Brett M. Morris

Stellar activity complicates exoplanet transmission spectra, particularly for smaller planets around M dwarfs with JWST. The transit-light-source (TLS) effect, the imprinting of spectral differences between the average stellar disk and the occulted transit chord onto the transmission spectrum, makes it challenging to directly use the out-of-transit spectrum to correct for stellar contamination. Theory and observations suggest that spots may concentrate toward higher latitudes when the Coriolis force is substantial relative to buoyancy, leaving the equatorial region relatively quiet. Here, we evaluate how the latitudinal distribution of active regions shapes the strength of the TLS effect for planets spanning a range of impact parameters ( b ), using TRAPPIST-1 as a testbed. We first construct a fiducial model to illustrate two distribution regimes. With our model, the moderate- b outer TRAPPIST-1 planets (f, g, h) occult a more typical region of the stellar disk than the inner planets and are thereby less affected by the TLS effect, though their bias may vary more from visit to visit as these active regions evolve with time. More generally, our results imply an impact parameter “sweet spot” for atmospheric characterization, independent of the sign of the active-region temperature contrast, whose location depends on the distribution of active regions. The distribution may be revealed by transit residuals as multiple planets probe different latitudes, while longitudes are sampled in time, such that the variance and frequency of the correlated scatter could constrain active-region filling factors, sizes, and separations.

We investigate the geometric albedos of hot Jupiters by comparing observational data from space telescopes TESS, Kepler, CoRoT, and CHEOPS against theoretical models. The study aims to understand the distribution of observed geometric albedos across different bandpasses and how these observations align with or deviate from model predictions. We curated a comprehensive sample of observed geometric albedos, using either existing Spitzer secondary eclipse measurements or a scaling law between the equilibrium and dayside temperature to remove any contaminating thermal planetary emission. We then utilised hierarchical Bayesian modelling to identify trends with planetary properties such as equilibrium temperature, gravity, and stellar metallicity. On a population level, we found no statistical difference in the distributions of geometric albedos measured by TESS compared to those measured by Kepler, CoRoT, and CHEOPS. We confront the geometric albedo sample with a simple but first-principles model that includes Rayleigh scattering by molecular hydrogen and absorption by sodium, water, titanium oxide, and vanadium oxide. We find that the abundance of sodium and water are the key absorbers that influence the geometric albedos of hot Jupiters, whilst the addition of titanium oxide and vanadium oxide (in the absence of condensation) results in vanishing geometric albedos that are inconsistent with the observed distributions.

Stellar photospheric heterogeneity is a dominant astrophysical systematic impacting exoplanet transmission spectroscopy. NASA’s Pandora SmallSat Mission is designed to address this challenge through contemporaneous visible-band photometry and near-infrared spectroscopy of exoplanet host stars. Here, we present an end-to-end simulation study quantifying Pandora’s ability to infer stellar photospheric properties and correct stellar contamination using out-of-transit observations. We construct eight representative stellar activity scenarios and generate 160 simulated Pandora datasets, incorporating time-dependent stellar spectra, instrument response, and noise. Given accurate models, Bayesian retrievals of joint visible photometry (0.4–0.7 μ m) and near-infrared spectroscopy (0.9–1.6 μ m, R ≈ 120) recover photospheric temperatures with typical uncertainties of ≈30 K, with no significant bias. Models with two spectral components (i.e., a quiescent photosphere and spots) are strongly favored in 95% of cases; one-component models are preferred when true spot filling factors fall below a detection threshold of ≈0.3%. We propagate the true and inferred stellar parameters to compute true, inferred, and residual contamination signals under physically motivated spot geometries. For simple spot distributions, contamination signals of 10 ² –10 ³ ppm are reduced to ≲10 ppm—well below Pandora’s expected transmission spectroscopy precision (30–100 ppm). For more complex spot distributions, geometric degeneracies limit deterministic corrections, leaving residual contamination at the 10 ³ ppm level that must be mitigated using additional constraints, such as spot-crossing events and joint stellar–planetary retrievals of transmission spectra. These results define regimes in which stellar contamination can be corrected from stellar observations alone and show how Pandora stellar observations can identify cases where additional information is required.

