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A&A
Volume 666, October 2022
Article Number L10
Number of page(s) 21
Section Letters to the Editor
DOI https://doi.org/10.1051/0004-6361/202244489
Published online 13 October 2022

© T. Azevedo Silva et al. 2022

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article is published in open access under the Subscribe-to-Open model. Subscribe to A&A to support open access publication.

1. Introduction

Ultra-hot Jupiters are currently the most readily accessible laboratories for the study of exoplanet atmospheres. Their size and large atmospheric scale heights, combined with the proximity to the host stars, make them appealing targets for the study of light that is transmitted through planetary atmospheres. With the recent developments of instruments for high-resolution spectroscopy (e.g., ESPRESSO; Pepe et al. 2010, 2021), the enhanced ability to retrieve high-resolution planetary spectra from the transit observations of ultra-hot Jupiters provided unique glimpses into the atmosphere of these extreme worlds. From the detection of several chemical species (e.g., Casasayas-Barris et al. 2019; Tabernero et al. 2021) to evaporating atmospheres (e.g., Yan & Henning 2018) and the study of winds (e.g., Ehrenreich et al. 2020; Seidel et al. 2021), resolving line features over short exposures has proven to be key to unraveling these distant alien atmospheres.

Two of the best examples are WASP-76b and WASP-121b (West et al. 2016; Delrez et al. 2016). Both planets are inflated ultra-hot Jupiters on orbits with periods shorter than two days and equilibrium temperatures close to 2500 K (for more information, see Appendix B.1). They were observed with ESPRESSO, and on one of the observing nights, the four UTs of the Very Large Telescope (VLT) were used. These targets are currently benchmarks in the study of atmospheric composition and dynamics (Seidel et al. 2019; Ehrenreich et al. 2020; Tabernero et al. 2021; Fortney et al. 2021; Sánchez-López et al. 2022). Transmission spectroscopy studies report the detection of species from H1, Li, Na, Mg, K, Ca+, V, Cr, Mn, Fe, Co1, Ni, and Sr+ for WASP-76b (Tabernero et al. 2021; Kesseli et al. 2022) and H, Li, Na, Mg, K, Ca, Ca+, Sc+, V, Cr, Mn1, Fe, Fe+, and Ni for WASP-121b (Hoeijmakers et al. 2020; Borsa et al. 2021; Merritt et al. 2021) using ESPRESSO high-resolution observations for two transits each. The detection of these species, together with their respective velocities, broadening, and depths, provides important insights into the composition and dynamics of these extreme atmospheres.

In this study we revisit these datasets and extend the list of currently detected species. This paper is structured as follows. In Sect. 2 we describe the observations, and in Sect. 3 we show how we reduced the data, extracted the planetary spectra, and cross-correlated these spectra with synthetic spectra that were specifically designed for ultra-hot Jupiters. The results and discussion are then given in Sect. 4.

2. Observational data

We analyzed data from two transits of WASP-76b and WASP-121b that were observed with ESPRESSO. These same datasets have recently been studied and led to the detection of multiple species for each of the planets (WASP-76b: Tabernero et al. 2021; Kesseli et al. 2022; WASP-121b: Borsa et al. 2021). The 1UT observations we used were obtained as part of the ESPRESSO Guaranteed Time Observations (program 1102.C-0744, PI: F. Pepe) that cover a wavelength range from 3800 Å to 7880 Å. The HR21 mode (high resolution with 2 × 1 binning, Pepe et al. 2021) was used, and a resolution of R ∼ 140 000 was achieved. The 4UT observations were taken during the commissioning of ESPRESSO and used the MR42 mode (medium resolution with 4× and a 2× binning in the spatial and dispersion directions, R ∼ 70 000). The observations are summarized in Table 1. For more information, we refer to Tabernero et al. (2021) and Borsa et al. (2021).

Table 1.

Summary of the transit observations of WASP-76b and WASP-121b.

The data were reduced using version 2.2.8 of the Reduction Software (DRS) pipeline2. From the obtained data products, we used the sky-subtracted 1D (orders merged) spectra S1D_SKYSUB_A.

