution MCMC to marginalize the posterior distribution (Eastman et al. 2013). We ran twenty-two chains each for 30,000 steps and discarded the first 2% of each chain as burn-in before combining them into a single chain.

For the model assuming chemical equilibrium, the relative elemental abundances for each model were calculated in equilibrium on the fly, with the elements fit assuming solar values and varying the metallicity ([M/H]). However, we allowed for non-solar elemental compositions by varying the carbon, oxygen and potassium elemental abundances ([C/C ], [O/O ], [K/K ]) separately. For the spectral synthesis, we included the spectrally active molecules of H 2 , He, H 2 O, CO 2 , CO, CH 4 , NH 3 , Na, K, TiO, VO, FeH, and Fe. The temperature was assumed to be isothermal, fit with one parameter, and we also included a uniform grey cloud parameterized by an opacity and a cloud top pressure level.

Figure 12 shows the chemical equilibrium retrieval spectrum with the estimated transit depths. Since the LDSS-3C spectrum for WASP-79b shows an unexpected positive slope from 0.65 µm to 0.8 µm, rather than the anticipated negative slope due to Rayleigh scattering, the model has a hard time reproducing the LDSS-3C data in the shorter wavelengths. This retrieval is driven toward a low temperature of ∼800 K, which would be unexpected for this planet, as the equilibrium temperature is ∼1800 K. The retrieval is also driven toward high clouds by the muted 1.3 µm range of the HST data, which is relatively flat and high compared to the 1.4 µm feature, which is large and dips down comparatively far at 1.6 µm. The chemical equilibrium model essentially is forced to use clouds to fit these features, though with a BIC of 70.75, this model does not provide a particularly good fit.

For the free-chemistry retrieval, we assumed a constant abundance for each molecule that was independently fit, and we varied the H 2 O, CO, Na, K, VO, FeH and H - abundances; we included only these molecules as we expect them to have strong spectral features in the wave-.3

.4 .5 .6 .7 .8 .9 1 1.5 2 2.5 3 3. bands corresponding to the data. Similar to the equilibrium model, we also included a grey cloud and assumed an isothermal temperature profile. The free-retrieval results in a better fit, with a BIC of 60.75 for the same number of data points and free parameters, as it fills in the 1.2 µm HST opacity, where we would expect to see a larger dip at ∼1 µm if water were the only absorber at these wavelengths (Figure 14, [START_REF] Tennyson | Atoms[END_REF]). With the opacity of FeH at ∼1µm, this model better accommodates the slope of the water feature at ∼1.6 µm as well as the diminishing opacity in the bluer wavelengths. The H -provides additional opacity in the 0.7 to 1.3 µm range, decreasing the amount of FeH in the atmosphere that is needed to reproduce the opacity in the HST data. The H 2 O volume mixing ratio is well-constrained to an abundance of -2.20 ≤ log(H 2 O) ≤ -1.55, which is 40x solar. Similar results have been found for WASP-121b (Evans et al. 2018;Mikal-Evans et al. 2019). This model also allows for a clearer atmosphere than the chemical equilibrium model. The temperature is still lower than that expected by equilibrium (1140 K ± 180), though the temperature uncertainties are large, and the marginalized distribution differs with the equilibrium value by less than 3-sigma confidence.

As can be seen in the posterior distribution in Figure 15, water and temperature are well-constrained. For the cloud top, we see a degeneracy between its altitude and .

3

.4 .5 .6 .7 .8 .9 1 1.5 2 2.5 3 3. Atmospheric spectrum from ATMO freechemistry retrieval based on HST, LDSS, TESS, and Spitzer transit depth estimates. The red line shows the best-fit model. With the FeH and H -, this model better accommodates the slope of the water feature at longer wavelengths as well as the diminished opacity in the bluer wavelengths. This model also accommodates a clearer atmosphere than the chemical equilibrium model, as well as a higher temperature (∼1200 K). This model had a BIC of 60.75 for 25 data points and 8 free parameters.

its opacity. We also see a degeneracy between FeH and H -, implying an upper limit to the amount of H -that we can expect in this atmosphere. The upper limit on VO implies that there is no significant amount in this atmosphere. The Spitzer data weakly constrain the upper limits for CO/CO 2 but do not provide a lower limit.

