Related papers: One-dimensional Convolutional Neural Networks for …
The Euclid telescope, due for launch in 2021, will perform an imaging and slitless spectroscopy survey over half the sky, to map baryon wiggles and weak lensing. During the survey Euclid is expected to resolve 100,000 strong gravitational…
Precise physical properties of the known transiting exoplanets are essential for their precise atmospheric characterization using modern and upcoming instruments. Leveraging the large volume of high SNR photometric follow-up data from TESS,…
We present a novel machine-learning approach for detecting faint point sources in high-contrast adaptive optics imaging datasets. The most widely used algorithms for primary subtraction aim to decouple bright stellar speckle noise from…
The treatment of systematic noise is a significant aspect of transit exoplanet data processing due to the signal strength of systematic noise relative to a transit signal. Typically the standard approach to transit detection is to estimate…
Rings around exoplanets (exorings) are one of the most expected discoveries in exoplanetary research. There is an increasing number of theoretical and observational efforts for detecting exorings, but none of them have succeeded yet. Most…
There is a unique solution of the planet and star parameters from a planet transit light curve with two or more transits if the planet has a circular orbit and the light curve is observed in a band pass where limb darkening is negligible.…
Exoplanet detection by direct imaging is a difficult task: the faint signals from the objects of interest are buried under a spatially structured nuisance component induced by the host star. The exoplanet signals can only be identified when…
Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts. The classifier uses the…
NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detection sensitivity. Accurately determining the occurrence rate…
Global Navigation Satellite System (GNSS) signals are subject to different kinds of events causing significant errors in positioning. This work explores the application of Machine Learning (ML) methods of anomaly detection applied to GNSS…
Context. Detecting regular dips in the light curve of a star is an easy way to detect the presence of an orbiting planet. COROT is a Franco-European mission launched at the end of 2006, and one of its main objectives is to detect planetary…
We present a theoretical analysis of the optical light curves (LCs) for short-period high-mass transiting extrasolar planet systems. Our method considers the primary transit, the secondary eclipse, and the overall phase shape of the LC…
The exoplanet detection is the most exciting and challenging field of astronomy. The discovery of many exoplanets has revolutionized our understanding of the formation and evolution of planetary systems and has showed new ways to search for…
One of the biggest challenges facing large transit surveys is the elimination of false-positives from the vast number of transit candidates. We investigate to what extent information from the lightcurves can identify blend scenarios and…
This paper presents a 1-D convolutional graph neural network for fault detection in microgrids. The combination of 1-D convolutional neural networks (1D-CNN) and graph convolutional networks (GCN) helps extract both spatial-temporal…
Recent interest in on-orbit servicing and Active Debris Removal (ADR) missions have driven the need for technologies to enable non-cooperative rendezvous manoeuvres. Such manoeuvres put heavy burden on the perception capabilities of a…
New time-domain surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe millions of transient alerts each night, making standard approaches of visually identifying new and interesting transients…
Very high quality light curves are now available for thousands of detached eclipsing binary stars and transiting exoplanet systems as a result of surveys for transiting exoplanets and other large-scale photometric surveys. I have developed…
The TESS follow-up of a large number of known transiting exoplanets provide unique opportunity to study their physical properties more precisely. Being a space-based telescope, the TESS observations are devoid of any noise component…
Convolutional Neural Networks (CNNs) have demonstrated potential for the real-time analysis of data from gravitational-wave detector networks for the specific case of signals from coalescing compact-object binaries such as black-hole…