Julian C. van Eyken

High-resolution imaging is widely used to constrain false positive scenarios in exoplanet validation, but it is a finite follow-up resource that reaches only a subset of candidates, and its population-level impact on validation outcomes has not been quantified through controlled removal experiments. Using an automated pipeline built on TRICERATOPS , we compute the false positive probability (FPP) of 443 TESS planet candidates. For the 264 planet candidates with high-resolution imaging observations, we compute FPP with and without the corresponding contrast curves, allowing us to quantify the impact of the additional data. We find that 72% of 68 contrast-curve-bearing validated planets would fail validation without their adopted contrast curves. The fraction requiring imaging decreases with increasing planet size, from 100% below 1.7 R _⊕ to 33% above 4 R _⊕ : within our sample and TRICERATOPS -based analysis, the availability of high-resolution imaging directly limits the yield of small-planet validation and the supply of validated targets for atmospheric characterization. Our analysis statistically validates 64 new TESS planets with sizes spanning 0.94 to 7.83 R _⊕ across hosts of spectral types: M through F. Four of these are highly amenable to JWST observations based on the transmission and emission spectroscopy metrics, and each achieves validation only with its imaging constraint.

Context . Hot Jupiters are key targets for understanding planet formation, migration, and atmospheres. Yet most of the ground-based observational resources for the follow-up of the TESS mission are focused on the confirmation of low-mass planet candidates. This leaves the more massive planets, such as hot Jupiters, without mass determinations and definitive confirmations. Aims . We used the CAFE ₂ spectrograph at the Calar Alto Observatory to monitor the radial velocity of stars with hot-Jupiter candidates that have been left behind by follow-up efforts with the goal of confirming their planetary nature. Here, we present the results for seven candidates. Methods . We monitored the radial velocity of the seven candidate host stars TOI-603, TOI-1137, TOI-1837, TOI-2114, TOI-4492, TOI-5806, and TOI-5811. Each hosts a hot-Jupiter candidate detected by the TESS mission. We characterized these stars and jointly modeled the CAFE ₂ RVs and the TESS photometric data to unravel the nature of the transiting objects and to infer their properties. Results . The objects we confirmed to be new planets are TOI-603 b (mass 33.0 ^+6.5 _−6.2 M _⊕ , period 16.2 d); TOI-2114 b (1.01 ^+0.14 _−0.12 M _Jup , 6.2 d); TOI-4492 b (5.92 ^+0.67 _−0.64 M _Jup , 4.4 d); TOI-5806 b (2.77 ^+0.34 _−0.32 M _Jup , 3.2 d); and TOI-5811 B b (0.81 ^+0.11 _−0.10 M _Jup , 6.3 d). Based on their masses and periods, TOI-603 b is a member of the “Neptune savanna”, while TOI-2114 b, TOI-4492 b, TOI-5806 b, and TOI-5811 B b are hot Jupiters orbiting slightly evolved stars. We found the candidate TOI-5811.01 to actually be a planet orbiting the nearby bound companion TOI-5811 B. We also identified a bound stellar companion to TOI-5806 at a projected separation of 248 au, thus both form satellite-type planetary systems. As for the two remaining candidates, TOI-1837.01 is definitely an eclipsing binary, while the nature of TOI-1137.01 remains indeterminate. Conclusions . The five newly confirmed planets orbit relatively bright stars (G = 8.6–10.2 mag), and four of them are excellent candidates for atmospheric studies (with transmission spectroscopy metrics exceeding 90 for TOI-603 b, TOI-2114 b, TOI-5806 b, and TOI-5811 B b). The complex configurations of all of these systems underscore the need for intensive follow-up efforts to clarify the nature of transiting planet candidates.

Despite decades of research on hot Jupiters, there are still several theories for their formation. Perhaps hot Jupiters form in several ways. Atmospheric and dynamical studies have the capability to constrain the formation scenarios. However, potential targets have to be well characterized before these observations can further constrain the theories. We present the confirmation and characterization of five hot and warm Jupiters discovered by the TESS space mission. Using TESS data combined with ground-based observations, we determine the masses, radii, and other parameters of TOI-2040 b, TOI-2049 b, TOI-2578 b, TOI-4427 b, and TOI-4458 b. Three of the planets have equilibrium temperatures of about 1800 K while two have temperatures of about 1000 K. Particularly interesting for future atmospheric characterizations are TOI-2578 b and TOI-4427 b, because of their low density and large transmission spectroscopy metric. TOI-4458 b is of special interest because it is in the northern PLATO field. It appears that TOI-2040 b has a small, but measurable eccentricity.

