arXiv subjects

Quentin Changeat

Publications and source records attributed to Quentin Changeat.

At least 55 records · Page 3Linked to original sources

arXiv2022

Early Release Science of the exoplanet WASP-39b with JWST NIRISS

Transmission spectroscopy provides insight into the atmospheric properties and consequently the formation history, physics, and chemistry of transiting exoplanets. However, obtaining precise inferences of atmospheric properties from transmission spectra requires simultaneously measuring the strength and shape of multiple spectral absorption features from a wide range of chemical species. This has been challenging given the precision and wavelength coverage of previous observatories. Here, we present the transmission spectrum of the Saturn-mass exoplanet WASP-39b obtained using the SOSS mode of the NIRISS instrument on the JWST. This spectrum spans $0.6 - 2.8 μ$m in wavelength and reveals multiple water absorption bands, the potassium resonance doublet, as well as signatures of clouds. The precision and broad wavelength coverage of NIRISS-SOSS allows us to break model degeneracies between cloud properties and the atmospheric composition of WASP-39b, favoring a heavy element enhancement ("metallicity") of $\sim 10 - 30 \times$ the solar value, a sub-solar carbon-to-oxygen (C/O) ratio, and a solar-to-super-solar potassium-to-oxygen (K/O) ratio. The observations are best explained by wavelength-dependent, non-gray clouds with inhomogeneous coverage of the planet's terminator.

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arXiv2022

Exploring the Ability of HST WFC3 G141 to Uncover Trends in Populations of Exoplanet Atmospheres Through a Homogeneous Transmission Survey of 70 Gaseous Planets

We present the analysis of the atmospheres of 70 gaseous extrasolar planets via transit spectroscopy with Hubble's Wide Field Camera 3 (WFC3). For over half of these, we statistically detect spectral modulation which our retrievals attribute to molecular species. Among these, we use Bayesian Hierarchical Modelling to search for chemical trends with bulk parameters. We use the extracted water abundance to infer the atmospheric metallicity and compare it to the planet's mass. We also run chemical equilibrium retrievals, fitting for the atmospheric metallicity directly. However, although previous studies have found evidence of a mass-metallicity trend, we find no such relation within our data. For the hotter planets within our sample, we find evidence for thermal dissociation of dihydrogen and water via the H$^-$ opacity. We suggest that the general lack of trends seen across this population study could be due to i) the insufficient spectral coverage offered by HST WFC3 G141, ii) the lack of a simple trend across the whole population, iii) the essentially random nature of the target selection for this study or iv) a combination of all the above. We set out how we can learn from this vast dataset going forward in an attempt to ensure comparative planetology can be undertaken in the future with facilities such as JWST, Twinkle and Ariel. We conclude that a wider simultaneous spectral coverage is required as well as a more structured approach to target selection.

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arXiv2022

Is binning always sinning? The impact of time-averaging for exoplanet phase curves

We explore how finite integration time or temporal binning can affect the analysis of exoplanet phase-curves. We provide analytical formulae to account for this effect or, if neglected, to estimate the potential biases in the retrieved parameters. As expected, due to their smoother variations over longer time-scales, phase curves can be binned more heavily than transits without causing severe biases. In the simplest case of a sinusoidal phase curve with period $P$, the integration time $Δt$ reduces its amplitude by the scaling factor $\text{sinc}{ \left ( πΔt / P \right ) }$, without altering its phase or shape. We also provide formulae to predict reasonable parameter error bars from phase-curve observations. Our findings are tested with both synthetic and real datasets, including unmodelled astrophysical signals and/or instrumental systematic effects. Tests with the Spitzer data show that binning can affect the best-fitting parameters beyond predictions, due to the correction of high-frequency correlated noise. Finally, we summarize key guidelines for speeding up the analysis of exoplanet phase curves without introducing significant biases in the retrieved parameters.

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arXiv2022

Identification of carbon dioxide in an exoplanet atmosphere

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (i.e., elements heavier than helium, also called "metallicity"), and thus formation processes of the primary atmospheres of hot gas giants. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2 but have not yielded definitive detections due to the lack of unambiguous spectroscopic identification. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science Program (ERS). The data used in this study span 3.0 to 5.5 μm in wavelength and show a prominent CO2 absorption feature at 4.3 μm (26σ significance). The overall spectrum is well matched by one-dimensional, 10x solar metallicity models that assume radiative-convective-thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide, and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 μm that is not reproduced by these models.

