Advances inMachine and Deep Learning for Modeling and Real-Time Detection of Multi-messenger Sources

E. A. Huerta, Zhizhen Zhao

Research output: Chapter in Book/Report/Conference proceedingChapter


We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Original languageEnglish (US)
Title of host publicationHandbook of Gravitational Wave Astronomy
Number of pages27
ISBN (Electronic)9789811643064
ISBN (Print)9789811643057
StatePublished - Jan 1 2022


  • Artificial intelligence
  • Big data
  • Deep learning
  • Electromagnetic surveys
  • Gravitational waves
  • High performance computing
  • Interpretable artificial intelligence
  • Multi-messenger astrophysics
  • Numerical relativity
  • Real-time inference

ASJC Scopus subject areas

  • General Physics and Astronomy


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