Pandora is a SmallSat mission dedicated to understanding exoplanets and their host stars by disentangling the impact of stellar heterogeneity on exoplanet transmission spectra. Selected as a NASA Astrophysics Pioneers mission in 2021, Pandora will provide simultaneous long-term visible photometric monitoring (0.4–0.7 μ m) and low-resolution near-infrared (NIR) spectroscopy (0.9–1.6 μ m) of transiting systems for the purposes of monitoring host star variability and characterizing exoplanetary atmospheres. Pandora’s year-long prime mission from 2026 to 2027 coincides with the middle of a decade defined by targeted efforts for atmospheric characterization of exoplanets, offering a key opportunity to leverage this new resource to maximize science with JWST and other observatories. Here we investigate Pandora’s anticipated performance for the general exoplanet population accessible to transit spectroscopy, from hot Jupiters to temperate sub-Neptunes. By modeling the atmospheres of five test cases broadly consistent with the bulk properties of HD 209458b, HD 189733b, WASP-80 b, HAT-P-18 b, and K2-18 b, we find that Pandora may provide abundance constraints as precise as ∼1.0 dex for main atmospheric absorbers such as H ₂ O and CH ₄ . Then, we explore the synergies between Pandora and JWST. Our results suggest that targets with JWST data in the NIR can benefit from the addition of Pandora observations and result in more reliable abundance estimates than with JWST data alone. Moreover, Pandora can serve the community by providing precursory observations of targets of interest for JWST atmospheric characterization. We conclude by outlining strategies for the use of Pandora as a standalone observatory and in synergy with JWST.

One of the forefront goals in the field of exoplanets is the detection of an atmosphere on a temperate terrestrial exoplanet, and among the best suited systems to do so is TRAPPIST-1. However, JWST transit observations of the TRAPPIST-1 planets show significant contamination from stellar surface features that we are unable to confidently model. Here, we present the motivation and first observations of our JWST multicycle program of TRAPPIST-1 e, which utilize close transits of the airless TRAPPIST-1 b to model-independently correct for stellar contamination, with the goal of determining whether TRAPPIST-1 e has an Earth-like mean molecular weight atmosphere containing CO ₂ . We present our simulations, which show that with 15 close transit observations, we will be able to detect this atmosphere on TRAPPIST-1 e at Δ ln Z = 5 or greater confidence assuming we are able to correct for stellar contamination using the close transit observations. We also show the first three observations of our program. We find that our ability to correct for stellar contamination can be inhibited when strong stellar flares are present, as flares can break the assumption that the star does not change meaningfully between planetary transits. The cleanest observation demonstrates the removal of stellar contamination contribution through an increased preference for a flat line over the original TRAPPIST-1 e spectrum, but highlights how minor data analysis assumptions can propagate significantly when searching for small atmospheric signals. This is amplified when using the signals from multiple planets, which is important to consider as we continue our atmospheric search.

It is an open question whether small planets around M dwarfs are able to maintain atmospheres. The Hot Rocks Survey aims to address this question by observing nine rocky exoplanets orbiting M dwarfs with MIRI emission photometry to constrain the onset of atmospheres. In this paper, we present two MIRI F1500W (15 μm) eclipses of LTT 3780 b, an ultrashort-period super-Earth (P = 0.768 days, R = 1.325 R _⊕, M = 2.46 M _⊕) that receives 111× Earth’s instellation, the highest in the survey. We find a combined eclipse depth of 312 ± 38 ppm, which is consistent between different data reduction and analysis assumptions, bolstering our confidence in the eclipse detection. This eclipse depth is consistent with the thermal emission from a bare rock surface, with a dayside temperature of T day = 114 3 − 99 + 104 K, 98% ± 9% of the maximum temperature predicted for a zero-albedo, zero heat redistribution blackbody. We are able to confidently rule out CO₂-based atmospheres down to a 0.01 bar surface pressure to greater than 3σ (ruling out an approximately Mars-like atmosphere). We are unable to rule out a pure H₂O 1 bar atmosphere, though we argue that this composition is unlikely on such a highly irradiated planet, nor O₂ atmospheres due to the lack of features in the bandpass, though we can put constraints on CO₂-mixture atmospheres. As a potential bare rock, we consider a variety of surface composition models, but are unable to distinguish between them. However, LTT 3780 b is an excellent target for follow-up JWST observations to determine its surface composition and rule out additional atmospheric compositions.

