Computationally Tractable Inference for Multi-Messenger Astrophysics

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Multi-messenger astrophysics leverages multiple modalities of observations, such as gravitational waves, light, neutrinos, and cosmic rays, to observe astrophysical events and objects. Two specific issues arising in multi-messenger astrophysics motivate much of this research project: detecting cross-correlation between gravitational waves and electromagnetic sky maps and constraining the neutron star equation of state. Addressing these issues formally with the data produced from multi-messenger observations presents challenges that require the development of novel statistical and computational methodology. This project aims to develop improved (1) statistical techniques for detecting cross-correlation between a conjectured gravitational wave background and the cosmic microwave background sky map and (2) Bayesian algorithms for analysis of gravitational wave signatures in binary neutron star mergers. The research will provide interdisciplinary opportunities for professional development of the next generation of statisticians and astronomers. The project will focus on developing methods for performing goodness-of-fit tests for multidimensional parametric models characterized by high computational complexity, paying particular attention to identifying the sources of mismodelling. Another focus will be developing methods for convergence analysis of Markov chain Monte Carlo methods in both low-dimensional (fixed sizes of state space and observed data) and in high-dimensional (size of observed data and state space increase simultaneously) regimes. Convergence analysis in these regimes should be viewed as complementary; without such convergence analyses, practitioners have limited ability to assess the reliability of their MCMC experiments and hence any subsequent inference. The new methods will be made publicly available through open-source software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.