Steve Bryson

η _⊕ , the occurrence rate of rocky habitable zone exoplanets orbiting Sun-like stars, is of great interest to both the astronomical community and the general public. The Kepler space telescope has made it possible to estimate η _⊕ , but estimates by different groups vary by more than an order of magnitude. We identify several causes for this range of estimates. We first review why, despite being designed to estimate η _⊕ , Kepler’s observations are not sufficient for a high-confidence estimate, due to Kepler’s detection limit coinciding with the η _⊕ regime. This results in a need to infer η _⊕ , for example extrapolating from a regime of non-habitable zone, non-rocky exoplanets. We examine two broad classes of causes that can account for the large discrepancy in η _⊕ found in the literature: (a) differences in definitions and input data between studies, and (b) fundamental limits in Kepler data that lead to large uncertainties and poor accuracy. We highlight the risk of large biases when using extrapolation to describe small exoplanet populations in the habitable zone. We discuss how η _⊕ estimates based on Kepler data can be improved, such as reprocessing Kepler data for more complete, higher-reliability detections and better exoplanet catalog characterization. We briefly survey upcoming space telescopes capable of measuring η _⊕ , and how they can be used to supplement Kepler data.

Searching for life elsewhere in the universe is one of the most highly prioritized pursuits in astronomy today. However, the ability to observe evidence of Earth-like life through biosignatures is limited by the number of planets in the solar neighborhood with conditions similar to Earth. The occurrence rate of Earth-like planets in the habitable zones of Sun-like stars, η _⊕ , is therefore crucial for addressing the apparent lack of consensus on its value in the literature. Here we present a review of the current understanding of η _⊕ . We first provide definitions for parameters that contribute to η _⊕ . Then, we discuss the previous and current estimated parameter values and the context of the limitations on the analyses that produced these estimates. We compile an extensive list of the factors that go into any calculation of η _⊕ , and how detection techniques and surveys differ in their sensitivity and ability to accurately constrain η _⊕ . Understanding and refining the value of η _⊕ is crucial for upcoming missions and telescopes, such as the planned Habitable Worlds Observatory and the Large Interferometer for Exoplanets, which aim to search for biosignatures on exoplanets in the solar neighborhood.

Though free-floating planets (FFPs) may outpopulate their bound counterparts in the terrestrial-mass range, they remain one of the least explored exoplanet demographics. Due to their negligible electromagnetic emission at all wavelengths, the only observational technique able to detect these worlds is gravitational microlensing. Microlensing by terrestrial-mass FFPs induces rare, short-duration magnifications of background stars, requiring high-cadence, wide-field surveys to detect these events. The Transiting Exoplanet Survey Satellite (TESS), though designed to detect close-bound exoplanets via transits, boasts a full-frame image cadence as short as 200 s and has monitored hundreds of millions of stars, providing a unique dataset in which to search for rare short-duration transients. We have performed a preliminary search for FFP microlensing in 7.5 million light curves from TESS Sectors 61–65. We find one short-duration event with a light-curve morphology consistent with expectations for a low-mass FFP, but in tension with the expected FFP abundance in this mass range. We consider possible false-positive interpretations of this event such as stellar flares, heartbeat binaries, and centrifugal breakout. We find that all interpretations pose some challenges, and we discuss the possibility that the event may constitute a first example of a new class of pernicious false positives that future space-based microlensing efforts will encounter. Our ongoing search through the TESS dataset will significantly support the upcoming hunt for rogue worlds with dedicated space-based microlensing surveys, and our results may be used alongside these surveys to place interesting constraints on the spatial distribution of FFPs in the Galaxy.

