EXONEST: The Bayesian Exoplanetary Explorer

The fields of astronomy and astrophysics are currently engaged in an unprecedented era of discovery as recent missions have revealed thousands of exoplanets orbiting other stars. While the Kepler Space Telescope mission has enabled most of these exoplanets to be detected by identifying transiting events, exoplanets often exhibit additional photometric effects that can be used to improve the characterization of exoplanets. The EXONEST Exoplanetary Explorer is a Bayesian exoplanet inference engine based on nested sampling and originally designed to analyze archived Kepler Space Telescope and CoRoT (Convection Rotation et Transits plan\'etaires) exoplanet mission data. We discuss the EXONEST software package and describe how it accommodates plug-and-play models of exoplanet-associated photometric effects for the purpose of exoplanet detection, characterization and scientific hypothesis testing. The current suite of models allows for both circular and eccentric orbits in conjunction with photometric effects, such as the primary transit and secondary eclipse, reflected light, thermal emissions, ellipsoidal variations, Doppler beaming and superrotation. We discuss our new efforts to expand the capabilities of the software to include more subtle photometric effects involving reflected and refracted light. We discuss the EXONEST inference engine design and introduce our plans to port the current MATLAB-based EXONEST software package over to the next generation Exoplanetary Explorer, which will be a Python-based open source project with the capability to employ third-party plug-and-play models of exoplanet-related photometric effects.Comment: 30 pages, 8 figures, 5 tables. Presented at the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017) in Jarinu/SP Brasi

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval

Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric retrieval by implementing a random forest to perform retrievals in seconds that are consistent with the traditional, computationally-expensive nested-sampling retrieval method. We expand upon their approach by presenting a new machine learning model, \texttt{plan-net}, based on an ensemble of Bayesian neural networks that yields more accurate inferences than the random forest for the same data set of synthetic transmission spectra. We demonstrate that an ensemble provides greater accuracy and more robust uncertainties than a single model. In addition to being the first to use Bayesian neural networks for atmospheric retrieval, we also introduce a new loss function for Bayesian neural networks that learns correlations between the model outputs. Importantly, we show that designing machine learning models to explicitly incorporate domain-specific knowledge both improves performance and provides additional insight by inferring the covariance of the retrieved atmospheric parameters. We apply \texttt{plan-net} to the Hubble Space Telescope Wide Field Camera 3 transmission spectrum for WASP-12b and retrieve an isothermal temperature and water abundance consistent with the literature. We highlight that our method is flexible and can be expanded to higher-resolution spectra and a larger number of atmospheric parameters

Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks

Atmospheric retrievals (AR) of exoplanets typically rely on a combination of a Bayesian inference technique and a forward simulator to estimate atmospheric properties from an observed spectrum. A key component in simulating spectra is the pressure-temperature (PT) profile, which describes the thermal structure of the atmosphere. Current AR pipelines commonly use ad hoc fitting functions here that limit the retrieved PT profiles to simple approximations, but still use a relatively large number of parameters. In this work, we introduce a conceptually new, data-driven parameterization scheme for physically consistent PT profiles that does not require explicit assumptions about the functional form of the PT profiles and uses fewer parameters than existing methods. Our approach consists of a latent variable model (based on a neural network) that learns a distribution over functions (PT profiles). Each profile is represented by a low-dimensional vector that can be used to condition a decoder network that maps $P$ to $T$. When training and evaluating our method on two publicly available datasets of self-consistent PT profiles, we find that our method achieves, on average, better fit quality than existing baseline methods, despite using fewer parameters. In an AR based on existing literature, our model (using two parameters) produces a tighter, more accurate posterior for the PT profile than the five-parameter polynomial baseline, while also speeding up the retrieval by more than a factor of three. By providing parametric access to physically consistent PT profiles, and by reducing the number of parameters required to describe a PT profile (thereby reducing computational cost or freeing resources for additional parameters of interest), our method can help improve AR and thus our understanding of exoplanet atmospheres and their habitability.Comment: Accepted for publication in Astronomy & Astrophysic

An Unusual Transmission Spectrum for the Sub-Saturn KELT-11b Suggestive of a Sub-Solar Water Abundance

We present an optical-to-infrared transmission spectrum of the inflated sub-Saturn KELT-11b measured with the Transiting Exoplanet Survey Satellite (TESS), the Hubble Space Telescope (HST) Wide Field Camera 3 G141 spectroscopic grism, and the Spitzer Space Telescope (Spitzer) at 3.6 $\mu$m, in addition to a Spitzer 4.5 $\mu$m secondary eclipse. The precise HST transmission spectrum notably reveals a low-amplitude water feature with an unusual shape. Based on free retrieval analyses with varying molecular abundances, we find strong evidence for water absorption. Depending on model assumptions, we also find tentative evidence for other absorbers (HCN, TiO, and AlO). The retrieved water abundance is generally $\lesssim 0.1\times$ solar (0.001--0.7$\times$ solar over a range of model assumptions), several orders of magnitude lower than expected from planet formation models based on the solar system metallicity trend. We also consider chemical equilibrium and self-consistent 1D radiative-convective equilibrium model fits and find they too prefer low metallicities ($[M/H] \lesssim -2$, consistent with the free retrieval results). However, all the retrievals should be interpreted with some caution since they either require additional absorbers that are far out of chemical equilibrium to explain the shape of the spectrum or are simply poor fits to the data. Finally, we find the Spitzer secondary eclipse is indicative of full heat redistribution from KELT-11b's dayside to nightside, assuming a clear dayside. These potentially unusual results for KELT-11b's composition are suggestive of new challenges on the horizon for atmosphere and formation models in the face of increasingly precise measurements of exoplanet spectra.Comment: Accepted to The Astronomical Journal. 31 pages, 20 figures, 7 table