While we don't spectrally resolve Na, the free-chemistry retrieval includes it because the TESS transit depth is deeper than that for LDSS-3C, and the TESS data extend into wavebands where Na features are present. This can lift the retrieval model of the TESS data point above the LDSS-3C spectrum. In practice, other absorbers may be causing absorption shortward of the LDSS-3C data. Bean et al. (2018) provides the atmospheric retrieval results for WASP-79b including only the HST/WFC3 observation data with contributions from haze scattering. Figure 16 shows the retrieval spectrum with simulated JWST observation data and demonstrates the constraints that the LDSS-3C data place on the scattering slope for WASP-79b. With the large error bars of the LDSS-3C data and the precise TESS data, the LDSS-3C data do not highly constrain the retrieval, but they do help rule out large scattering slopes, as was previously thought to be likely (Bean et al. 2018) Using the methods described in Stevenson (2016), we compute a H 2 O -J(H) index for WASP-79b of 0.659. . The H -provides additional opacity in the 0.7 to 1.3 µm range, decreasing the amount of FeH in the atmosphere that is needed. This model allows for a clearer atmosphere than the chemical equilibrium model, as well as a higher temperature of ∼1200 K, which is more consistent with the expected equilibrium temperature of this planet.

Given its temperature and log g, this H 2 O -J(H) being less than 1.0 rules out the diagonal dashed line in Figure 2 of Stevenson (2016) as a suitable boundary between clear and cloudy atmospheres and provides a better constraint on the empirical relationship between water feature strength and surface gravity.

JWST Expectations

JWST simulated observations were generated using Pandexo (Batalha et al. 2017) with the retrieval model spectrum, assuming stellar T ef f = 6600 K, log g = 4.2, and [Fe/H] = +0.03 (Smalley et al. 2012). Figure 16 shows the simulated observations for the freechemistry retrieval model, providing an update to Bean et al. ( 2018)'s Figure 7 -which was generated using just the HST data -based on the inclusion of the LDSS, TESS, and Spitzer data in addition to the HST data. Given these additional data, we expect to see a flatter spectrum with less pronounced Rayleigh scattering and H 2 O and CO 2 features than was originally predicted for the JWST observations. WASP-121b (Evans et al. 2016) and HAT-P-26b (Wakeford et al. 2017) also showed a similar shape in the WFC3 spectrum, with muted depth in the 1.2 -1.3 µm wavelength interval compared to the depth of the water feature at 1.6 µm. Given the relatively moderate T eq of 990 K for HAT-P-26b, it would be unexpected for FeH to be present in its atmosphere in sufficient abundance to impact the transmission spectrum (Visscher et al. 2010), and this feature is likely best explained by a uniform scattering cloud (Wakeford et al. 2017). WASP-121b, however, has a T eq ∼2400 K, putting it in a temperature regime comparable to WASP-79b. Evans et al. (2016) compared models including haze only, TiO/VO, and TiO/VO/FeH and found that the models excluding FeH could not reproduce the WFC3 transmission spectrum at wavelengths near 1.3 µm (Evans et al. 2016). The comparable T eq s and similar spectrum shapes of WASP-121b and WASP-79b imply that FeH may be a spectral mechanism for both planets and should be considered in the models for similar exoplanets.

As Sing et al. (2016) note, hot Jupiters occupy a large parameter space with a wide range of gravities, metallicities, and temperatures, all of which affect a planet's atmospheric structure, circulation, and condensate formation. It is therefore difficult to predict the spectral features of a given exoplanet. In their investigation of the influences of nonuniform cloud cover on transmission spectra, Line & Parmentier (2016) found that the presence of inhomogeneous clouds along the terminators of transiting exoplanets can strongly influence our interpretation of current transit transmission spectra; that a nonuniform cloud cover along the planetary terminator can influence the observed transmission spectra; and that failing to account for nonuniform cloud cover can bias molecular abundance determinations. They demonstrated that the spectrum of a globally uniform deeper cloud has a flatter shape and deeper trough than that of a nonuniform cloud cover, but that a nonuniform cloud cover spectrum was nearly identical to that produced by an atmosphere with a high mean molecular weight (Line & Parmentier 2016).