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arXiv2022

ESA-Ariel Data Challenge NeurIPS 2022: Inferring Physical Properties of Exoplanets From Next-Generation Telescopes

The study of extra-solar planets, or simply, exoplanets, planets outside our own Solar System, is fundamentally a grand quest to understand our place in the Universe. Discoveries in the last two decades have re-defined our understanding of planets, and helped us comprehend the uniqueness of our very own Earth. In recent years the focus has shifted from planet detection to planet characterisation, where key planetary properties are inferred from telescope observations using Monte Carlo-based methods. However, the efficiency of sampling-based methodologies is put under strain by the high-resolution observational data from next generation telescopes, such as the James Webb Space Telescope and the Ariel Space Mission. We are delighted to announce the acceptance of the Ariel ML Data Challenge 2022 as part of the NeurIPS competition track. The goal of this challenge is to identify a reliable and scalable method to perform planetary characterisation. Depending on the chosen track, participants are tasked to provide either quartile estimates or the approximate distribution of key planetary properties. To this end, a synthetic spectroscopic dataset has been generated from the official simulators for the ESA Ariel Space Mission. The aims of the competition are three-fold. 1) To offer a challenging application for comparing and advancing conditional density estimation methods. 2) To provide a valuable contribution towards reliable and efficient analysis of spectroscopic data, enabling astronomers to build a better picture of planetary demographics, and 3) To promote the interaction between ML and exoplanetary science. The competition is open from 15th June and will run until early October, participants of all skill levels are more than welcomed!

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arXiv2022

Five key exoplanet questions answered via the analysis of 25 hot Jupiter atmospheres in eclipse

Population studies of exoplanets are key to unlocking their statistical properties. So far the inferred properties have been mostly limited to planetary, orbital and stellar parameters extracted from, e.g., Kepler, radial velocity, and GAIA data. More recently an increasing number of exoplanet atmospheres have been observed in detail from space and the ground. Generally, however, these atmospheric studies have focused on individual planets, with the exception of a couple of works which have detected the presence of water vapor and clouds in populations of gaseous planets via transmission spectroscopy. Here, using a suite of retrieval tools, we analyse spectroscopic and photometric data of 25 hot Jupiters, obtained with the Hubble and Spitzer Space Telescopes via the eclipse technique. By applying the tools uniformly across the entire set of 25 planets, we extract robust trends in the thermal structure and chemical properties of hot Jupiters not obtained in past studies. With the recent launch of JWST and the upcoming missions Twinkle, and Ariel, population based studies of exoplanet atmospheres, such as the one presented here, will be a key approach to understanding planet characteristics, formation, and evolution in our galaxy.

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arXiv2022

The transmission spectrum of WASP-17 b from the optical to the near-infrared wavelengths: combining STIS, WFC3 and IRAC datasets

We present the transmission spectrum of the inflated hot-Jupiter WASP-17 b, observed with the STIS and WFC3 instruments aboard the Hubble Space Telescope, allowing for a continuous wavelength coverage from ~0.4 to ~1.7 um. Observations taken with IRAC channel 1 and 2 on the Spitzer Space Telescope are also included, adding photometric measurements at 3.6 and 4.5 um. HST spectral data was analysed with Iraclis, a pipeline specialised in the reduction of STIS and WFC3 transit and eclipse observations. Spitzer photometric observations were reduced with the TLCD-LSTM method, utilising recurrent neural networks. The outcome of our reduction produces incompatible results between STIS visit 1 and visit 2, which leads us to consider two scenarios for G430L. Additionally, by modelling the WFC3 data alone, we can extract atmospheric information without having to deal with the contrasting STIS datasets. We run separate retrievals on the three spectral scenarios with the aid of TauREx 3, a fully Bayesian retrieval framework. We find that, independently of the data considered, the exoplanet atmosphere displays strong water signatures and potentially, the presence of aluminium oxide (AlO) and titanium hydride (TiH). A retrieval that includes an extreme photospheric activity of the host star is the preferred model, but we recognise that such a scenario is unlikely for an F6-type star. Due to the incompleteness of all STIS spectral lightcurves, only further observations with this instrument would allow us to properly constrain the atmospheric limb of WASP-17 b, before JWST or Ariel will come online.

