DeepAI AI Chat
Log In Sign Up

Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels

by   Shreshth A. Malik, et al.
University of Oxford

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 light curves, there lacks a robust approach for detecting single-transit events. However, volunteer-labelled transits recently collected by the Planet Hunters TESS (PHT) project now provide an unprecedented opportunity to investigate a data-driven approach to long-period exoplanet detection. In this work, we train a 1-D convolutional neural network to classify planetary transits using PHT volunteer scores as training data. We find using volunteer scores significantly improves performance over synthetic data, and enables the recovery of known planets at a precision and rate matching that of the volunteers. Importantly, the model also recovers transits found by volunteers but missed by current automated methods.


Automatic classification of eclipsing binary stars using deep learning methods

In the last couple of decades, tremendous progress has been achieved in ...

Deep Domain Adaptation for Detecting Bomb Craters in Aerial Images

The aftermath of air raids can still be seen for decades after the devas...

An application of Saddlepoint Approximation for period detection of stellar light observations

One of the main features of interest in analysing the light curves of st...

Real-time detection of anomalies in large-scale transient surveys

New time-domain surveys, such as the Rubin Observatory Legacy Survey of ...

Early detection of Crossfire attacks using deep learning

Crossfire attack is a recently proposed threat designed to disconnect wh...

Identifying Planetary Transit Candidates in TESS Full-Frame Image Light Curves via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite (TESS) mission measured light ...

Identifying microlensing events using neural networks

Current gravitational microlensing surveys are observing hundreds of mil...

Code Repositories


Identify long period exoplanets from TESS light curves using deep learning

view repo