However, the shape of the ingress and the egress of the transit is determined by the shape of the planetary limb and can potentially be used to constrain the cloud distribution over the planet limb and break the degeneracies between partial cloudiness and high mean molecular weight atmospheres. The shape of the residuals strongly depends on the distribution of clouds, and while the ingress and egress are symmetric in the case of polar clouds, they are antisymmetric in the case of morning clouds (Line & Parmentier 2016).

These are just a few reasons why exoplanet transit transmission data are needed from JWST, a 6.5 m, spacebased, near-to mid-infrared telescope. Unlike HST, which is maintained in a low Earth orbit that carries it around the globe approximately every 90 minutes, JWST will orbit at the Sun-Earth L2 point, giving it an uninterrupted view of the sky (Wakeford & Sing 2016). With this uninterrupted view, JWST should be able to provide transit data with sufficiently precise timing to enable de- VMR ln(VO) For the cloud top, we see a degeneracy between its altitude and its opacity. We also see a degeneracy between FeH and H -, implying an upper limit to the amount of H -that we can expect in this atmosphere. The lack of constraint on VO implies that it is not present in this atmosphere. The combination of the deeper TESS transit depth and shallower short-wavelength LDSS3 data caused the model to include Na in the atmosphere.

VMR log(K) -5 -4 -3 -2 -1 0 -12 -10 -8 -6 -4 -2 -5 -4 -3 -2 -1 0 -12 -10 -8 -6 -4 -2 -3.5 -3.0 -2.5 -2.0 -1.5 VMR log(H2O) -12 -10 -8 -6 -4 -2 VMR log(K) -3.5 -3.0 -2.5 -2.0 -1.5 -12 -10 -8 -6 -4 -2 -3.5 -3.0 -2.5 -2.0 -1.5 -1 2 -1 0 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 VMR log(CO) -12 -10 -8 -6 -4 -2 VMR log(K) -12 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 -1 2 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 VMR log(Na) -12 -10 -8 -6 -4 -2 VMR log(K) -12 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 -1 2 -1 0 -8 -6 -4 -2 -1 2 -10 -8 -6 -4 -2 VMR log(K)
2 -5 -4 -3 -2 -1 0 Cloud Top (Rp l ) -12 -10 -8 -6 -4 -2 VMR ln(K) -5 -4 -3 -2 -1 0 -12 -10 -8 -6 -4 -2 -3.5 -3.0 -2.5 -2.0 -1.5 VMR ln(H2O) -1 2 -1 0 -8 -6 -4 -2 VMR ln(K) -3.5 -3.0 -2.5 -2.0 -1.5 -1 2 -1 0 -8 -6 -4 -2 -1 2 -10 -8 -6 -4 -2 VMR ln(CO) -12 -10 -8 -6 -4 -2 VMR ln(K) -1 2 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 VMR ln(Na) -1 2 -1 0 -8 -6 -4 -2 VMR ln(K) -12 -10 -8 -6 -4 -2 -1 2 -1 0 -8 -6 -4 -2 -12 -10 -8 -6 -4 -2 VMR
-5 -4 -3 -2 -1 0 -12 -10 -8 -3.5 -3.0 -2.5 -2.0 -1.5 VMR ln(H2O) -1 2 -1 0 -8 VMR ln(VO) -3.5 -3.0 -2.5 -2.0 -1.5 -1 2 -1 0 -8 -1 2 -10 -8 -6 -4 -2 VMR ln(CO) -12 -10 -8 VMR ln(VO) -1 2 -10 -8 -6 -4 -2 -12 -10 -8 -12 -10 -8 -6 -4 -2 VMR ln(Na) -1 2 -1 0 -8 VMR ln(VO) -12 -10 -8 -6 -4 -2 -1 2 -1 0 -8 -1 2 -1 0 -8 -6 -4 -2 VMR ln(K) -12 -10 -8 VMR ln(VO) -1 2 -1 0 -8 -6 -4 -2 -
tection of clouds at the terminator. These more precise observations in a broader range of wavelengths will allow JWST observations of WASP-79b to contribute to the identification of clouds vs hazes in the atmosphere of this hot Jupiter. With its muted but detectable water feature and its occupation of the clear/cloudy transition region of the temperature/gravity phase space, WASP-79b continues to represent an interesting target for the ERS program.