TRAPPIST-1 e is one of the very few rocky exoplanets that is both amenable to atmospheric characterization and resides in the habitable zone of its star—located at a distance from its star such that it might, with the right atmosphere, sustain liquid water on its surface. Here, we present a set of four JWST/NIRSpec PRISM transmission spectra of TRAPPIST-1 e obtained in mid-to-late 2023. Our transmission spectra exhibit similar levels of stellar contamination as observed in prior works for other planets in the TRAPPIST-1 system but over a wider wavelength range, showcasing the challenge of characterizing the TRAPPIST-1 planets even at relatively long wavelengths (3–5 μm). While we show that current stellar modeling frameworks are unable to explain the stellar contamination features in our spectra, we demonstrate that we can marginalize over those features instead using Gaussian processes, which enables us to perform novel exoplanet atmospheric inferences with our transmission spectra. In particular, we are able to rule out cloudy, primary H₂-dominated (≳80% by volume) atmospheres at better than a 3σ level. Constraints on possible secondary atmospheres on TRAPPIST-1 e are presented in a companion paper. Our work showcases how JWST is breaking ground in the precision needed to constrain the atmospheric composition of habitable-zone rocky exoplanets.

TRAPPIST-1 e is one of the very few rocky exoplanets that is both amenable to atmospheric characterization and that resides in the habitable zone of its star -- located at a distance from its star such that it might, with the right atmosphere, sustain liquid water on its surface. Here, we present a set of 4 JWST/NIRSpec PRISM transmission spectra of TRAPPIST-1 e obtained from mid to late 2023. Our transmission spectra exhibit similar levels of stellar contamination as observed in prior works for other planets in the TRAPPIST-1 system (Lim et al, 2023; Radica et al., 2024), but over a wider wavelength range, showcasing the challenge of characterizing the TRAPPIST-1 planets even at relatively long wavelengths (3-5 um). While we show that current stellar modeling frameworks are unable to explain the stellar contamination features in our spectra, we demonstrate that we can marginalize over those features instead using Gaussian Processes, which enables us to perform novel exoplanet atmospheric inferences with our transmission spectra. In particular, we are able to rule out cloudy, primary H$_2$-dominated ($\gtrsim$ 80$\%$ by volume) atmospheres at better than a 3$σ$ level. Constraints on possible secondary atmospheres on TRAPPIST-1 e are presented in a companion paper (Glidden et al., 2025). Our work showcases how JWST is breaking ground into the precisions needed to constrain the atmospheric composition of habitable-zone rocky exoplanets.

We present initial results from a planned 10 yr survey of Ca II H and K emission, using observations made with the Astrophysical Research Consortium 3.5 m Telescope at Apache Point Observatory. The primary goal of the survey is to investigate activity cycles in low-mass stars. The sample includes stars chosen from the legacy Mount Wilson Observatory (MWO) survey carried out by Olin Wilson more than 50 yr ago, together with newly identified planet-hosting stars and a select sample of early to mid M dwarfs. This paper presents the first 4 yr of data, comprising 1040 observations of 271 stars, with a specific focus on K and M stars. We identify a subsample of 153 stars for continuing observations over the full 10 yr survey. Early results indicate that our data are consistent with the MWO cycle periods over a time span of more than 50 yr; that there is a bifurcation in activity in the late K range with separate populations of low- and high-activity stars at lower masses; and that M dwarf planet hosts tend to be mainly found in the population of low-activity stars, even in the unbiased (by activity) TESS sample, potentially indicating a link between activity and planet formation. We have also found indications of possible cyclic variability in some of the lower-mass stars in the sample. Our ultimate goal is to link the activity cycle and rotation periods in a robust sample of stars spanning the FGKM spectral types and to investigate the implications for the underlying magnetic dynamo.

We present StarryStarryProcess, a novel hierarchical Bayesian framework for mapping stellar surfaces using exoplanet transit light curves. While previous methods relied solely on stellar rotational light curves—which contain limited information about spot properties—our approach leverages planetary transits as probes of stellar surfaces. When a planet crosses a spot during transit, it creates a distinctive change in the light curve that directly reveals spot properties. Our model integrates planetary transit modeling with stellar variability analysis by combining the spherical harmonic surface map representation from starry, the probabilistic approach to spot properties of StarryProcess, and a comprehensive transit model that accounts for spot-crossing events during transits. We demonstrate through synthetic data experiments that our model successfully recovers spot distributions, stellar orientation, and spot physical properties. We extend the framework to handle evolving stellar surfaces through time-dependent modeling. Applying our method to TESS observations of TOI-3884, we find evidence for high-latitude spot concentrations and significant spin–orbit misalignment. The transit-based approach overcomes fundamental limitations of previous models by providing constraints on spot properties that would remain hidden in the null space of rotational light curves alone. This methodology enables more accurate exoplanet characterization by disentangling stellar activity due to starspots from planetary signals while simultaneously providing insights into stellar magnetic activity patterns. The whole paper is reproducible and can be found by clicking the GitHub icon ✎.