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arXiv2022

A retrieval challenge exercise for the Ariel mission

The Ariel mission, due to launch in 2029, will obtain spectroscopic information for 1000 exoplanets, providing an unprecedented opportunity for comparative exoplanetology. Retrieval codes - parameteric atmospheric models coupled with an inversion algorithm - represent the tool of choice for interpreting Ariel data. Ensuring that reliable and consistent results can be produced by these tools is a critical preparatory step for the mission. Here, we present the results of a retrieval challenge. We use five different exoplanet retrieval codes to analyse the same synthetic datasets, and test a) the ability of each to recover the correct input solution and b) the consistency of the results. We find that generally there is very good agreement between the five codes, and in the majority of cases the correct solutions are recovered. This demonstrates the reproducibility of retrievals for transit spectra of exoplanets, even when codes are not previously benchmarked against each other.

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arXiv2022

Cross-sections for heavy atmospheres: H$_2$O continuum

Most of the exoplanets detected up to now transit in front of their host stars, allowing for the generation of transmission spectra; the study of exoplanet atmospheres relies heavily upon accurate analysis of these spectra. Recent discoveries mean that the study of atmospheric signals from low-mass, temperate worlds are becoming increasingly common. The observed transit depth in these planets is small and more difficult to analyze. Analysis of simulated transmission spectra for two small, temperate planets (GJ 1214 b and K2-18 b) is presented, giving evidence for significant differences in simulated transit depth when the water vapor continuum is accounted for when compared to models omitting it. These models use cross-sections from the CAVIAR lab experiment for the water self-continuum up to 10,000 cm$^{-1}$; these cross-sections exhibit an inverse relationship with temperature, hence lower-temperature atmospheres are the most significantly impacted. Including the water continuum strongly affects transit depths, increasing values by up to 80 ppm, with the differences for both planets being detectable with the future space missions Ariel and JWST. It is imperative that models of exoplanet spectra move toward adaptive cross-sections, increasingly optimized for H$_2$O-rich atmospheres. This necessitates including absorption contribution from the water vapor continuum into atmospheric simulations.

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arXiv2022

Cross-sections for heavy atmospheres: H$_2$O self-broadening

The discovery of super-Earth and mini-Neptune exoplanets means that atmospheric signals from low-mass, temperate exoplanets are being increasingly studied. The signal acquired as the planet transits its host star, known as the transit depth, is smaller for these planets and, as such, more difficult to analyze. The launch of the space telescopes James Webb (JWST) & Ariel will give rise to an explosion in the quality and quantity of spectroscopic data available for an unprecedented number of exoplanets in our galaxy. Accurately extracting the information content, thereby permitting atmospheric science, of such data-sets will require robust models and techniques. We present here the analysis of simulated transmission spectra for water-rich atmospheres, giving evidence for non-negligible differences in simulated transit depths when self-broadening of H$_2$O is correctly accounted for, compared with the currently typically accepted standard of using H$_2$ and He-broadened cross-sections. Our case-study analysis is carried out on two super-Earths, focusing on water-based atmospheres, ranging from H$_2$-rich to H$_2$O-rich. The transit depth is considerably affected, increasing values by up to 60 ppm, which is shown to be detectable with JWST and Ariel. The differences are most pronounced for the lighter (i.e. $mu$ $\sim$ 4) atmospheres. Our work illustrates that it is imperative that the field of exoplanet spectroscopy moves toward adapted cross-sections, increasingly optimized for high-mu atmospheres for studies of super-Earths and mini-Neptunes.

