A deep-learning search for technosignatures of 820 nearby stars

Abstract

The goal of the Search for Extraterrestrial Intelligence (SETI) is to quantify the prevalence of technological life beyond Earth via their "technosignatures". One theorized technosignature is narrowband Doppler drifting radio signals. The principal challenge in conducting SETI in the radio domain is developing a generalized technique to reject human radio frequency interference (RFI). Here, we present the most comprehensive deep-learning based technosignature search to date, returning 8 promising ETI signals of interest for re-observation as part of the Breakthrough Listen initiative. The search comprises 820 unique targets observed with the Robert C. Byrd Green Bank Telescope, totaling over 480, hr of on-sky data. We implement a novel beta-Convolutional Variational Autoencoder to identify technosignature candidates in a semi-unsupervised manner while keeping the false positive rate manageably low. This new approach presents itself as a leading solution in accelerating SETI and other transient research into the age of data-driven astronomy.

10 pages of main paper followed by 16 pages of methods; 17 figures total and 7 tables; published in Nature Astronomy

References in corpus (5)

• Practical Bayesian Optimization of Machine Learning Algorithms
• A Machine-Learning-Based Direction-of-Origin Filter for the Identification of Radio Frequency Interference in the Search for Technosignatures
• Narrow-Band Signal Localization for SETI on Noisy Synthetic Spectrogram Data
• Machine Vision and Deep Learning for Classification of Radio SETI Signals
• Commensal, Multi-user Observations with an Ethernet-based Jansky Very Large Array

Cited by in corpus (11)

• The Breakthrough Listen Search for Intelligent Life: Technosignature Search of 97 Nearby Galaxies
• A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz
• A Radio Technosignature Search of TRAPPIST-1 with the Allen Telescope Array
• On Detecting Interstellar Scintillation in Narrowband Radio SETI
• Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches
• A solution to continuous RFI in narrowband radio SETI with FAST: The MultiBeam Point-source Scanning strategy
• COSMIC's Large-Scale Search for Technosignatures during the VLA sky Survey: Survey Description and First Results
• A Simultaneous Dual-site Technosignature Search Using International LOFAR Stations
• A Deep Neural Network Based Reverse Radio Spectrogram Search Algorithm
• Multibeam SETI Observations toward Nearby M dwarfs with FAST
• Technosignature Searches with Real-time Alert Brokers