3. Planetary transmission spectrum and cross-correlation analysis

3.1. Telluric correction

Before light reaches the VLT mirrors, it crosses Earth’s atmosphere, which leaves its imprints on the observed spectra in the form of terrestrial absorption features. To correct for Earth absorption lines, we use the Molecfit3 pipeline (Smette et al. 2015; Kausch et al. 2015) within the ExoReflex environment (Freudling et al. 2013) as in Allart et al. (2017). With this same tool, we simultaneously accounted for the barycentric Earth radial velocity (BERV) in each exposure (Allart et al. 2017). The wavelength regions we used to fit the terrestrial features are 6890–6900 Å, 7160–7340 Å, and 7590–7770 Å (as in Tabernero et al. 2021). These regions were selected because they are rich in telluric lines and poor in stellar features. We alternatively attempted to optimize these regions by defining more smaller regions and were very careful to exclude any stellar features. However, the two reductions produced similar results (illustrated in Fig. C). In Appendix C we provide our Molecfit input parameters together with an illustrative plot of before and after telluric correction around a single line of the sodium doublet (5891.58 Å, Fig. C.1).

3.2. Planetary spectrum extraction

To extract the planetary transmission spectrum, we followed a reasoning similar to the techniques outlined by Redfield et al. (2008) and Wyttenbach et al. (2015). These techniques have been successfully applied and improved in many recent studies using high-resolution transmission spectroscopy (e.g., Yan et al. 2017; Allart et al. 2020; Tabernero et al. 2021; Borsa et al. 2021; Casasayas-Barris et al. 2021; Seidel et al. 2022).

We started by shifting each individual spectrum into the reference frame of the star. By applying Keplerian models, we corrected for the Doppler shifts arising from the orbital pull of the planet. We then created a template of the star without any planetary absorption. To do this, we combined the out-of-transit exposures into a stellar spectrum with a high signal-to-noise ratio, called the master-out. To build this master-out, we first corrected the shape of the retrieved continuum changes for flux variations across the exposures that are due to different atmospheric conditions (airmass, seeing, etc.). We started by selecting the spectrum with the lowest airmass as the reference, and divided each of the individual spectra by this reference. We then masked the region of the spectrum in which the signal-to-noise ratio was low4 or that included strong telluric features5 and fit a third-degree polynomial function to the unmasked data. We divided out the trend for each of the individual spectra and combined the corrected out-of-transit spectra with a weighted average to create a preliminary master-out, using the inverse square of flux uncertainties as the weights.

We then performed a similar procedure, in which we instead divided the individual spectra by the created preliminary master-out. The reason for this additional step was that all the individual spectra (in-transit and out-of-transit) were later divided by the same out-of-transit template. As a result of this division, a clear wiggle pattern becomes visible across the spectra. This is to be expected for the ESPRESSO data, as noted by Tabernero et al. (2021) and Borsa et al. (2021). In Appendix D we show the wiggles across the wavelength range for a single exposure of WASP-121b with the 4UTs. The wiggle amplitude and frequency vary across wavelengths and do not behave as perfect sinusoids. To correct for these wiggles together with residual features from the flux normalization, we fit each spectrum with splines6. We then divided our spectra over the fit splines. An example of this fitting is illustrated in Fig. D.1.

Finally, we shifted these individual spectra according to the orbital velocity of the planet and computed the weighted averages of the spectral regions of interest. We thus created masters of the out-of-transit and in-transit data in the rest frames of the planet and star.

3.3. Cross-correlation analysis

After the planetary transmission spectrum was retrieved for each of the exposures, we performed a cross-correlation analysis with all the templates from The Mantis Network I7 (Kitzmann et al. 2021). These templates allow for the use of individual lines that would otherwise go unnoticed due to the high noise in the retrieved planetary spectrum. By using the cross-correlation function (CCF) approach, these individual lines can be combined into a detectable line profile. For the WASP-76b and WASP-121b line mask, we considered an isothermal atmosphere at 2500 K8 because of the equilibrium temperatures of the two planets (West et al. 2016; Delrez et al. 2016) and in line with the application outlined in Kitzmann et al. (2021). The number of lines used per species in our wavelength range is listed in Appendix E.