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arXiv2021

Tracing the formation history of giant planets in protoplanetary disks with Carbon, Oxygen, Nitrogen and Sulphur

The composition of giant planets is imprinted by their migration history and the compositional structure of their hosting disks. Studies in recent literature investigate how the abundances of C and O can constrain the formation pathways of giant planets forming within few tens of au from the star. New ALMA observations, however, suggest planet-forming regions possibly extending to hundreds of au. We explore the implications of these wider formation environments through n-body simulations of growing and migrating giant planets embedded in planetesimal disks, coupled with a compositional model of the protoplanetary disk where volatiles are inherited from the molecular cloud and refractories are calibrated against extrasolar and Solar System data. We find that the C/O ratio provides limited insight on the formation pathways of giant planets that undergo large-scale migration. This limitation can be overcome thanks to nitrogen and sulphur. Jointly using the C/N, N/O and C/O ratios breaks any degeneracy in the formation and migration tracks of giant planets. The use of elemental ratios normalized to the respective stellar ratios supplies additional information on the nature of giant planets, thanks to the relative volatility of O, C and N in disks. When the planetary metallicity is dominated by the accretion of solids C/N* $>$ C/O* $>$ N/O* (* denoting this normalized scale), otherwise N/O* $>$ C/O* $>$ C/N*. The S/N ratio provides an additional independent probe into the metallicity of giant planets and their accretion of solids.

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arXiv2021

On spectroscopic phase-curve retrievals: H2 dissociation and thermal inversion in the atmosphere of the ultra-hot Jupiter WASP-103 b

This work presents a re-analysis of the spectroscopic phase-curve observations of the ultra hot Jupiter WASP-103 b obtained by the Hubble Space Telescope (HST) and the Spitzer Telescope. Traditional 1D and unified 1.5D spectral retrieval techniques are employed, allowing to map the thermal structure and the abundances of trace gases in this planet as a function of longitude. On the day-side, the atmosphere is found to have a strong thermal inversion, with indications of thermal dissociation traced by continuum H- opacity. Water vapor is found across the entire atmosphere but with depleted abundances of around 1e-5, consistent with the thermal dissociation of this molecule. Regarding metal oxide and hydrides, FeH is detected on the hot-spot and the day-side of WASP-103 b, but TiO and VO are not present in detectable quantities. Carbon-bearing species such as CO and CH4 are also found, but since their detection is reliant on the combination of HST and Spizer, the retrieved abundances should be interpreted with caution. Free and Equilibrium chemistry retrievals are overall consistent, allowing to recover robust constraints on the metallicity and C/O ratio for this planet. The analyzed phase-curve data indicates that the atmosphere of WASP-103 b is consistent with solar elemental ratios.

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arXiv2021

Alfnoor: assessing the information content of Ariel's low resolution spectra with planetary population studies

The ARIEL Space Telescope will provide a large and diverse sample of exoplanet spectra, performing spectroscopic observations of about 1000 exoplanets in the wavelength range $0.5 \to 7.8 \; μm$. In this paper, we investigate the information content of ARIEL's Reconnaissance Survey low resolution transmission spectra. Among the goals of the ARIEL Reconnaissance Survey is also to identify planets without molecular features in their atmosphere. In this work, (1) we present a strategy that will allow to select candidate planets to be reobserved in a ARIEL's higher resolution Tier; (2) we propose a metric to preliminary classify exoplanets by their atmospheric composition without performing an atmospheric retrieval; (3) we introduce the possibility to find other methods to better exploit the data scientific content.

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arXiv2021

Disentangling Atmospheric Compositions of K2-18 b with Next Generation Facilities

Recent analysis of the planet K2-18b has shown the presence of water vapour in its atmosphere. While the H2O detection is significant, the Hubble Space Telescope (HST) WFC3 spectrum suggests three possible solutions of very different nature which can equally match the data. The three solutions are a primary cloudy atmosphere with traces of water vapour (cloudy sub-Neptune), a secondary atmosphere with a substantial amount (up to 50% Volume Mixing Ratio) of H2O (icy/water world) and/or an undetectable gas such as N2 (super-Earth). Additionally, the atmospheric pressure and the possible presence of a liquid/solid surface cannot be investigated with currently available observations. In this paper we used the best fit parameters from Tsiaras et al. (2019) to build James Webb Space Telescope (JWST) and Ariel simulations of the three scenarios. We have investigated 18 retrieval cases, which encompass the three scenarios and different observational strategies with the two observatories. Retrieval results show that twenty combined transits should be enough for the Ariel mission to disentangle the three scenarios, while JWST would require only two transits if combining NIRISS and NIRSpec data. This makes K2-18b an ideal target for atmospheric follow-ups by both facilities and highlights the capabilities of the next generation of space-based infrared observatories to provide a complete picture of low mass planets.

