Arnaud Salvador

Spectroscopic characterization of rocky exoplanets with the James Webb Space Telescope has brought the origin and evolution of their atmospheres into the focus of exoplanet science. Time-evolved models of the feedback between interior and atmosphere are critical to predict and interpret these observations and link them to the solar system terrestrial planets. However, models differ in methodologies and input data, which can lead to significant differences in interpretation. In this paper, we present the experimental protocol of the Coupled atmospHere Interior modeL Intercomparison (CHILI) project. CHILI is an (exo)planet model intercomparison project within the Climates Using Interactive Suites of Intercomparisons Nested for Exoplanet Studies (CUISINES) framework, which aims to support a diverse set of multimodel intercomparison projects in the exoplanet community. The present protocol includes the initial set of participating magma ocean models, divided into evolutionary and static models, and two types of test categories, one focused on solar system planets (Earth and Venus) and the other on exoplanets orbiting low-mass M dwarfs. Both test categories aim to quantify the evolution of key markers of the links between planetary atmospheres and interiors over geological timescales. The proposed tests would allow us to quantify and compare the differences between coupled atmosphere–interior models used by the exoplanet and planetary science communities. Results from the proposed tests will be published in dedicated follow-up papers. To encourage the community to join this comparison effort, and as an example, we present initial test results for the early Earth and TRAPPIST-1 b, conducted with models differing in the treatment of energy transport in the planetary interior and atmosphere, surface boundary layer, geochemistry, and in- and outgassing of volatile compounds.

Evolution primitive et habitabilité des planètes rocheuses: Les planètes rocheuses achèvent leur formation dans des processus collisionnels très énergétiques.L'énergie libérée lors des impacts majeurs a vraisemblablement fondu la surface des planètes, formant ainsi un océan de roches en fusion. Le refroidissement et la solidification de cet « océan de magma » conditionnent la différentiation chimique du manteau et la distribution des éléments volatils entre les différents réservoirs de la planète. C'est lors de cette phase évolutive, commune aux planètes rocheuses, que l'atmosphère est formée par dégazage des volatils et que les conditions initiales de l'évolution future des planètes se mettent en place. C'est ainsi une phase évolutive de première importance pour comprendre l'apparition des océans d'eau primitifs, le démarrage de la convection thermique du manteau et l'actuelle diversité des planètes telluriques.Un modèle numérique couplant l'évolution thermique de l'océan de magma en interaction avec l'atmosphère a été utilisé pour étudier le refroidissement de la planète et les conditions de surface résultantes. Nous avons investigué l'influence du contenu initial en volatil combiné avec la distance orbitale de la planète sur la formation des premiers océans d'eau à la fin du refroidissement, pour des atmosphères avec et sans nuages. Cette approche a ensuite été étendue aux planètes rocheuses extra-solaires orbitant des étoiles froides.Le contenu relatif en H2O et CO2 de l'atmosphère peut empêcher la formation d'océans, menant à des planètes ayant une surface solide sans océans d'eau. Des lois d'échelle prédisent la formation d'océans en fonction du contenu initial en volatil. Une épaisse couche nuageuse diminue la température de surface et maintient des conditions clémentes plus proche de l'étoile rendant ainsi possible la formation d'océan sur Vénus. Ces conditions de surface tempérées pourraient alors être favorable à l'émergence de la vie et suggèrent qu'en fonction de la couverture nuageuse, la Terre et Vénus pourraient être dans un état relativement similaire à la fin de la phase océan de magma, contrairement à ce qui est généralement admis.Pour les étoiles froides, la formation d'océans d'eau n'est possible qu'à des flux stellaires plus faibles que dans notre système solaire, correspondant à des distances étoile-planète relativement plus importantes.L'effet refroidissant des nuages est atténué pour les étoiles froides autour desquelles la bordure intérieure de la zone d'habitabilité tend à être indépendante de la couverture nuageuse.

A next generation of space-based observatories aims to detect and characterize potentially Earth-like exoplanets around Sun-like stars using reflected-light spectroscopy. However, it remains unclear how such direct-imaging observations, being limited in spectral coverage and signal-to-noise ratio (S/N), translate into constraints on atmospheric composition and habitability. Coronagraphs used for high-contrast imaging typically operate over narrow bandpasses, and exposure time limits can restrict data quality. To optimize observing strategies and instrument design, we use our atmospheric retrieval tool, rfast , to assess the performance of a Habitable Worlds Observatory–type mission across different spectral bandpasses—red, blue, visible, near-infrared (NIR), and their combination—and S/N levels—10, 15, and 20; from moderate to moderate-high observation quality—in retrieving a wide range of 17 atmospheric, surface, bulk, and orbital parameters of a habitable Earth analog. We outline the observation requirements for each parameter and the detection capabilities of each case within a novel scenario where spectral data are taken “early,” prior to achieving orbit constraints (which may require repeat visits to a system). For coronagraph-restricted and NIR-only bandpasses, most of the limited retrievable information is already captured at S/N = 10, with little improvement at higher S/Ns. For broader spectral coverage, the quality and quantity of retrieved information improve with increasing S/N, but combining visible and NIR ranges provides the most comprehensive characterization, even at moderate S/Ns. To maximize returns, wider spectral coverage should be prioritized over improving S/N when spectral access is limited.