We computed the CCFs in the planet rest frame, with the previously mentioned binary masks, using the SciPy cross-correlation tool (Virtanen et al. 2020). For an easier visualization of the absorption signal, we also produced tomography plots and computed the absorption across a 2D cross-correlation grid in the Kp–planet velocity plane (hereafter Kp plots). For examples, see Fig. 1.

thumbnail Fig. 1.

Cross-correlation of the Ba+ mask with the retrieved planetary spectra for the two observation nights of WASP-76b (top on 2018 September 3, and bottom on 2018 October 31). Left: cross-correlation functions of the averaged in-transit exposures on the planetary frame of reference. Center: Kp-plots. Map of the sum of all the individual exposures in the planet rest frame across different values in the Kp–planet velocity plane. The dashed green lines represent the expected position of the planetary signal on this map. Right: tomographic plots in the planetary rest frame. The white lines represent the transit contacts.

The tomography plots show the signature of the Rossiter–McLaughlin effect (RM). Because of current limitations and uncertainties (Casasayas-Barris et al. 2021) in the modeling of the RM and the associated center-to-limb variation (CLV), we chose not to attempt to model these effects. Instead of modeling, we masked the region that matched the stellar velocities (−15 km s−1 to +15 km s−1 in the stellar rest frame) and combined the remaining signal. In addition to masking the stellar component, this process removes part of the planetary signal, which at times can cause a diminished S/N. An illustration of this masking for the F9 mask is shown in Appendix F.

We fit Gaussian profiles to the CCFs of the species with visible planetary absorption features. We used the lmfit Python package (Newville et al. 2016) to find the best-fit values and respective uncertainties. We did not perform a CCF for hydrogen9, but instead directly fit the Hα line on the retrieved planetary spectrum (master-in). However, we do not expect the Ca+ absorption to follow a Gaussian profile. As mentioned in Borsa et al. (2021), the Ca+ H&K lines are significantly blueshifted and their profiles are wider and deeper than those of any other species, which suggests that it extends beyond the Roche lobe10. The authors also noticed slight asymmetries in these line profiles and pointed to planetary atmospheric escape as a possible explanation. In our analysis, we found similar results and a clear asymmetric profile for the 4 UT partial transit. The individual H&K lines and the combined CCF using the Mantis mask both show extended blueshifted absorption (see Fig. G.1) beyond an underlying Gaussian profile. This indicates that calcium may be escaping the planetary atmosphere. A detailed modeling of this profile might confirm this hypothesis and allow an estimate of the atmospheric escape rate of calcium.

4. Results and discussions

In Table A.1 we list the species for which a visual inspection showed tentative absorption features, together with the best-fit values and uncertainties from the Gaussian fit parameters (amplitude, center RV, and full width at half maximum, FWHM). The CCF line profile and Kp-plots for each of these are provided in Appendix H.

For WASP-76b, we find a new chemical species in the atmosphere of this planet, Ba+. It shows a strong absorption signal on both of the observing nights. We also confirm the detections made by Tabernero et al. (2021) and Kesseli et al. (2022) of H, Li, Na, Mg, Ca+, V, Cr, Mn, and Fe. The strongest K lines lie in a region that we excluded because of high telluric contamination; therefore, K was not included in our study. We did not recover Co, Ni, and Sr+ either, which were claimed by Kesseli et al. (2022). The reason might be differences in the retrieval process.

We confirm the detections of H, Li, Na, Mg, Ca+, V, Cr, Mn, Fe, and Fe+ that were claimed by Borsa et al. (2021) and of Ca and Ni by Merritt et al. (2021) in WASP-121b. The new species we claim to be present in the atmosphere of WASP-121b are Ba+, Co, and Sr+. In addition to these, we also find tentative evidence of the presence of Ti+. It was visible when we removed the signal that matched the stellar velocities (see Fig. G.2).

Overall, we see the trend that most of the detected species are blueshifted relative to their expected line positions. This trend was also observed in previous studies (e.g., Cauley et al. 2021; Pai Asnodkar et al. 2022) and is expected to be due to the winds across the terminator, which move from the dayside to the nightside of the planet.