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arXiv2021

TauREx III: A fast, dynamic and extendable framework for retrievals

TauREx 3 is the next generation of the TauREx exoplanet atmospheric retrieval framework for Windows, Mac, and Linux. It is a complete rewrite with a full Python stack that makes it easy-to-use, high-performance, dynamic, and flexible. The new main TauREx program is built with modularity in mind, allowing the user to augment its functionalities with custom code and efficiently perform retrievals on custom parameters. We achieve this result by dynamic determination of fitting parameters, whereby TauREx 3 can detect new parameters for retrieval from user code through a simple interface. TauREx 3 can act as a library with a simple 'import taurex' command, providing a rich set of classes and functions related to atmospheric modelling. A 10x speedup in forward model computations is achieved as compared to the previous version with a sixfold reduction in retrieval times while maintaining robust results. TauREx 3 is intended as a standalone, all-in-one package for retrievals while the TauREx 3 Python library can build or augment a user's custom data pipeline easily.

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arXiv2021

Peeking inside the Black Box: Interpreting Deep Learning Models for Exoplanet Atmospheric Retrievals

Deep learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly non-linear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being 'black boxes'. It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us - among other things - of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that for different molecules, the wavelength ranges to which the DNN's predictions are most sensitive, indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions.

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arXiv2021

An exploration of model degeneracies with a unified phase curve retrieval analysis: The light and dark sides of WASP-43 b

The analysis of exoplanetary atmospheres often relies upon the observation of transit or eclipse events. While very powerful, these snapshots provide mainly 1-dimensional information on the planet structure and do not easily allow precise latitude-longitude characterisations. The phase curve technique, which consists of measuring the planet emission throughout its entire orbit, can break this limitation and provide useful 2-dimensional thermal and chemical constraints on the atmosphere. As of today however, computing performances have limited our ability to perform unified retrieval studies on the full set of observed spectra from phase curve observations at the same time. Here, we present a new phase curve model that enables fast, unified retrieval capabilities. We apply our technique to the combined phase curve data from the Hubble and Spitzer space telescopes of the hot-Jupiter WASP-43 b. We tested different scenarios and discussed the dependence of our solution to different assumptions in the model. Our more comprehensive approach suggests that multiple interpretation of this dataset are possible but our more complex model is consistent with the presence of thermal inversions and a metal rich atmosphere, contrasting with previous data analyses, although this likely depends on the Spitzer data reduction. The detailed constraints extracted here demonstrate the importance of developing and understanding advanced phase curve techniques, which we believe will unlock access to a richer picture of exoplanet atmospheres.

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arXiv2021

ARES V: No Evidence For Molecular Absorption in the HST WFC3 Spectrum of GJ 1132 b

We present a study on the spatially scanned spectroscopic observations of the transit of GJ 1132 b, a warm ($\sim$500 K) Super-Earth (1.13 R$_\oplus$) that was obtained with the G141 grism (1.125 - 1.650 $μ$m) of the Wide Field Camera 3 (WFC3) onboard the Hubble Space Telescope. We used the publicly available Iraclis pipeline to extract the planetary transmission spectra from the five visits and produce a precise transmission spectrum. We analysed the spectrum using the TauREx3 atmospheric retrieval code with which we show that the measurements do not contain molecular signatures in the investigated wavelength range and are best-fit with a flat-line model. Our results suggest that the planet does not have a clear primordial, hydrogen-dominated atmosphere. Instead, GJ 1132 b could have a cloudy hydrogen-dominated envelope, a very enriched secondary atmosphere, be airless, or have a tenuous atmosphere that has not been detected. Due to the narrow wavelength coverage of WFC3, these scenarios cannot be distinguished yet but the James Webb Space Telescope may be capable of detecting atmospheric features, although several observations may be required to provide useful constraints.

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