CONCLUSIONS

As part of the PanCET program, we have performed a spectral analysis of the hot Jupiter WASP-79b using HST/WFC3 data (1.1 -1.7 µm) and the process described in Stevenson et al. (2014). We have detected a probable water feature centered at 1.4 µm that is consistent with the spectra of other hot Jupiters. The LDSS-3C data (0.6 -1.0 µm) are noisy, and the location of the reference star relative to the target star hindered negation of atmospheric effects occurring during the observation. The spectrum extracted from the LDSS-3C data is therefore difficult to interpret, but overall looks relatively flat. In conjunction with the muting of the water feature in the HST/WFC3 spectrum, this may indicate the presence of clouds in the atmosphere of this hot Jupiter, though ATMO models indicate that including the absorbers FeH 2018), which shows the Pandexo results for the best-fit solution for just the HST/WFC3 data with contributions from haze scattering. Right: anticipated constraints (red) on the atmospheric temperature and water abundance compared with constraints from HST (blue). The constraints are improved by orders-of-magnitude due to increased data resolution and the presence of multiple water features (Greene et al. 2016).

and H -provides a better fit to the data and allows for a temperature more consistent with the equilibrium temperature. The XMM Newton, TESS, and AIT observation data indicate that the decreased transit depths in bluer wavelengths of the LDSS-3C data are not caused by stellar faculae or plage, though the low resolution of these spectral data makes it difficult to determine what may be causing these shallower transit depths. The transit depths estimated from the TESS, LDSS, HST, and Spitzer data are all in good agreement, indicating the viability of the methods described herein.

WASP-79b represents a primary target for the PanCET program, and given the detectable water feature and the delayed launch of the JWST, it is now a primary target for the JWST Early Release Science (ERS) program (Bean et al. 2018) and will be scheduled for 42 hours of JWST observation time in four different modes. These observations will provide more precise data over a broader range of wavelengths, providing a more detailed spectrum and possibly allowing for the detection of terminator clouds and/or vibrational modes of condensate species.

Figure 1 .

 1 Figure 1. Transit depth estimates for the 12 transits of WASP-79b available from TESS. Estimates are shown with 1σ uncertainties. The red lines indicate the weighted mean of the transit depths with 1σ uncertainties.

Figure 4 .

 4 Figure 4. (a) The Cassegrain Position Rotator Angle as a function of time for the white light curve (WLC) transit extraction. Note that the telescope passed through zenith, as indicated by both the telescope position and the airmass (b). This resulted in a shift of the illumination on the detector and an associated shift in the relative flux between the target and reference stars, as shown in (c).

Figure 5 .

 5 Figure 5. Two-dimensional light curve for the Dec 2016 LDSS-3C WASP-79b observations showing the flux of the target star normalized against the flux of the reference star. Normalized flux is shown per wavelength as a function of frame number. The 6540-6590, 7570-7700, and 9250-9750 channels show increased absorption, particularly early on in the observation. The 6540-6590 and 7570-7700 channels were masked to remove their influence from the light curve extraction. The solid vertical lines indicate the times for which data was removed based on visual inspection as described in Step 1 of the iterative outlier rejection process.

Figure 6 .Figure 7 .

 67 Figure6. Spectral drift in the dispersion direction and spectral stretch over the course of the observation for the target and reference stars. The drift was in excess of 1 pixel for both the target and reference stars, while the stretch was 4 pixels for the target star over the course of the observation.

Figure 8 .

 8 Figure 8. White and spectroscopic residuals for the light curves extracted from the LDSS-3C data. Values represent 1σ residuals. The gaps in the spectroscopic plots indicate times for which noisy observation data were masked.

Figure 11 .

 11 Figure 11. Comparison of observed transit times with computed transit times for Smalley, WFC3, LDSS-3C, Spitzer, and TESS observations. Computed transit times are based on the updated ephemeris and orbital period provided in Table 2.

Figure 12 .

