CAREER: Building the U.S. Workforce for Multimessenger Astrophysics via Foundational AI and Next-Generation GW Observatories

The first direct detection of gravitational waves, resulting from the merger of two black holes, in 2015 opened a whole new view on the Universe. While almost 400 gravitational-wave events have been reported since that time, gaps in the technological ability of the gravitational-wave detectors have been exposed. This project will launch an integrated research and workforce program that will establish a framework that bolsters the next generation of gravitational-wave detectors to be more sensitive to signals that are not currently accessible. Foundational artificial intelligence (AI) models will also be developed to identify signatures of intermediate-mass black holes that have been missed in archived data by more traditional analysis methods. The workforce development program, in partnerships with historical black colleges and universities (HBCUs), will create mentored research pathways in gravitational-wave science, AI, and next-generation detector technologies for undergraduate and graduate students. Two annual workshops on AI and gravitational waves will also be offered. Public outreach activities entail developing graphics and other products to make the complex science of black holes and gravitational waves accessible to the general public. Since LIGO’s landmark discovery in 2015, gravitational-wave (GW) astronomy has delivered two major surprises: the detection of black holes in—and well above—the expected supernova mass gap (60–120 M_Sun), and only a single joint GW–electromagnetic event, highlighting key limitations in current multi-messenger capabilities. The central scientific goals of this project are to uncover the astrophysical origins of the intermediate-mass black holes (IMBHs) that are emerging in the GW data, and to enhance the multi-messenger landscape of binary neutron star (BNS) mergers. The team will pursue three innovations: (i) establish a framework for multiband, multi-messenger astrophysics targeting IMBH and BNS sources in the 0.1–10 Hz “missing band,” inaccessible to current earth-based GW detectors such as LIGO and planned space-based LISA mission; (ii) develop foundational AI models on public LIGO data that are tailored specifically for identifying astrophysical signatures from IMBHs that have evaded traditional data-analysis approaches; and (iii) launch a workforce initiative that merges GW science, AI, and cutting-edge GW detector development into modular coursework and annual community workshops for students across R1 and R2 institutions and HBCUs. This workforce development will be an integration of the existing Fisk-Vanderbilt Bridge Program and the LIGO Fellows Program. 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. NSF Award ID: 2544531 | Program: 01002930DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Karan Jani | Institution: Vanderbilt University, NASHVILLE, TN | Award Amount: $536,597 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2544531 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2544531.html