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In 2024 October, JWST observed a transit of Kepler-167 e, a Jupiter-analog planet on a 1000+ day orbit. These observations, recorded over a long baseline of nearly 60 hr, were designed to search for signatures of planetary oblateness and/or exomoons comparable to Ganymede. In this first in a series of studies analyzing these data, we report on constraints on Kepler-167 e’s oblateness. We explored a large grid of data reduction pipelines and modeling choices, including a new entirely independent reduction pipeline (“katahdin”) and two new treatments for limb darkening. We find that under a Bayesian model comparison framework the data are fit equally well by both spherical and oblate planet models, and that our ability to constrain the oblateness is negatively impacted by the influence of exposure-long trends. Using the most conservative of our posteriors, we place a 95% upper bound on the projected oblateness of f < 0.097, which corresponds to a rotation period of P ≥ 7.11 hr if the planet’s spin axis is aligned with the sky plane. We note, however, that the final bound depends on the choice of reduction pipeline and systematics model, and that our suite of end-to-end analyses produced bounds as low as f < 0.065 at 95%. We conclude that leveraging JWST to make tighter constraints on planetary oblateness will require further investigation into mitigating exposure-long trends and correlated noise.

Exomoons represent a crucial missing puzzle piece in our efforts to understand extrasolar planetary systems. To address this deficiency, we here describe an exomoon survey of 70 cool, giant transiting exoplanet candidates found by Kepler. We identify only one exhibiting a moon-like signal that passes a battery of vetting tests: Kepler-1708 b. We show that Kepler-1708 b is a statistically validated Jupiter-sized planet orbiting a Sun-like quiescent star at 1.6 au. The signal of the exomoon candidate, Kepler-1708 b-i, is a 4.8 σ effect and is persistent across different instrumental detrending methods, with a 1% false-positive probability via injection–recovery. Kepler-1708 b-i is ~2.6 Earth radii and is located in an approximately coplanar orbit at ~12 planetary radii from its ~1.6 au Jupiter-sized host. Future observations will be necessary to validate or reject the candidate. A 4.8 σ exomoon candidate is found around gas giant Kepler-1708 b, which orbits at 1.6 au around its star. It is the only candidate from a dedicated survey that analysed 70 cool giant exoplanets discovered by Kepler. Kepler-1708 b-i has a radius of 2.6 Earth radii and orbits its planet at 12 planetary radii.

Accurate, precise, and computationally efficient removal of unwanted activity that exists as a combination of periodic, quasiperiodic, and nonperiodic systematic trends in time-series photometric data is a critical step in exoplanet transit analysis. Throughout the years, many different modeling methods have been used for this process, often called “detrending.” However, there is no community-wide consensus regarding the favored approach. In order to mitigate model dependency, we present an ensemble-based approach to detrending via a community of models and the democratic detrender: a modular and scalable open-source coding package that implements ensemble detrending. The democratic detrender allows users to select from a number of packaged detrending methods (including cosine filtering, Gaussian processes, and polynomial fits) or provide their own set of detrended light curves via methods of their choosing. It then combines the individually detrended light curves into a single method marginalized light curve. Additionally, the democratic detrender inflates each data point’s uncertainty based on the scatter between detrenders, thereby propagating model-selection uncertainty into the final light curve. This ensemble strategy does not guarantee improvement over the single best-performing detrending method, but it substantially reduces the risk of selecting a detrending solution that is poorly calibrated or overfit to noise.

Discovering and characterizing exoplanets at the outer edge of the transit method’s sensitivity has proven challenging owing to geometric biases and the practical difficulties associated with acquiring long observational baselines. Nonetheless, a sample of giant exoplanets on orbits longer than 100 days has been identified by transit hunting missions. We present long-term Doppler spectroscopy for 11 such systems with observation baselines spanning a few years to a decade. We model these radial velocity observations jointly with transit photometry to provide initial characterizations of these objects and the systems in which they exist. Specifically, we make new precise mass measurements for four long-period giant exoplanets (Kepler-111 c, Kepler-553 c, Kepler-849 b, and PH-2 b), we place new upper limits on mass for four others (Kepler-421 b, KOI-1431.01, Kepler-1513 b, and Kepler-952 b), and we show that several confirmed planets are in fact not planetary at all. We present these findings to complement similar efforts focused on closer-in short-period giant planets, and with the hope of inspiring future dedicated studies of cool giant exoplanets.

Recently Kipping (2021) identified the so-called \"exomoon corridor\", a potentially powerful new tool for identifying possible exomoon hosts, enabled by the observation that fully half of all planets hosting an exomoon will exhibit transit timing variation (TTV) periodicities of 2-4 epochs. One key outstanding problem in the search for exomoons, however, is the question of how well the methods we have developed under the single moon assumption extend to systems with multiple moons. In this work we use \\(N\\)-body simulations to examine the exomoon corridor effect in the more general case of \\(N 1\\) moons, generating realistic TTVs produced by satellite systems more akin to those seen in the outer Solar System. We find that indeed the relationship does hold for systems with up to 5 moons in both resonant and non-resonant chain configurations. Our results suggest an observational bias against finding systems with large numbers of massive moons; as the number of moons increases, total satellite mass ratios are generally required to be significantly lower in order to maintain stability, or architectures must be more finely tuned to survive. Moons produced in impact or capture scenarios may therefore dominate early detections. Finally, we examine the distribution of TTV periods measured for a large number of Kepler Objects of Interest (KOIs) and find the same characteristic exomoon corridor distribution in several cases. This could be dynamical evidence for an abundance of moons in the field, though we caution against strong inferences based on this result.