 12 Figure 12. Atmospheric spectrum from chemical equilibrium ATMO retrieval based on HST, LDSS, TESS, and Spitzer transit depth estimates. The red line shows the best-fit model, and the blue areas indicate the 1, 2, and 3σ uncertainties. Due to the high cloud deck that the model is driven to by the opacity at ∼1µm, this model does not fit the decreased absorption at 1.6 µm or the positive slope in the bluer wavelengths. This model had a BIC of 70.75 for 25 data points and 8 free parameters.

  Figure 13.Atmospheric spectrum from ATMO freechemistry retrieval based on HST, LDSS, TESS, and Spitzer transit depth estimates. The red line shows the best-fit model. With the FeH and H -, this model better accommodates the slope of the water feature at longer wavelengths as well as the diminished opacity in the bluer wavelengths. This model also accommodates a clearer atmosphere than the chemical equilibrium model, as well as a higher temperature (∼1200 K). This model had a BIC of 60.75 for 25 data points and 8 free parameters.

Figure 14 .

 14 Figure14. Atmospheric spectra from ATMO free chemistry retrieval showing opacity contributions from potential atmospheric components. H2O and FeH constitute the bulk of the atmospheric opacity, with FeH providing increased opacity at ∼1µm. The H -provides additional opacity in the 0.7 to 1.3 µm range, decreasing the amount of FeH in the atmosphere that is needed. This model allows for a clearer atmosphere than the chemical equilibrium model, as well as a higher temperature of ∼1200 K, which is more consistent with the expected equilibrium temperature of this planet.

Figure 15 .

 15 Figure 15. Pairs plot for the free chemistry atmospheric retrieval showing variable correlations and constraints. The orange crosses indicate the median best fit values, and the dashed lines show the 1σ uncertainties. Water and temperature are wellconstrained.For the cloud top, we see a degeneracy between its altitude and its opacity. We also see a degeneracy between FeH and H -, implying an upper limit to the amount of H -that we can expect in this atmosphere. The lack of constraint on VO implies that it is not present in this atmosphere. The combination of the deeper TESS transit depth and shallower short-wavelength LDSS3 data caused the model to include Na in the atmosphere.

Figure 16 .

 16 Figure 16. JWST simulated observations (left) and anticipated temperature and water constraints (right) from the PanCET Program observations of WASP-79b. Left: the simulated observations were generated using Pandexo (Batalha et al. 2017), based on the free-chemistry atmospheric retrieval spectrum and the observation data described previously. Simulated observations are shown with the estimated LDSS, TESS, HST, and Spitzer transit depths. Results are binned to R = 100 (left). The LDSS-3 data constrain the scattering slope, compared to Figure 7 in Bean et al. (2018), which shows the Pandexo results for the best-fit solution for just the HST/WFC3 data with contributions from haze scattering. Right: anticipated constraints (red) on the atmospheric temperature and water abundance compared with constraints from HST (blue). The constraints are improved by orders-of-magnitude due to increased data resolution and the presence of multiple water features(Greene et al. 2016).

Time from Measured Transit Center (hrs)

		0 250 250 500 0 0 500 500 0 500 500 0 500	3	2	1	0	1	2	White 1.125-1.160 1.160-1.195 1.195-1.230 1.230-1.265
	Residuals (ppm)	500 0 500 500 500 0 0 500 500 500 0 500 500 0 500 0 500 500 500 500 0 0 500 500 0 500 500 500 500 0 500 0 500	3	2	1	0	1	2	1.615-1.650 1.265-1.300 1.300-1.335 1.335-1.370 1.370-1.405 1.405-1.440 1.440-1.475 1.475-1.510 1.510-1.545 1.545-1.580 1.580-1.615
	Figure 3. White and spectroscopic residuals for light curves
	extracted from the HST/WFC3 data. Values represent 1σ
	residuals.

  Spectrum constructed from transit depths of 15 wavelength bins of HST/WFC3 data. Inversion of the transit depth provides a representation of the relative absorption at different wavelengths. The increased absorption at 1.4 µm indicates a water absorption feature. The horizontal error bars indicate the wavelength bins used for the light curve analysis.

