Computing Transiting Exoplanet Parameters with 1D Convolutional Neural Networks

arXiv:2402.13673v1 Announce Type: cross
Abstract: The transit method allows the detection and characterization of planetary systems by analyzing stellar light curves. Convolutional neural networks appear to offer a viable solution for automating these analyses. In this research, two 1D convolutional neural network models, which work with simulated light curves in which transit-like signals were injected, are presented. One model operates on complete light curves and estimates the orbital period, and the other one operates on phase-folded light curves and estimates …

abstract arxiv astro-ph.ep astro-ph.im computing convolutional neural network convolutional neural networks cs.lg detection exoplanet light network networks neural network neural networks parameters research solution systems transit type work