Multimodal Analysis of Gravitational Wave Signals and Gamma-Ray Bursts from Binary Neutron Star Mergers

Elena Cuoco,Barbara Patricelli,Filip Morawski,Alberto Iess

doi:10.3390/universe7110394

Abstract

A major boost in the understanding of the universe was given by the revelation of the first coalescence event of two neutron stars (GW170817) and the observation of the same event across the entire electromagnetic spectrum. With third-generation gravitational wave detectors and the new astronomical facilities, we expect many multi-messenger events of the same type. We anticipate the need to analyse the data provided to us by such events not only to fulfil the requirements of real-time analysis, but also in order to decipher the event in its entirety through the information emitted in the different messengers using machine learning. We propose a change in the paradigm in the way we do multi-messenger astronomy, simultaneously using the complete information generated by violent phenomena in the Universe. What we propose is the application of a multimodal machine learning approach to characterize these events.

Highlights

The detection of gravitational waves (GWs) from the inspiral phase and coalescence of a pair of neutron stars (NS) on 17 August 2017 [1] and the following observations of the event in its electromagnetic (EM) counterparts marked the beginning of multi-messenger astronomy with GWs.For the first time, we observed the coalescence of two NSs through GWs and EM radiation across the entire electromagnetic spectrum, thanks to the participation of more than 70 astronomical observatories to the EM follow-up campaign
We propose a change in the paradigm in the way we do multi-messenger astronomy, simultaneously using the complete information generated by violent phenomena in the Universe
What we propose is the application of a multimodal machine learning approach to characterize these events

Summary

Introduction

The detection of gravitational waves (GWs) from the inspiral phase and coalescence of a pair of neutron stars (NS) on 17 August 2017 [1] and the following observations of the event in its electromagnetic (EM) counterparts (see [2] and references therein) marked the beginning of multi-messenger astronomy with GWs. Multi-messenger astronomy opens up new scenarios for the observation of the Universe and new perspectives for the investigations of astronomical objects, and new challenges for the way of extracting all information that these astrophysical events bring with them. Multimodal machine learning MMML analysis is efficiently applied in many fields of data analysis for the more inclusive interpretation of events where several modalities are concurrent, such as in a video with audio; images with captions; or images, text, and sound [13] To our knowledge, these techniques have never been applied in the interpretation of astrophysical data, where signals of different nature can be almost simultaneous. Even the ability to caption GW data with an associated GRB event could help in quickly identifying source parameters

From Multi-Messenger Observations to Multimodal Analysis

Application to Astrophysical Sources

Outlook and Perspective