		1.17				1.836
		1.16				1.224
	Transit Depth (%)	1.12 1.13 1.14 1.15				1.224 0.612 0.000 0.612 Scale Height
		1.11					1.836
		1.1 1.10	1.2	1.3 Wavelength ( m) 1.4 1.5	1.6	1.7	2.448
	Figure 9.

  Spectrum constructed from transit depths of 8 wavelength bins of LDSS-3C data. The large spread in transit depth estimates -particularly noticeable at 0.9 and 0.95 µm -is likely due to interference from Earth's atmosphere that could not be fully accounted for due to the distance of the reference star from the target star. The 0.65 µm point may be low due to detector cutoff at the blue edge. The transit depth estimates for the white light curve analysis described in 2.3.2 and for the TESS analysis (Section 2.1) are provided for comparison.

		1.250					7.65
		1.225					6.12
	Transit Depth (%)	1.075 1.100 1.125 1.150 1.175 1.200	TESS Transit Depth White Transit Depth		3.06 4.59 1.53 0.00 1.53 3.06 Scale Height
		1.050					4.59
		0.6 1.025	0.7	0.8 Wavelength ( m) 0.9	1.0	1.1	6.12
	Figure 10.

Table 1 .

 1 Normalized Transit Depths and Uncertainties

	Instrument	Waveband	(Rp/R * ) 2 σ (Rp/R * ) 2
		(µ m)
	TESS	0.586 -1.031	1.1396	0.014
		0.625 -0.67	1.0725	0.0316
		0.675 -0.725	1.0955	0.0206
		0.725 -0.757	1.1026	0.0101
	LDSS-3C	0.770 -0.825	1.1175	0.0073
		0.825 -0.875	1.1209	0.0204
		0.875 -0.925	1.1610	0.0205
		0.925 -0.975	1.2071	0.0215
		0.975 -1.025	1.1282	0.0332
		1.125 -1.160	1.1486	0.0050
		1.160 -1.195	1.1514	0.0053
		1.195 -1.230	1.1398	0.0051
		1.230 -1.265	1.1395	0.0047
		Table 1 continued

Table 2 .

 2 Transit Times and Uncertainties

	Instrument	Transit Times Transit Time Error
		(BJDTDB)
	Spitzer	2457713.37538	8.0e-04
		2457720.70005	3.5e-04
	LDSS-3C	2457742.674342	6.7e-05
	HST/WFC3	2457815.92219	1.1e-04
		2458412.89196	5.4e-04
		2458416.55480	2.9e-04
		2458427.54200	3.0e-04
		2458431.20355	3.1e-04
		2458434.86644	2.9e-04
	TESS	2458438.52868	3.1e-04
		2458442.19138	2.9e-04
		2458445.85332	3.0e-04
		2458449.51586	3.3e-04
		2458453.17815	3.2e-04
		2458456.84066	3.2e-04
		2458460.50406	3.0e-04
	New Epoch	2455545.23874	3.7e-04
	New Period (days)	3.66239264	5.6e-07
		3. DISCUSSION

Acknowledgements Support for program GO-14767 was provided by NASA through a grant from the Space Telescope Science Institute (STScI), which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. This work is also based on observations made with the LCO Magellan Clay Telescope. Travel to LCO/Magellan was funded by the Sagan Fellowship Program, supported by NASA and administered by the NASA Exoplanet Science Institute (NExScI). We would like to thank Hannah Diamond-Lowe and Zach Berta-Thompson for their assistance with the LDSS-3C stretching analysis. Work done by B.M. Kilpatrick was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program under Grant Number 80NSSC17K0484. This portion of the work is based on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. Alain Lechavelier des Etangs acknowledges support from the Centre National d' Études Spatiale (CNES). Jorge Sanz-Forcada acknowledges funding by the Spanish MINECO grant AYA2016-79425-C3-2-P. This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (project Four Aces; grant agreement No 724427). It has also been carried out in the frame of the National Centre for Competence in Research PlanetS supported by the Swiss National Science Foundation (SNSF).

Software: ATMO(Amundsenetal.2014;Tremblinetal. 2015Tremblinetal. , 2016Tremblinetal. , 2017;;Drummond et al. 2016;Goyal et al. 2018;Mikal-Evans et al. 2019), BATMAN (Kreidberg et al. 2015), T-RECS (Stevenson et al. 2016a)