Another surprising finding is the detection of Ba+ in both planets. This is the heaviest detected element in exoplanetary atmospheres to date. The datasets of WASP-76b and WASP-121b represent some of the highest currently available S/N datasets. That Ba+ is detected in both of the studied planets may indicate that this heavy species can be common in the atmospheres of ultra-hot Jupiters. The CCF plots, tomography plots, and Kp-plots are shown in Figs. 1 and 2 for the two planets. Close to the expected planet velocity lies a clear absorption signal that follows the planetary Kp in all the exposures. Faint absorption signals directly on the planetary spectrum at the position of the strongest lines of the Ba+ CCF mask are likewise visible (Appendix I). We also note the ionization trend of these alkaline earth metals (Ca+, Sr+, and Ba+). The presence of these heavy ionized species at high altitudes in the atmospheres of ultra-hot Jupiters may be evidence of unexpected atmospheric dynamics. It is beyond the scope of this paper to describe the mechanisms that would explain the presence of these species in the upper layers of the atmosphere. However, we hope that we encourage further atmospheric modeling with this discovery.

thumbnail Fig. 2.

Same as Fig. 1, but for the WASP-121b observing nights (top in 1UT mode on 2018 November 30, and bottom in 4UT mode on 2019 January 6).

As studied in Borsa et al. (2021), we also note the much higher S/N and clearer absorption features for the lower-resolution 4UT partial transit (despite the lower resolution: ∼70 000). This clearly demonstrates the potential of the 16m equivalent mirror or of future high-resolution spectrographs for the Extremely Large Telescope (e.g., ANDES; Marconi et al. 2021).

1

For these species, only tentative detections are given. We confirm H in WASP-76b and Mn in WASP-121b as detected.

4

Regions in which the signal-to-noise ratio is significantly below the baseline (> 5σ), e.g., < 3900 Å.

5

Regions in which the telluric correction was inadequate because of low flux from strong telluric absorption, e.g., 6850–7700 Å.

6

We fit the splines over spectral segments of ∼200 Å. As a first step, we also tried to fit the wiggles in each exposure using varying sinusoids on limited wavelength intervals, but we found better results with the spline method.

7

We performed the CCF study with templates from the following species: Li, O, Na, Mg, Al, Si, P, S, K, Ca, Ca+, Sc, Sc+, Ti, Ti+, V, V+, Cr, Cr+, Mn, Mn+, Fe, Fe+, Co, Ni, Ni+, Cu, Zn, Ga, Ge, Rb, Sr, Sr+, Y, Y+, Zr, Zr+, Nb, Mo, Ru, Rh, Pd, Cd, In, Sn, Te, Cs, Ba, Ba+, La, La+, Ce, Ce+, Pr, Nd, Nd+, Sm, Sm+, Eu, Eu+, Gd, Gd+, Tb, Tb+, Dy, Dy+, Ho, Ho+, Er, Er+, Tm, Tm+, Yb, Lu, Lu+, Hf, Hf+, W, Re, Os, Ir, Pt, Tl, Pb, Bi, Th, Th+, U, and U+. Some other species were available but had no lines in our wavelength region of interest.

8

For Fe+, given the empty line list at 2500 K, we used the mask corresponding to a temperature of 3000 K.

9

No Mantis masks were available for hydrogen.

10

We estimated the effective planet radius at the line center by assuming R eff 2 / R p 2 =(δ+h)/δ $ R_\text{eff}^2 / R_\text{p}^2 = (\delta + h)/\delta $, where δ is the transit depth and h is the transmitted line amplitude (Chen et al. 2020). For Ca+ in WASP-121b, we find effective radii of ∼1.7 Rp (night 1) and ∼2.1 Rp (night 2), in agreement with Borsa et al. (2021).

