TRAPPIST-1 in High Resolution: Constraining Exoplanet Atmospheres Amid Systematics
Bibliographic record
Abstract
Introduction & Goals Studying terrestrial planets orbiting M dwarfs is our best opportunity to identify potentially habitable worlds and search for biosignatures beyond our solar system. The TRAPPIST-1 system, hosting seven rocky, Earth-sized, transiting exoplanets, stands out as a promising target, with three planets (e, f, and g) residing in the habitable zone. JWST observations with low spectral resolution have already ruled out cloud-free hydrogen- and helium-rich atmospheres for all the system’s planets. This is expected since XUV radiation from the M8 host would have driven atmospheric escape, leaving the seven planets either airless or with high mean molecular weight atmospheres.So far, no atmosphere has been detected on any of these planets, largely due to the intense stellar activity of TRAPPIST-1. A significant obstacle is the transit light source effect (TLSE), which arises from the often incorrect assumption that the light from the transit chord – the region of the star occulted by the planet as it transits – is representative of the entire stellar disk. This is particularly problematic for late M dwarfs with substantial surface coverage of spots and faculae, which contaminate transit observations by introducing spectral features that mimic atmospheric signals and far exceed the actual planetary signal.This presentation will focus on the use of data from ground-based telescopes equipped with high resolution spectrographs, a novel approach to characterize the atmospheres of rocky exoplanets. My objectives are:Detect an atmosphere on TRAPPIST-1 b and e, specifically measure the abundance of water and methane, or place upper limits on these quantities; Investigate the impact of stellar activity on high resolution spectroscopic observations of transiting exoplanets, which remains poorly understood. Methods We use archival high resolution observations from the SPIRou spectrograph on the Canada-France-Hawaii Telescope to constrain the atmospheric composition of TRAPPIST-1 b and e. SPIRou operates in the infrared, which is ideal for detecting greenhouse gases in exoplanetary atmospheres, and it provides the precision needed to resolve individual absorption lines. However, this instrument is affected by persistence, a residual signal from the guide star that contaminates the first few exposures of the science observations with its spectral features, introducing spurious signals in the data that can be mistaken for a planetary atmosphere.We analyze 11 transits of TRAPPIST-1 b and 2 of TRAPPIST-1 e using the open-source pipeline Spectral Transmission And Radiation Search for High resolutIon Planet Signal (STARSHIPS)1. This wealth of data offers a unique opportunity to push the limits of atmospheric detection from the ground. After correcting for persistence and other systematics, we cross-correlate the observations with atmospheric models generated with petitRADTRANS2. To assess detection sensitivity, we inject synthetic atmospheric signals into the raw data and measure the strength of the signal recovered by the pipeline. We then perform Bayesian retrievals to extract constraints on atmospheric parameters. By comparing the results obtained with and without persistence correction, we demonstrate the importance of identifying and mitigating these systematics (see Figure 1). In parallel, we examine out-of-transit spectra to assess the impact of stellar contamination on high resolution spectroscopy. Figure 1: Result of a preliminary cross-correlation between an atmospheric model of TRAPPIST-1 b and two different nights of observation. In (a), a spurious signal (yellow) appears at the intersection of the dotted lines, suggesting a detection. In contrast, (b) shows no such signal at the intersection, indicating that the observation from night (a) was affected by persistence. This underscores the necessity, in high resolution transmission spectroscopy of terrestrial exoplanets, to observe multiple transits to identify nights compromised by systematics and to correct for these effects before claiming a detection. Expected Results I intend to present strong upper limits on the abundances of H2O and CH4, markers of habitability, in the atmospheres of TRAPPIST-1 b and e. I aim to provide the first detailed characterization of the imprint of both stellar activity and persistence in high resolution transit observations. Finally, I will showcase STARSHIPS as an accessible tool for analyzing high resolution spectroscopic observations, from hot Jupiters to Earth-like exoplanets. While the analysis is still ongoing, final results are expected in time for the conference.Impact These new constraints will help the exoplanet community eliminate specific atmospheric scenarios for the TRAPPIST-1 planets, providing essential context to interpret the results from ongoing JWST programs, which currently struggle to distinguish between bare rocks and thick, high mean molecular weight atmospheres. Leveraging an extensive dataset, our results contribute to understanding the lower limits of detectable atmospheres with the current set of ground-based telescopes. As such, they will inform the design of future observing programs of rocky planets around M dwarfs with ground-based facilities like the Extremely Large Telescope. More broadly, this work advances the search for habitable worlds by facilitating the atmospheric characterization of all exoplanets whose spectra may be affected by stellar contamination. 1 https://github.com/boucherastro/starships2 https://petitradtrans.readthedocs.io
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".