Related papers: Exoplanet Detection using Machine Learning

We propose a new framework to predict stellar properties from light curves. We analyze the light-curve data from the Kepler space mission and develop a novel tool for deriving the stellar rotation periods for main-sequence stars. Using this…

The Kepler Mission has discovered thousands of exoplanets and revolutionized our understanding of their population. This large, homogeneous catalog of discoveries has enabled rigorous studies of the occurrence rate of exoplanets and…

The microlensing technique has found 10 exoplanets to date and promises to discover more in the near future. While planetary transit light curves all show a familiar shape, planetary perturbations to microlensing light curves can manifest a…

Detecting exoplanet transits at X-ray wavelengths would provide a window into the effects of high energy irradiation on the upper atmospheres of planets. However, stars are relatively dim in the X-ray, making exoplanet transit detections…

We present a detection criterion for exo-planets to be used with the space mission COROT. This criterion is based on the transit method, which suggests the observation of star dimming caused by partial occulations by planetary companions.…

We show that exoplanets in the M31 galaxy may be detected with the pixel-lensing method by using telescopes making high cadence observations of an ongoing microlensing event. Although the mean mass for detectable exoplanets is about $2…

In a previous paper, we have introduced a deep learning neural network that should be able to detect the existence of very shallow periodic planetary transits in the presence of red noise. The network in that feasibility study would not…

We are still in the early days of exoplanet discovery. Astronomers are beginning to model the atmospheres and interiors of exoplanets and have developed a deeper understanding of processes of planet formation and evolution. However, we have…

All life on Earth needs water. NASA's quest to follow the water links water to the search for life in the cosmos. Telescopes like JWST and mission concepts like HabEx, LUVOIR and Origins are designed to characterise rocky exoplanets…

Over the past decade, the study of extrasolar planets has evolved rapidly from plain detection and identification to comprehensive categorization and characterization of exoplanet systems and their atmospheres. Atmospheric retrieval, the…

Exoplanets, or planets outside our own solar system, have long been of interest to astronomers; however, only in the past two decades have scientists had the technology to characterize and study planets so far away from us. With advanced…

Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniques such as linear regression and neural networks can…

Photometry with the transit method has arguably been the most successful exoplanet discovery method to date. A short overview about the rise of that method to its present status is given. The method's strength is the rich set of parameters…

Despite the ever-growing number of exoplanets discovered and the extensive analyses carried out to find their potential satellites, only two exomoon candidates, Kepler-1625b-i and Kepler-1708 b-i, have been discovered to date. A…

We present the Cambridge Exoplanet Transit Recovery Algorithm (CETRA), a fast and sensitive transit detection algorithm, optimised for GPUs. CETRA separates the task into a search for transit signals across linear time space, followed by a…

We present a novel method for direct detection and characterization of exoplanets from space. This method uses four collecting telescopes, combined with phase chopping and a spectrometer, with observations on only a few baselines rather…

Precise exoplanet characterization requires precise classification of exoplanet host stars. The masses of host stars are commonly estimated by comparing their spectra to those predicted by stellar evolution models. However,…

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ~85% of the sky throughout its two-year primary mission, resulting in millions of TESS 30-minute cadence light curves to analyze in the search for…

We explore the application of machine learning based on mixture density neural networks (MDNs) to the interior characterization of low-mass exoplanets up to 25 Earth masses constrained by mass, radius, and fluid Love number $k_2$. We create…

We present ExoMiner++, an enhanced deep learning model that builds on the success of ExoMiner to improve transit signal classification in 2-minute TESS data. ExoMiner++ incorporates additional diagnostic inputs, including periodogram, flux…