Acknowledgments

This work was supported by Fundação para a Ciência e a Tecnologia (FCT) and Fundo Europeu de Desenvolvimento Regional (FEDER) via COMPETE2020 through the research grants UIDB/04434/2020, UIDP/04434/2020, PTDC/FIS-AST/32113/2017 & POCI-01-0145-FEDER-032113, PTDC/FIS-AST/28953/2017 & POCI-01-0145-FEDER-028953. This work has been carried out in the frame of the National Centre for Competence in Research PlanetS supported by the Swiss National Science Foundation (SNSF). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project SPICE DUNE, grant agreement No 947634). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project FOUR ACES; grant agreement No 724427). T.A.S acknowledges support from the Fundação para a Ciência e a Tecnologia (FCT) through the Fellowship PD/BD/150416/2019 and POCH/FSE (EC). O.D.S.D. is supported in the form of work contract (DL 57/2016/CP1364/CT0004) funded by FCT. R.A. is a Trottier Postdoctoral Fellow and acknowledges support from the Trottier Family Foundation. This work was supported in part through a grant from FRQNT. This work has been carried out within the framework of the National Centre of Competence in Research PlanetS supported by the Swiss National Science Foundation. The authors acknowledge the financial support of the SNSF. F.B. acknowledges support from PRIN INAF 2019. C.M.J. acknowledges FCT and POCH/FSE (EC) support through Investigador FCT Contract 2021.01214.CEECIND/CP1658/CT0001. H.M.T. acknowledges financial support from the Agencia Estatal de Investigación of the Ministerio de Ciencia, Innovación y Universidades through project PID2019-109522GB-C51/AEI/10.13039/50110001103 E.E-B. acknowledges financial support from the European Union and the State Agency of Investigation of the Spanish Ministry of Science and Innovation (MICINN) under the grant PRE2020-093107 of the Pre-Doc Program for the Training of Doctors (FPI-SO) through FSE funds. F.P.E. and C.L.O. would like to acknowledge the Swiss National Science Foundation (SNSF) for supporting research with ESPRESSO through the SNSF grants nr. 140649, 152721, 166227 and 184618. The ESPRESSO Instrument Project was partially funded through SNSF’s FLARE Programme for large infrastructures. Y.A. acknowledges the support of the Swiss National Fund under grant 200020_172746. D.E. acknowledges financial support from the Swiss National Science Foundation for project 200021_200726. N.J.N. was financed by projects POCI-01-0145-FEDER-028987, PTDC/FIS-AST/28987/2017, PTDC/FIS-AST/0054/2021 and EXPL/FIS-AST/1368/2021, as well as UIDB/04434/2020 & UIDP/04434/2020, CERN/FIS-PAR/0037/2019, PTDC/FIS-OUT/29048/2017. A.S.M. acknowledges financial support from the Spanish Ministry of Science and Innovation (MICINN) under 2018 Juan de la Cierva program IJC2018-035229-I. A.S.M. acknowledges financial support from the MICINN project PID2020-117493GB-I00 and from the Government of the Canary Islands project ProID2020010129.

