Enabling real-time multi-messenger astrophysics discoveries with deep learning
arXiv:1911.11779 · doi:10.1038/s42254-019-0097-4
Abstract
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics.
Invited Expert Recommendation for Nature Reviews Physics. The art work produced by E. A. Huerta and Shawn Rosofsky for this article was used by Carl Conway to design the cover of the October 2019 issue of Nature Reviews Physics
References in corpus (20)
- GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral
- Large Magellanic Cloud Cepheid Standards Provide a 1% Foundation for the Determination of the Hubble Constant and Stronger Evidence for Physics Beyond LambdaCDM
- A gravitational-wave standard siren measurement of the Hubble constant
- The Electromagnetic Counterpart of the Binary Neutron Star Merger LIGO/VIRGO GW170817. II. UV, Optical, and Near-IR Light Curves and Comparison to Kilonova Models
- Light Curves of the Neutron Star Merger GW170817/SSS17a: Implications for R-Process Nucleosynthesis
- First measurement of the Hubble constant from a dark standard siren using the Dark Energy Survey galaxies and the LIGO/Virgo binary-black-hole merger GW170814
- Estimating the Contribution of Dynamical Ejecta in the Kilonova Associated with GW170817
- THC: a new high-order finite-difference high-resolution shock-capturing code for special-relativistic hydrodynamics
- Relativistic simulations of black hole-neutron star coalescence: the jet emerges
- Results from the Supernova Photometric Classification Challenge
- SkyNet: A modular nuclear reaction network library
- Three-Dimensional Supernova Explosion Simulations of 9-, 10-, 11-, 12-, and 13-M Stars
- Complete waveform model for compact binaries on eccentric orbits
- Optical Follow-up of Gravitational-wave Events with Las Cumbres Observatory
- How Many Kilonovae Can Be Found in Past, Present, and Future Survey Datasets?
- Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders
- Mary, a pipeline to aid discovery of optical transients
- BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery
- Astro 2020 Science White Paper: Joint Gravitational Wave and Electromagnetic Astronomy with LIGO and LSST in the 2020's
- Data Access for LIGO on the OSG