The circumplanetary environments in our Solar System host a stunning array of moon and ring systems. Study of these environs has yielded valuable insights into planetary system formation and evolution, and there is every reason to believe that we will have much to learn from the moons and rings that are likely to exist in exoplanetary systems as well. This has motivated a small but growing number of researchers to investigate questions related to the formation, stability, long-term viability, composition, and observability of these exomoons and exorings. Still, due to a range of significant observational challenges, we remain at a relatively early stage of this work. As a result, we continue to face a number of difficult, unanswered questions, but this also means there are myriad opportunities for fundamental contributions to the field. In this review we will examine a variety of important issues for the astronomical community to consider, with an aim of providing a comprehensive understanding of ongoing efforts to identify and characterize exomoons and exorings, while also increasing interest and engagement. We begin with an overview of what we expect from systems hosting moons and/or rings in terms of their architectures, habitability, and observational signatures. We then highlight the contributions from a variety of works that have been aimed at detecting and characterizing them. We conclude by examining the outlook for finding these objects and discussing a number of ongoing challenges that we will want to overcome in the years ahead.

Targeted observations of possible exomoon host systems will remain difficult to obtain and time-consuming to analyze in the foreseeable future. As such, time-domain surveys such as Kepler, K2 and TESS will continue to play a critical role as the first step in identifying candidate exomoon systems, which may then be followed-up with premier ground- or space-based telescopes. In this work, we train an ensemble of convolutional neural networks (CNNs) to identify candidate exomoon signals in single-transit events observed by Kepler. Our training set consists of \\(\\)27,000 examples of synthetic, planet-only and planet+moon single transits, injected into Kepler light curves. We achieve up to 88\\% classification accuracy with individual CNN architectures and 97\\% precision in identifying the moons in the validation set when the CNN ensemble is in total agreement. We then apply the CNN ensemble to light curves from 1880 Kepler Objects of Interest with periods \\(>10\\) days (\\(\\)57,000 individual transits), and further test the accuracy of the CNN classifier by injecting planet transits into each light curve, thus quantifying the extent to which residual stellar activity may result in false positive classifications. We find a small fraction of these transits contain moon-like signals, though we caution against strong inferences of the exomoon occurrence rate from this result. We conclude by discussing some ongoing challenges to utilizing neural networks for the exomoon search.

Exomoons are predicted to produce transit timing variations (TTVs) upon their host planet. Unfortunately, so are many other astrophysical phenomena - most notably other planets in the system. In this work, an argument of reductio ad absurdum is invoked, by deriving the transit timing effects that are impossible for a single exomoon to produce. Our work derives three key analytic tests. First, one may exploit the fact that a TTV signal from an exomoon should be accompanied by transit duration variations (TDVs), and that one can derive a TDV floor as a minimum expected level of variability. Cases for which the TDV upper limit is below this floor can thus be killed as exomoon candidates. Second, formulae are provided for estimating whether moons are expected to be 'killable' when no TDVs presently exist, thus enabling the community to estimate whether it's even worth deriving TDVs in the first place. Third, a TTV ceiling is derived, above which exomoons should never be able to produce TTV amplitudes. These tools are applied to a catalog of TTVs and TDVs for two and half thousand Kepler Objects Interest, revealing over two hundred cases that cannot be due to a moon. These tests are also applied to the exomoon candidate Kepler-1625b i, which comfortably passes the criteria. These simple analytic results should provide a means of rapidly rejecting putative exomoons and streamlining the search for satellites.

The search for exomoons in time-domain photometric data has to-date generally consisted of fitting transit models that are comprised of a planet hosting a single moon. This simple model has its advantages, but it may not be particularly representative, as most of the major moons in our Solar System are found in multi-moon satellite systems. It is critical that we investigate, then, the impact of applying a single-moon model to systems containing multiple moons, as there is the possibility that utilizing an inaccurate or incomplete model could lead to erroneous conclusions about the system. To that end, in this work we produce a variety of realistic multi-moon light curves, perform standard single-moon model selection, and analyze the impacts that this model choice may have on the search for exomoons. We find that the number of moons in a system fit with a single-moon model generally has little impact on whether we find evidence for a moon in that system, and other system attributes are individually not especially predictive. However, the model parameter solutions for the moon frequently do not match any real moon in the system, instead painting a picture of a ``phantom'' moon. We find no evidence that multi-moon systems yield corresponding multi-modal posteriors. We also find a systematic tendency to overestimate planetary impact parameter and eccentricity, to derive unphysical moon densities, and to infer potentially unphysical limb darkening coefficients. These results will be important to keep in mind in future exomoon search programs.