Related papers: One-dimensional Convolutional Neural Networks for …
Transit photometry is perhaps the most successful method for detecting exoplanets to date. However, a substantial amount of signal processing is needed since the dip in the signal detected, an indication that there is a planet in transit,…
In this work we describe a Convolutional Neural Network (CNN) to accurately predict the scene illumination. Taking image patches as input, the CNN works in the spatial domain without using hand-crafted features that are employed by most…
This paper describes a simple activity for plotting and characterizing the light curve from an exoplanet transit event by way of differential photometry analysis. Using free digital imaging software, participants analyse a series of…
A fast artificial neural network is developed for the prediction of cosmic ray transport in turbulent astrophysical magnetic fields. The setup is trained and tested on bespoke datasets that are constructed with the aid of test-particle…
Strong variations of any kind and causes within a stellar light curve may prohibit the detection of transits, particularly of faint or shallow transits caused by small planets passing in front of the stellar disk. The success of future…
The availability of a robust and efficient routine for calculating light curves of a finite source magnified due to bending its light by the gravitational field of an intervening binary lens is essential for determining the characteristics…
Classifying variable stars is crucial for advancing our understanding of stellar evolution and dynamics. As large-scale surveys generate increasing volumes of light curve data, the demand for automated and reliable classification techniques…
Following the widespread practice of exoplanetary transit simulations, various presumed components of an extrasolar system can be examined in numerically simulated transits, including exomoons, rings around planets, and the deformation of…
We present DOHA, a new algorithm for cotrending photometric light curves obtained by transiting exoplanet surveys. The algorithm employs a novel approach to the traditional "differential photometry" technique, by selecting the most suitable…
The upcoming TESS mission is expected to find thousands of transiting planets around bright stars, yet for three-quarters of the fields observed the temporal coverage will limit discoveries to planets with orbital periods below 13.7 days.…
The radial velocity technique is currently used to classify transiting objects. While capable of identifying grazing binary eclipses, this technique cannot reliably identify blends, a chance overlap of a faint background eclipsing binary…
The transit technique is responsible for the majority of exoplanet discoveries to date. Characterizing these planets involves careful modeling of their transit profiles. A common technique involves expressing the transit duration using a…
The method of direct imaging has detected many exoplanets and made important contribution to the field of planet formation. The standard method employs angular differential imaging (ADI) technique, and more ADI image frames could lead to…
Late-type stars are known to host numerous exoplanets, and their photometric variability, primarily caused by rotational modulation, provides a unique opportunity to study starspots. As exoplanets transit in front of their host stars, they…
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…
Terrain relative navigation can improve the precision of a spacecraft's position estimate by detecting global features that act as supplementary measurements to correct for drift in the inertial navigation system. This paper presents a…
We present a simple and powerful method for extracting transit signals associated with a known transiting planet from noisy light curves. Assuming the orbital period of the planet is known and the signal is periodic, we illustrate that…
Light curves produced by wide-field exoplanet transit surveys such as CoRoT, Kepler, and TESS are affected by sensor-wide systematic noise which is correlated both spatiotemporally and with other instrumental parameters such as photometric…
The Zone of Avoidance makes it difficult for astronomers to catalogue galaxies at low latitudes to our galactic plane due to high star densities and extinction. However, having a complete sky map of galaxies is important in a number of…
Convolutional neural networks (CNNs) are widely used for image recognition and text analysis, and have been suggested for application on one-dimensional data as a way to reduce the need for pre-processing steps. Pre-processing is an…