References

  1. Allart, R., Lovis, C., Pino, L., et al. 2017, A&A, 606, A144 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  2. Allart, R., Pino, L., Lovis, C., et al. 2020, A&A, 644, A155 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Borsa, F., Allart, R., Casasayas-Barris, N., et al. 2021, A&A, 645, A24 [EDP Sciences] [Google Scholar]
  4. Bourrier, V., Ehrenreich, D., Lendl, M., et al. 2020, A&A, 635, A205 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Casasayas-Barris, N., Pallé, E., Yan, F., et al. 2019, A&A, 628, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  6. Casasayas-Barris, N., Palle, E., Stangret, M., et al. 2021, A&A, 647, A26 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  7. Cauley, P. W., Wang, J., Shkolnik, E. L., et al. 2021, AJ, 161, 152 [Google Scholar]
  8. Chen, G., Casasayas-Barris, N., Pallé, E., et al. 2020, A&A, 635, A171 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Delrez, L., Santerne, A., Almenara, J. M., et al. 2016, MNRAS, 458, 4025 [NASA ADS] [CrossRef] [Google Scholar]
  10. Ehrenreich, D., Lovis, C., Allart, R., et al. 2020, Nature, 580, 597 [Google Scholar]
  11. Fortney, J. J., Dawson, R. I., & Komacek, T. D. 2021, J. Geophys. Res. (Planets), 126, e06629 [NASA ADS] [Google Scholar]
  12. Freudling, W., Romaniello, M., Bramich, D. M., et al. 2013, A&A, 559, A96 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Hoeijmakers, H. J., Seidel, J. V., Pino, L., et al. 2020, A&A, 641, A123 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  14. Høg, E., Fabricius, C., Makarov, V. V., et al. 2000, A&A, 355, L27 [Google Scholar]
  15. Kausch, W., Noll, S., Smette, A., et al. 2015, A&A, 576, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  16. Kesseli, A. Y., Snellen, I. A. G., Casasayas-Barris, N., Mollière, P., & Sánchez-López, A. 2022, AJ, 163, 107 [NASA ADS] [CrossRef] [Google Scholar]
  17. Kitzmann, D., Hoeijmakers, J. H., Grimm, S. L., et al. 2021, A&A, submitted [arXiv:2112.11380] [Google Scholar]
  18. Marconi, A., Abreu, M., Adibekyan, V., et al. 2021, The Messenger, 182, 27 [NASA ADS] [Google Scholar]
  19. Merritt, S. R., Gibson, N. P., Nugroho, S. K., et al. 2021, MNRAS, 506, 3853 [NASA ADS] [CrossRef] [Google Scholar]
  20. Newville, M., Stensitzki, T., Allen, D. B., et al. 2016, Astrophysics Source Code Library [record ascl:1606.014] [Google Scholar]
  21. Pai Asnodkar, A., Wang, J., Eastman, J. D., et al. 2022, AJ, 163, 155 [NASA ADS] [CrossRef] [Google Scholar]
  22. Pepe, F. A., Cristiani, S., Rebolo Lopez, R., et al. 2010, in Ground-based and Airborne Instrumentation for Astronomy III, eds. I. S. McLean, S. K. Ramsay, & H. Takami, SPIE Conf. Ser., 7735, 77350F [NASA ADS] [Google Scholar]
  23. Pepe, F., Cristiani, S., Rebolo, R., et al. 2021, A&A, 645, A96 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  24. Redfield, S., Endl, M., Cochran, W. D., & Koesterke, L. 2008, ApJ, 673, L87 [Google Scholar]
  25. Sánchez-López, A., Landman, R., Mollière, P., et al. 2022, A&A, 661, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Seidel, J. V., Ehrenreich, D., Wyttenbach, A., et al. 2019, A&A, 623, A166 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Seidel, J. V., Ehrenreich, D., Allart, R., et al. 2021, A&A, 653, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Seidel, J. V., Cegla, H. M., Doyle, L., et al. 2022, MNRAS, 513, L15 [NASA ADS] [CrossRef] [Google Scholar]
  29. Smette, A., Sana, H., Noll, S., et al. 2015, A&A, 576, A77 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. Tabernero, H. M., Zapatero Osorio, M. R., Allart, R., et al. 2021, A&A, 646, A158 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  31. Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nat. Methods, 17, 261 [Google Scholar]
  32. West, R. G., Hellier, C., Almenara, J. M., et al. 2016, A&A, 585, A126 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Wyttenbach, A., Ehrenreich, D., Lovis, C., Udry, S., & Pepe, F. 2015, A&A, 577, A62 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Yan, F., & Henning, T. 2018, Nat. Astron., 2, 714 [Google Scholar]
  35. Yan, F., Pallé, E., Fosbury, R. A. E., Petr-Gotzens, M. G., & Henning, T. 2017, A&A, 603, A73 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]

Appendix A: Additional table

Table A.1.

Summary of the Gaussian fit parameters for the detected species in the transits of WASP-76b and WASP-121b.

Appendix B: Parameters

Table B.1.

Stellar and planetary parameters.

Appendix C: Telluric correction. Input parameters and spectrum comparison

Table C.1.

Some of the key input parameters used in Molecfit.

thumbnail Fig. C.1.

Illustration of the Molecfit telluric correction on a single line from the sodium D-line doublet in the observed spectrum of WASP-76b on the night of 2018 October 31 in all exposures. The vertical dashed purple line represents the expected line position. Top left: Sodium line prior to the telluric correction. Top right: Sodium line after the Molecfit telluric correction. Bottom: Ratio of the nontelluric-corrected over telluric-corrected spectral lines. Inset: Flux and air-mass variation over the transit observation. As expected for observations later in the night, with higher airmass, the removed telluric features are stronger.

Appendix D: Wiggles

thumbnail Fig. D.1.