We report the discovery of TOI-7019b, the first transiting brown dwarf (BD) known to orbit a star that is part of the Milky Way’s ancient thick disk, as defined chemically ([Fe/H] = −0.79 ± 0.05 dex, [ α /Fe] = +0.26 ± 0.05 dex, [M/H] = −0.59 ± 0.06 dex) and kinematically ( v _⊥ ≈ 150 ± 1 km s ⁻¹ ). We estimate a system age τ = 12 ± 2 Gyr by fitting the host star’s spectrum and spectral energy distribution to alpha-enhanced isochrones and independently using the age−metallicity relation of the thick disk. This makes TOI-7019 by far the most metal-poor and ancient BD host known to date. We measure a BD mass of 61.3 M _J ± 2.1 M _J and radius of 0.82 R _J ± 0.02 R _J from a joint analysis of transit photometry and radial velocity measurements, along with an orbital period of 48.2592 ± 0.0001 days and an orbital eccentricity of 0.403 ± 0.002. The measured radius appears to be 12.3% ± 2.8% larger than predicted relative to standard evolutionary models for old, metal-poor BDs, as well as models that include stellar radiation, hinting at missing physics like the magnetic inhibition of convection. TOI-7019b lowers the probed metallicity regime for transiting BDs by over a factor of two, making it a benchmark system to test evolutionary models in the low-metallicity regime. Future measurements of TOI-7019b’s atmosphere will test whether a BD’s atmospheric composition tracks its host star’s abundances, as expected for binary-like co-formation.

The TESS Input Catalog (TIC) was built on Gaia Data Release 2 (DR2). To date, there has not been an update to the TIC to incorporate Gaia Data Release 3 (DR3) IDs. In this Research Note, we outline how we cross-matched the TIC with Gaia DR3 IDs, its immediate applications to exoplanet research, and lessons learned when dealing with such large datasets. A full TIC/Gaia DR3 cross-match table is available for download on the Exoplanet Follow-up Observing Program website, and a Jupyter Notebook with instructions to reproduce the table is available on GitHub.

The NASA Exoplanet Archive (NEA) and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NEA provides a complete and accurate accounting of exoplanetary systems published by NASA missions and by the community in the refereed literature. In anticipation of continued exponential growth in the number of exoplanetary systems and the increasing complexity in our characterization of these systems, the NEA has restructured its primary tables and interfaces, as well as extending and standardizing their modes of access. The Exoplanet Follow-up Observing Program service provides the exoplanet community with a venue for coordinating and sharing follow-up and precursor data for exoplanets, their host stars, and stars that might eventually be targets for future planet searches and recently reached 1 million files uploaded by the community. In this paper, we describe the updates to our data holdings, functionality, accessibility, and tools, as well as future priorities for these two services.

The NASA Exoplanet Archive and the Exoplanet Follow-up Observing Program service are two widely used resources for the exoplanet community. The NASA Exoplanet Archive provides a complete and accurate accounting of exoplanetary systems published by NASA missions and by the community in the refereed literature. In anticipation of continued exponential growth in the number of exoplanetary systems, and the increasing complexity in our characterization of these systems, the NASA Exoplanet Archive has restructured its primary tables and interfaces, as well as extending and standardizing their modes of access. The Exoplanet Follow-up Observing Program service provides the exoplanet community with a venue for coordinating and sharing follow-up and precursor data for exoplanets, their host stars, and stars that might eventually be targets for future planet searches, and recently reached one million files uploaded by the community. In this paper we describe the updates to our data holdings, functionality, accessibility, and tools, as well as future priorities for these two services.

Atmospheric retrieval is a modeling technique used to determine a planet’s atmosphere’s temperature and composition from spectral data. The retrieved atmospheric composition can provide understanding into the surface fluxes of gaseous species necessary to maintain the stability of that atmosphere, leading to insights into the geological as well as biological processes active on the planet. Among exoplanets, rocky terrestrial ones are of particular interest because of their theoretical habitability. Atmospheric retrieval is both time consuming and computationally intensive. Traditional retrieval methods involve the use of complex algorithms that generate numerous atmospheric models. These models are then compared to observational data, and a posterior distribution is constructed to determine the most likely value and associated uncertainty for each model parameter. Runtimes scale with the number of model parameters, and when many molecular species are considered, become prohibitively long. The issue will become especially prohibitive as the number of detected exoplanets will grow tremendously in the near future. Machine learning (ML) offers a way to reduce the time to perform a retrieval by orders of magnitude, given a sufficient data set to train with. Here we present a large data set of 3,112,620 synthetic planetary systems generated with our Intelligent Exoplanet Atmospheric Retrieval framework based on the NASA Planetary Spectrum Generator. The data set contains the parameters defining each planetary system and the simulated spectra of stellar, planetary and noise components. The data set was designed to enable the first ML retrieval model for rocky terrestrial exoplanets, and it is publicly available through the NASA Exoplanet Archive.