The Transiting Exoplanet Survey Satellite (TESS) has identified several thousand planet candidates orbiting a wide variety of stars, and has provided an exciting opportunity for demographic studies. However, current TESS planet searches require significant manual inspection efforts to identify planets among the enormous number of detected transit-like signatures, which limits the scope of such searches. Demographic studies also require a detailed understanding of the relationship between observed and true exoplanet populations, a task for which current TESS planet catalogs are rendered unsuitable by the subjectivity of vetting by eye. We present LEO-Vetter , a publicly available and fully automated exoplanet vetting system designed after the Kepler Robovetter, which is capable of efficiently producing catalogs of promising planet candidates and making statistically robust TESS demographic studies possible. LEO-Vetter implements flux- and pixel-level tests against noise/systematic false positives and astrophysical false positives. The vetter achieves high completeness (91%) and high reliability against noise/systematic false alarms (97%) based on its performance on simulated data. We demonstrate the usefulness of the vetter by searching ∼200,000 M dwarf light curves, and reducing ∼20,000 transit-like detections down to 172 uniformly vetted planet candidates. LEO-Vetter facilitates analyses that would otherwise be impractical to perform on all possible signals due to time constraints or computational limitations. Users will be able to efficiently produce their own TESS planet catalog starting with transit-like detections, as well as have the framework needed to characterize their catalog’s completeness and reliability for occurrence rates.

η _⊕ is the expected number of rocky habitable zone planets per star. Γ_⊕, the slope of the planet population in log space at Earth’s parameter values, is a quantity that is often used as a proxy for η _⊕. I discuss their relationship, focusing on how Γ_⊕ is an approximation to η _⊕ that may have large errors. I provide an explicit example showing that Γ_⊕ may underestimate η _⊕ by a factor of 2 in common cases.

We present a centroid-free method to identify which star is the source of a known transit signal from pixel data. This method is based on observed and simulated difference images, and provides a relative probability of a star being the source of the transit compared to other known stars. This method is robust at low S/N compared to common centroid-based methods, and is well suited for space-based transit surveys such as Kepler and TESS.

We recently described the results of an initial search through TESS Sector 61 for free-floating planets. In this short note, we provide important context for our results and clarify the language used in our initial manuscript to ensure that our intended message is appropriately conveyed.

We present Kepler exoplanet occurrence rates for planets between 0.5 and 16 R _⊕ and between 1 and 400 days. To measure occurrence, we use a nonparametric method via a kernel density estimator and use bootstrap random sampling for uncertainty estimation. We use a full characterization of completeness and reliability measurements from the Kepler Data Release 25 catalog, including detection efficiency, vetting completeness, astrophysical reliability, and false alarm reliability. We also include more accurate and homogeneous stellar radii from Gaia Data Release 2. In order to see the impact of these final Kepler properties, we revisit benchmark exoplanet occurrence rate measurements from the literature. We compare our measurements with previous studies to both validate our method and observe the dependence of these benchmarks on updated stellar and planet properties. For FGK stars, between 0.5 and 16 R _⊕ and between 1 and 400 days, we find an occurrence of 1.52 ± 0.08 planets per star. We investigate the dependence of occurrence as a function of radius, orbital period, and stellar type and compare with previous studies with excellent agreement. We measure the minimum of the radius valley to be 1.78 − 0.16 + 0.14 R _⊕ for FGK stars and find it to move to smaller radii for cooler stars. We also present new measurements of the slope of the occurrence cliff at 3–4 R _⊕, and find that the cliff becomes less steep at long orbital period. Our methodology will enable us to constrain theoretical models of planet formation and evolution in the future.

Most existing exoplanets are discovered using validation techniques rather than being confirmed by complementary observations. These techniques generate a score that is typically the probability of the transit signal being an exoplanet (y(x) = exoplanet) given some information related to that signal (represented by x). Except for the validation technique in Rowe et al. (2014), which uses multiplicity information to generate these probability scores, the existing validation techniques ignore the multiplicity boost information. In this work, we introduce a framework with the following premise: given an existing transit-signal vetter (classifier), improve its performance using multiplicity information. We apply this framework to several existing classifiers, which include vespa, Robovetter, AstroNet, ExoNet, GPC and RFC, and ExoMiner, to support our claim that this framework is able to improve the performance of a given classifier. We then use the proposed multiplicity boost framework for ExoMiner V1.2, which addresses some of the shortcomings of the original ExoMiner classifier, and validate 69 new exoplanets for systems with multiple Kepler Objects of Interests from the Kepler catalog.