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Vetting of exoplanet candidates in transit surveys is a manual process, which suffers from a large number of false positives and a lack of consistency. Previous work has shown that Convolutional Neural Networks (CNN) provide an efficient…
The detection of planetary transits in stellar photometric light-curves is poised to become the main method for finding substantial numbers of terrestrial planets. The French-European mission COROT (foreseen for launch in 2005) will perform…
With large numbers of transients discovered by current and future imaging surveys, machine learning is increasingly applied to light curve and host galaxy properties to select events for follow-up. However, finding rare types of transients…
Automated planetary transit detection has become vital to prioritize candidates for expert analysis given the scale of modern telescopic surveys. While current methods for short-period exoplanet detection work effectively due to periodicity…
In the identification of new planetary candidates in transit surveys, the employment of Deep Learning models proved to be essential to efficiently analyse a continuously growing volume of photometric observations. To further improve the…
Context. Hot subdwarfs, which are hot and small He-burning objects, are ideal targets for exploring the evolution of planetary systems after the red giant branch (RGB). Thus far, no planets have been confirmed around them, and no systematic…
A parametric adaptive physics-informed greedy Latent Space Dynamics Identification (gLaSDI) method is proposed for accurate, efficient, and robust data-driven reduced-order modeling of high-dimensional nonlinear dynamical systems. In the…
The Transiting Exoplanet Survey Satellite (TESS) Full-Frame Images (FFIs) provide photometric time series for millions of stars, enabling transit searches beyond the limited set of pre-selected 2-minute targets. However, FFIs present…
Transiting planets manifest themselves by a periodic dimming of their host star by a fixed amount. On the other hand, light curves of transiting circumbinary (CB) planets are expected to be neither periodic nor to have a single depth while…
Research into light curves from stars (temporal variation of brightness) has completely changed how exoplanets are discovered or characterised. This study including star light curves from the Kepler dataset as a way to discover exoplanets…
The Large Synoptic Survey Telescope (LSST) will photometrically monitor approximately 1 billion stars for ten years. The resulting light curves can be used to detect transiting exoplanets. In particular, as demonstrated by Lund et al.…
PLATO is designed to detect Earth-sized exoplanets around solar-type stars and to measure their radii with accuracy better than \(2\%\) via the transit method. Charge transfer inefficiency (CTI), a by-product of radiation damage to CCDs,…
In the coming decades, research in extrasolar planets aims to advance two goals: 1) detecting and characterizing low-mass planets increasingly similar to the Earth, and 2) improving our understanding of planet formation. We present a new…
Context: Transit surveys, both ground- and space- based, have already accumulated a large number of light curves that span several years. Aims: The search for transiting planets in these long time series is computationally intensive. We…
This paper is to introduce an online tool for the prediction of exoplanet transit light curves. Small telescopes can readily capture exoplanet transits under good weather conditions when the combination of a bright star and a large…
Transit timing variation (TTV) provides rich information about the mass and orbital properties of exoplanets, which are often obtained by solving an inverse problem via Markov Chain Monte Carlo (MCMC). In this paper, we design a new…
Blazars are characterized by largely aperiodic variability on timescales ranging from minutes to decades across the electromagnetic spectrum. The TESS (Transiting Exoplanet Survey Satellite) mission provides continuous sampling of blazar…
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 NASA Transiting Exoplanet Survey Satellite (TESS) is observing tens of millions of stars with time spans ranging from $\sim$ 27 days to about 1 year of continuous observations. This vast amount of data contains a wealth of information…
This paper presents GPFC, a novel Graphics Processing Unit (GPU) Phase Folding and Convolutional Neural Network (CNN) system to detect exoplanets using the transit method. We devise a fast folding algorithm parallelized on a GPU to amplify…