Pre-merger sky localization of gravitational waves from binary neutron star mergers using deep learning

Abstract

The simultaneous observation of gravitational waves (GW) and prompt electromagnetic counterparts from the merger of two neutron stars can help reveal the properties of extreme matter and gravity during and immediately after the final plunge. Rapid sky localization of these sources is crucial to facilitate such multi-messenger observations. Since GWs from binary neutron star (BNS) mergers can spend up to 10-15 mins in the frequency bands of the detectors at design sensitivity, early warning alerts and pre-merger sky localization can be achieved for sufficiently bright sources, as demonstrated in recent studies. In this work, we present pre-merger BNS sky localization results using CBC-SkyNet, a deep learning model capable of inferring sky location posterior distributions of GW sources at orders of magnitude faster speeds than standard Markov Chain Monte Carlo methods. We test our model's performance on a catalog of simulated injections from Sachdev et al. (2020), recovered at 0-60 secs before merger, and obtain comparable sky localization areas to the rapid localization tool BAYESTAR. These results show the feasibility of our model for rapid pre-merger sky localization and the possibility of follow-up observations for precursor emissions from BNS mergers.

7 pages, 5 figures

References in corpus (13)

• Advanced Virgo: a 2nd generation interferometric gravitational wave detector
• Multi-messenger Observations of a Binary Neutron Star Merger
• Gravitational Waves and Gamma-rays from a Binary Neutron Star Merger: GW170817 and GRB 170817A
• Advanced LIGO
• Observation of gravitational waves from two neutron star-black hole coalescences
• The Electromagnetic Counterpart of the Binary Neutron Star Merger LIGO/VIRGO GW170817. III. Optical and UV Spectra of a Blue Kilonova From Fast Polar Ejecta
• On r-process nucleosynthesis from matter ejected in binary neutron starmergers
• The MBTA Pipeline for Detecting Compact Binary Coalescences in the Third LIGO-Virgo Observing Run
• An early warning system for electromagnetic follow-up of gravitational-wave events
• First demonstration of early warning gravitational wave alerts
• Gravitational-wave Merger Forecasting: Scenarios for the early detection and localization of compact-binary mergers with ground based observatories
• Early Warnings of Binary Neutron Star Coalescence using the SPIIR Search
• The Gravitational-wave Optical Transient Observer (GOTO)

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• Prompt sky localization of compact binary sources using a meshfree approximation
• Eccentricity enables the earliest warning and localization of gravitational waves with ground-based detectors
• Reconstruction of binary black hole harmonics in LIGO using deep learning
• Next-generation global gravitational-wave detector network: Impact of detector orientation on compact binary coalescence and stochastic gravitational-wave background searches
• Novel Deep Learning Approach to Detecting Binary Black Hole Mergers
• Sky localization of gravitational waves from eccentric binaries
• Flexible Gravitational-Wave Parameter Estimation with Transformers
• Binary Black Hole Parameter Estimation with Hybrid CNN-Transformer Neural Networks