A ground-based near-infrared emission spectrum of the exoplanet HD 189733b

Detection of molecules using infrared spectroscopy probes the conditions and compositions of exoplanet atmospheres. Water (H2O), methane (CH4), carbon dioxide (CO2), and carbon monoxide (CO) have been detected in two hot Jupiters. These previous results relied on space-based telescopes that do not provide spectroscopic capability in the 2.4 - 5.2 micron spectral region. Here we report ground-based observations of the dayside emission spectrum for HD 189733b between 2.0-2.4 micron and 3.1-4.1 micron, where we find a bright emission feature. Where overlap with space-based instruments exists, our results are in excellent agreement with previous measurements. A feature at ~3.25 micron is unexpected and difficult to explain with models that assume local thermodynamic equilibrium (LTE) conditions at the 1 bar to 1 x 10-6 bar pressures typically sampled by infrared measurements. The most likely explanation for this feature is that it arises from non-LTE emission from CH4, similar to what is seen in the atmospheres of planets in our own Solar System. These results suggest that non-LTE effects may need to be considered when interpreting measurements of strongly irradiated exoplanets.Comment: 12 pages, 2 figures, published in Natur

Transiting Exoplanet Studies and Community Targets for JWST's Early Release Science Program

The James Webb Space Telescope will revolutionize transiting exoplanet atmospheric science due to its capability for continuous, long-duration observations and its larger collecting area, spectral coverage, and spectral resolution compared to existing space-based facilities. However, it is unclear precisely how well JWST will perform and which of its myriad instruments and observing modes will be best suited for transiting exoplanet studies. In this article, we describe a prefatory JWST Early Release Science (ERS) program that focuses on testing specific observing modes to quickly give the community the data and experience it needs to plan more efficient and successful future transiting exoplanet characterization programs. We propose a multi-pronged approach wherein one aspect of the program focuses on observing transits of a single target with all of the recommended observing modes to identify and understand potential systematics, compare transmission spectra at overlapping and neighboring wavelength regions, confirm throughputs, and determine overall performances. In our search for transiting exoplanets that are well suited to achieving these goals, we identify 12 objects (dubbed "community targets") that meet our defined criteria. Currently, the most favorable target is WASP-62b because of its large predicted signal size, relatively bright host star, and location in JWST's continuous viewing zone. Since most of the community targets do not have well-characterized atmospheres, we recommend initiating preparatory observing programs to determine the presence of obscuring clouds/hazes within their atmospheres. Measurable spectroscopic features are needed to establish the optimal resolution and wavelength regions for exoplanet characterization. Other initiatives from our proposed ERS program include testing the instrument brightness limits and performing phase-curve observations.(Abridged)Comment: This is a white paper that originated from an open discussion at the Enabling Transiting Exoplanet Science with JWST workshop held November 16 - 18, 2015 at STScI (http://www.stsci.edu/jwst/science/exoplanets). Accepted for publication in PAS

KELT-16b: A Highly Irradiated, Ultra-short Period Hot Jupiter Nearing Tidal Disruption

We announce the discovery of KELT-16b, a highly irradiated, ultra-short period hot Jupiter transiting the relatively bright (V = 11.7) star TYC 2688-1839-1/KELT-16. A global analysis of the system shows KELT-16 to be an F7V star with K and . The planet is a relatively high-mass inflated gas giant with density g cm-3, surface gravity , and K. The best-fitting linear ephemeris is and day. KELT-16b joins WASP-18b, -19b, -43b, -103b, and HATS-18b as the only giant transiting planets with P \u3c 1 day. Its ultra-short period and high irradiation make it a benchmark target for atmospheric studies by the Hubble Space Telescope, Spitzer, and eventually the James Webb Space Telescope. For example, as a hotter, higher-mass analog of WASP-43b, KELT-16b may feature an atmospheric temperature-pressure inversion and day-to-night temperature swing extreme enough for TiO to rain out at the terminator. KELT-16b could also join WASP-43b in extending tests of the observed mass-metallicity relation of the solar system gas giants to higher masses. KELT-16b currently orbits at a mere ∼1.7 Roche radii from its host star, and could be tidally disrupted in as little as a few ×105 years (for a stellar tidal quality factor of ). Finally, the likely existence of a widely separated bound stellar companion in the KELT-16 system makes it possible that Kozai-Lidov (KL) oscillations played a role in driving KELT-16b inward to its current precarious orbit

Life Beyond the Solar System: Remotely Detectable Biosignatures

For the first time in human history, we will soon be able to apply to the scientific method to the question "Are We Alone?" The rapid advance of exoplanet discovery, planetary systems science, and telescope technology will soon allow scientists to search for life beyond our Solar System through direct observation of extrasolar planets. This endeavor will occur alongside searches for habitable environments and signs of life within our Solar System. While these searches are thematically related and will inform each other, they will require separate observational techniques. The search for life on exoplanets holds potential through the great diversity of worlds to be explored beyond our Solar System. However, there are also unique challenges related to the relatively limited data this search will obtain on any individual world