Fitting procedure during the wiggle-correction step for some of the wavelength regions in the first exposure of the 4UT observing night of WASP-121b. The fit of the entire spectral range is shown in the last panel. We divide the spectrum into regions (vertical purple lines) in which we define the priors and bounds of the fitting functions. For some regions near the lowest and highest wavelengths, we did not apply the spline fitting because it would not be a correct match to the observed data.

thumbnail Fig. D.1.

continued.

Appendix E: Lines per species used from the Mantis masks.

Table E.1.

Number of lines per species we used for our CCFs using the Mantis masks at a temperature of 2500 K.

Appendix F: Stellar signal masking

thumbnail Fig. F.1.

Tomography plots in the planetary rest frame built from the WASP-121b CCFs (night 2, 4UTs) of the planetary spectrum with the F9 ESPRESSO mask. Left: Without masking the stellar signal. Right: By masking the stellar velocities ranging from -15 km/s to +15 km/s in the stellar rest frame. The white horizontal band for the early orbital phases originates from the lack of data at the start of transit.

Appendix G: Calcium II and titanium II CCFs

thumbnail Fig. G.1.

Left: CCF of the Ca+ mask with the retrieved planetary spectrum for WASP-121b (night 2, 4UTs) at the planetary rest frame. Center and right: WASP-121b retrieved planetary spectrum at the Ca+ H&K lines.

thumbnail Fig. G.2.

Left: CCF of the Ti+ mask with the retrieved planetary spectrum for WASP-121b (night 2, 4UTs). Center: CCF built from considering the contributions from spectra between -15 km/s and 15 km/s in the stellar frame of reference alone. Right: Same as the initial CCF, but excluding the previous stellar contribution region. All the plots are in the planetary rest frame.

Appendix H: CCF and Kp-plots for WASP-76b and WASP-121b

thumbnail Fig. H.1.

WASP-76b, night 1 (2018 September 3). CCFs of the averaged in-transit exposures in the planetary frame of reference for the detected chemical species, except for the Hα line, which is present directly in the retrieved planetary spectrum.

thumbnail Fig. H.2.

WASP-76b, night 1 (2018 September 3). Kp-plots. Map of the sum of all the individual exposures in the planetary rest frame across different values in the Kp - planetary velocity plane. We mask the signal that matches the stellar velocities ranging from -15 km/s to +15 km/s in the stellar rest frame. The dashed green lines represent the expected position of the planetary signal in this map.

thumbnail Fig. H.3.

Same as Fig. H.1 for WASP-76b, night 2 (2018 October 31).

thumbnail Fig. H.4.

Same as Fig. H.2 for WASP-76b, night 2 (2018 October 31).

thumbnail Fig. H.5.

Same as Fig. H.1 for WASP-121b, night 1 (1UT - 2018 November 30).

thumbnail Fig. H.6.

Same as Fig. H.2 for WASP-121b, night 1 (1UT - 2018 November 30).

thumbnail Fig. H.7.

Same as Fig. H.1 for WASP-121b, night 2 (4UT’s - 2019 January 6).

thumbnail Fig. H.8.

Same as Fig. H.2 for WASP-121b, night 2 (4UT’s - 2019 January 6)

Appendix I: Individual barium II lines

thumbnail Fig. I.1.

Planetary transmission spectrum for the WASP-121b, night 2 (4UTs, 2019 January 6) dataset, centered at the three strongest lines in the barium mask.

All Tables

Table 1.

Summary of the transit observations of WASP-76b and WASP-121b.

In the text
Table A.1.

Summary of the Gaussian fit parameters for the detected species in the transits of WASP-76b and WASP-121b.

In the text
Table B.1.

Stellar and planetary parameters.

In the text
Table C.1.

Some of the key input parameters used in Molecfit.

In the text
Table E.1.

Number of lines per species we used for our CCFs using the Mantis masks at a temperature of 2500 K.

In the text

All Figures

thumbnail Fig. 1.

Cross-correlation of the Ba+ mask with the retrieved planetary spectra for the two observation nights of WASP-76b (top on 2018 September 3, and bottom on 2018 October 31). Left: cross-correlation functions of the averaged in-transit exposures on the planetary frame of reference. Center: Kp-plots. Map of the sum of all the individual exposures in the planet rest frame across different values in the Kp–planet velocity plane. The dashed green lines represent the expected position of the planetary signal on this map. Right: tomographic plots in the planetary rest frame. The white lines represent the transit contacts.
In the text
thumbnail Fig. 2.

