This Project Grant award of $189,022 from the National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049, Mathematical and Physical Sciences) will fund an interdisciplinary team at the University of Massachusetts Dartmouth to develop advanced machine learning techniques for modeling gravitational waves from complex binary black hole systems. The project, titled "Collaborative Research: CDS & E: Data-Driven Discovery of Neural ODE Dynamics, Astrophysical Models, and Orbits (Neural ODE Dynamo)", aims to incorporate the effects of astrophysical environments, such as dark matter halos and accretion disks, into gravitational waveform models. The resulting models and machine learning methods will enable researchers to better study powerful collisions of binary black holes in extreme environments. The award also includes public outreach and the training of diverse students in science, technology, engineering, and math (STEM) fields. The project period runs from August 15, 2024 to July 31, 2027.
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