Related papers: exoplanet: Gradient-based probabilistic inference …
It has recently been demonstrated that deep learning has significant potential to automate parts of the exoplanet detection pipeline using light curve data from satellites such as Kepler \cite{borucki2010kepler} \cite{koch2010kepler} and…
The estimation of periodicity is a fundamental task in many scientific areas of study. Existing methods rely on theoretical assumptions that the observation times have equal or i.i.d. spacings, and that common estimators, such as the…
The field of astronomy is experiencing a data explosion driven by significant advances in observational instrumentation, and classical methods often fall short of addressing the complexity of modern astronomical datasets. Probabilistic…
We present a database of well determined orbital parameters of exoplanets. This database comprises spectroscopic orbital elements measured for 427 planets orbiting 363 stars from radial velocity and transit measurements as reported in the…
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian Inference, we can test…
Even though the original Kepler mission ended due to mechanical failures, the Kepler satellite continues to collect data. Using classification models, we can understand the features exoplanets possess and then use those features to…
There are many competing theories and models describing the formation, migration and evolution of exoplanet systems. As both the precision with which we can characterize exoplanets and their host stars, and the number of systems for which…
Useful information can be retrieved by analysing the transit light curve of a planet-hosting star or induced radial velocity oscillations. However, inferring the physical parameters of the planet, such as mass, size, and semi-major axis,…
Planets are complicated. Understanding how they work requires connecting individual objects to the context of broader populations. Exoplanets are easier to picture next to their closest Solar System archetypes, and planets in the Solar…
We obtain full information on the orbital parameters by combining radial velocity and astrometric measurements by means of Bayesian inference. We sample the parameter probability densities of orbital model parameters with a Markov chain…
We present the next generation public exoplanet fitting software, EXOFASTv2. It is capable of fitting an arbitrary number of planets, radial velocity data sets, astrometric data sets, and/or transits observed with any combination of…
In the broadest sense, the primary goal of exoplanet demographic surveys is to determine the frequency and distribution of planets as a function of as many of the physical parameters that may influence planet formation and evolution as…
I describe ongoing work on development of Bayesian methods for exploring periodically varying phenomena in astronomy, addressing two classes of sources: pulsars, and extrasolar planets (exoplanets). For pulsars, the methods aim to detect…
We present CONAN (COde for exoplaNet ANalysis), an open-source Python package for comprehensive analyses of exoplanetary systems. It provides a unified Bayesian framework to simultaneously analyze diverse exoplanet datasets to derive global…
Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose…
We present PlanetPack, a new software tool that we developed to facilitate and standardize the advanced analysis of radial velocity (RV) data for the goal of exoplanets detection, characterization, and basic dynamical $N$-body simulations.…
Recently, Odrzywolek and Rafelski (arXiv:1612.03556) have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using…
Photometric stability is a key requirement for time-resolved spectroscopic observations of transiting extrasolar planets. In the context of the Exoplanet Characterisation Observatory (EChO) mission design, we here present and investigate…
With the advanced capabilities of ground- and space-based telescopes, exoplanet science is beginning to characterize the physics and chemistry of exoplanet atmospheres. However, interpreting exoplanet observations requires sophisticated…
The characterization of an exoplanet's interior is an inverse problem, which requires statistical methods such as Bayesian inference in order to be solved. Current methods employ Markov Chain Monte Carlo (MCMC) sampling to infer the…