This Project Grant award, totaling $189,022, was provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) Federal Grant Program. The funding supports an interdisciplinary research team to use advanced machine learning techniques to develop new models for studying the complex gravitational wave signals from binary black hole systems in extreme astrophysical environments. The team plans to build on their previous work on gravitational waveform...
This $210,000 Project Grant awarded by the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) supports research by the University of Virginia to advance gravitational wave physics and astrophysics. The key goals are to: (i) Compute persistent gravitational wave signals from binary black hole mergers using new conservation law models, and assess their detection prospects. (ii) Improve modeling of the gravitational wave memory effect to better understand its...
This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) provides $149,703.00 to the University of Rhode Island to advance gravitational wave inference and waveform modeling using deep learning techniques. The key objectives are to develop neural network-based posterior estimation tools and efficient waveform surrogate models to enhance the speed and accuracy of gravitational wave data analysis. This work aims to substantially reduce...
This $294,769 Project Grant award from the National Science Foundation's (NSF) Division of Physics, under the Mathematical and Physical Sciences program (CFDA 47.049), supports research at the California Institute of Technology (Caltech) to enhance the discovery potential of gravitational wave observations from merging black holes. The key objectives of this 3-year award are to develop robust techniques for extracting measurements of black hole spin-precession and orbital eccentricity from...
This Project Grant award for $150,000 by the National Science Foundation (NSF) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) supports research in gravitational wave astrophysics. The research aims to solve Einstein's equations numerically using simulations run on NSF-funded supercomputers to study the inspiral and merger of binary neutron star systems and the associated gravitational waves. The results will increase understanding of gravitational wave...
This National Science Foundation Project Grant award provides $180,000.00 to the University of Massachusetts Dartmouth from July 1, 2023 to June 30, 2026 under the Mathematical and Physical Sciences program (CFDA 47.049). The primary goal of the project is to develop novel numerical simulations and data-driven models to predict gravitational wave signals from mergers of black holes and neutron stars. This research will test Einstein's general relativity under extreme conditions and help maximize...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support and extend ongoing research at the Massachusetts Institute of Technology (MIT) on the dynamics of binary black hole systems and the characterization of the gravitational waves they produce. The $360,000 award, spanning August 1, 2024 to July 31, 2027, will fund projects to improve the understanding of how black holes in binary systems interact and how...
This federal Project Grant award, issued by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, will enhance existing search strategies and analysis capabilities for discovering and characterizing the coalescence of compact binary systems, such as black holes and neutron stars. The $200,000 award, with a performance period from August 1, 2024 to July 31, 2027, will fund four key activities: (i) extending multi-messenger Bayesian inference...
This three-year Project Grant from the National Science Foundation's Mathematical and Physical Sciences program provides $360,000 to Brigham Young University to develop computational modeling capabilities for gravitational wave astronomy. Specifically, the university will expand its Dendrogram computational framework to calculate gravitational waveforms from binary neutron star inspirals and mergers with sufficient accuracy for inclusion in waveform catalogs. It will also study binary black hole...
This National Science Foundation (NSF) Division of Astronomical Sciences Project Grant, CFDA #47.049 Mathematical and Physical Sciences, is funding Drexel University to develop cutting-edge artificial intelligence (AI) systems that will optimize the search for electromagnetic signals accompanying gravitational wave events detected by advanced detectors. The $341,248 project, running from September 1, 2023 to August 31, 2026, aims to create an AI agent that can adaptively learn to make the best...