Same as Fig. 1, but for the WASP-121b observing nights (top in 1UT mode on 2018 November 30, and bottom in 4UT mode on 2019 January 6).
In the text
thumbnail Fig. C.1.

Illustration of the Molecfit telluric correction on a single line from the sodium D-line doublet in the observed spectrum of WASP-76b on the night of 2018 October 31 in all exposures. The vertical dashed purple line represents the expected line position. Top left: Sodium line prior to the telluric correction. Top right: Sodium line after the Molecfit telluric correction. Bottom: Ratio of the nontelluric-corrected over telluric-corrected spectral lines. Inset: Flux and air-mass variation over the transit observation. As expected for observations later in the night, with higher airmass, the removed telluric features are stronger.
In the text
thumbnail Fig. D.1.

Fitting procedure during the wiggle-correction step for some of the wavelength regions in the first exposure of the 4UT observing night of WASP-121b. The fit of the entire spectral range is shown in the last panel. We divide the spectrum into regions (vertical purple lines) in which we define the priors and bounds of the fitting functions. For some regions near the lowest and highest wavelengths, we did not apply the spline fitting because it would not be a correct match to the observed data.
In the text
thumbnail Fig. D.1.

continued.
In the text
thumbnail Fig. F.1.

Tomography plots in the planetary rest frame built from the WASP-121b CCFs (night 2, 4UTs) of the planetary spectrum with the F9 ESPRESSO mask. Left: Without masking the stellar signal. Right: By masking the stellar velocities ranging from -15 km/s to +15 km/s in the stellar rest frame. The white horizontal band for the early orbital phases originates from the lack of data at the start of transit.
In the text
thumbnail Fig. G.1.

Left: CCF of the Ca+ mask with the retrieved planetary spectrum for WASP-121b (night 2, 4UTs) at the planetary rest frame. Center and right: WASP-121b retrieved planetary spectrum at the Ca+ H&K lines.
In the text
thumbnail Fig. G.2.

Left: CCF of the Ti+ mask with the retrieved planetary spectrum for WASP-121b (night 2, 4UTs). Center: CCF built from considering the contributions from spectra between -15 km/s and 15 km/s in the stellar frame of reference alone. Right: Same as the initial CCF, but excluding the previous stellar contribution region. All the plots are in the planetary rest frame.
In the text
thumbnail Fig. H.1.

WASP-76b, night 1 (2018 September 3). CCFs of the averaged in-transit exposures in the planetary frame of reference for the detected chemical species, except for the Hα line, which is present directly in the retrieved planetary spectrum.
In the text
thumbnail Fig. H.2.

WASP-76b, night 1 (2018 September 3). Kp-plots. Map of the sum of all the individual exposures in the planetary rest frame across different values in the Kp - planetary velocity plane. We mask the signal that matches the stellar velocities ranging from -15 km/s to +15 km/s in the stellar rest frame. The dashed green lines represent the expected position of the planetary signal in this map.
In the text
thumbnail Fig. H.3.

Same as Fig. H.1 for WASP-76b, night 2 (2018 October 31).
In the text
thumbnail Fig. H.4.

Same as Fig. H.2 for WASP-76b, night 2 (2018 October 31).
In the text
thumbnail Fig. H.5.

Same as Fig. H.1 for WASP-121b, night 1 (1UT - 2018 November 30).
In the text
thumbnail Fig. H.6.

Same as Fig. H.2 for WASP-121b, night 1 (1UT - 2018 November 30).
In the text
thumbnail Fig. H.7.

Same as Fig. H.1 for WASP-121b, night 2 (4UT’s - 2019 January 6).
In the text
thumbnail Fig. H.8.

Same as Fig. H.2 for WASP-121b, night 2 (4UT’s - 2019 January 6)
In the text
thumbnail Fig. I.1.

Planetary transmission spectrum for the WASP-121b, night 2 (4UTs, 2019 January 6) dataset, centered at the three strongest lines in the barium mask.
In the text

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