Survey strategies for upcoming exoplanet direct imaging missions have considered varying assumptions of prior knowledge. Precursor radial velocity surveys could have detected nearby exo-Earths and provided prior orbit and mass constraints. Alternatively, a direct imaging mission performing astrometry could yield constraints on the orbit and phase angle of target planets. Understanding the impact of prior mass and orbit information on planetary characterization is crucial for efficiently recognizing habitable exoplanets. To address this question, we use a reflected-light retrieval tool to infer the atmospheric and bulk properties of directly imaged Earth-analogs while considering varying levels of prior information and signal-to-noise ratio (S/N). Because of the strong correlation between the orbit-related parameters and the planetary radius, prior information on the orbital distance and planetary phase angle yield much tighter constraints on the planetary radius: from R p = 2.95 − 1.95 + 2.69 R ⊕ without prior knowledge, to R p = 1.01 − 0.19 + 0.33 R ⊕ with prior determination of the orbit for S/N = 20 in the visible/near-infrared spectral range, thus allowing size determination from reflected light observations. However, additional knowledge of planet mass does not notably enhance radius ( R p = 0.98 − 0.14 + 0.17 R ⊕ ) or atmospheric characterization. Also, prior knowledge of the mass alone does not yield a tight radius constraint ( R p = 1.64 − 0.80 + 1.29 R ⊕ ) nor improves atmospheric composition inference. By contrast, because of its sensitivity to gas column abundance, detecting a Rayleigh scattering slope or bounding Rayleigh opacity helps to refine gas mixing ratio inferences without requiring prior mass knowledge. Overall, apart from radius determination, increasing the S/N is more beneficial than additional prior observations.

Long-term magma ocean phases on rocky exoplanets orbiting closer to their star than the runaway greenhouse threshold—the inner edge of the classical habitable zone—may offer insights into the physical and chemical processes that distinguish potentially habitable worlds from others. The thermal stratification of runaway planets is expected to significantly inflate their atmospheres, potentially providing observational access to the runaway greenhouse transition in the form of a habitable zone inner edge discontinuity in radius–density space. Here, we use Bioverse, a statistical framework combining contextual information from the overall planet population with a survey simulator, to assess the ability of ground- and space-based telescopes to test this hypothesis. We find that the demographic imprint of the runaway greenhouse transition is likely detectable with high-precision transit photometry for sample sizes ≳100 planets if at least ∼10% of those orbiting closer than the habitable zone inner edge harbor runaway climates. Our survey simulations suggest that, in the near future, ESA’s PLATO mission will be the most promising survey to probe the habitable zone inner edge discontinuity. We determine the survey strategies that maximize the diagnostic power of the obtained data and identify as key mission design drivers: (1) a follow-up campaign of planetary mass measurements and (2) the fraction of low-mass stars in the target sample. Observational constraints on the runaway greenhouse transition will provide crucial insights into the distribution of atmospheric volatiles among rocky exoplanets, which may help to identify the nearest potentially habitable worlds.

Background: DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) in metabolomics and lipidomics, for comprehensive profiling of molecules in biological samples. It provides unbiased coverage, improved reproducibility, and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum , successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field. Results: DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to study molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified statistically significant features responsible for group segregation. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra DB annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness. Significance: Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing and EAD synergistically enhances detection sensitivity while providing orthogonal fragmentation information, thereby facilitating a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying biomarkers of significance in the field of environmental assessment. Highlights: Advancements in Data-Independent-Acquisition methods for lipidomics and metabolomics. Zeno pulsing improves sensitivity in fragment detection and compound identification. Comprehensive structure elucidation of lipids and metabolites using EAD fragmentation.

Direct imaging spectroscopy with future space-based telescopes will constrain terrestrial planet atmospheric composition and potentially detect biosignature gases. One promising indication of life is abundant atmospheric O₂. However, various non-biological processes could also lead to O₂ accumulation in the atmospheres of potentially habitable planets around Sun-like stars. In particular, the absence of non-condensible background gases such as N₂ could result in appreciable H escape and abiotic O₂ buildup, so identifying background atmosphere composition is crucial for contextualizing any O₂ detections. Here, we perform retrievals on simulated directly imaged terrestrial planets using rfast, a new exoplanet atmospheric retrieval suite with direct imaging analysis capabilities. By simulating Earth-analog retrievals for varied atmospheric compositions, cloud properties, and surface pressures, we determine what wavelength range, spectral resolution, and signal-to-noise ratio (S/N) are necessary to constrain background gases’ identity and abundance. We find N₂ backgrounds can be uniquely identified with S/N ∼ 20 observations, provided that wavelength coverage extends beyond ∼1.6 μm to rule out CO-dominated atmospheres. Additionally, there is a low probability of O₂-dominated atmospheres due to an O₂–N₂ degeneracy that is only totally ruled out at S/N ∼ 40. If wavelength coverage is limited to 0.2–1.1 μm, then although all other cosmochemically plausible backgrounds can be readily excluded, N₂ and CO backgrounds cannot be distinguished. Overall, our simulated retrievals and associated integration time calculations suggest that near-infrared coverage to at least 1.6 μm and apertures approaching 8 m are needed to confidently rule out O₂ biosignature false positives within feasible integration times.