Collaborative Research: Frameworks: ML4GW, a machine learning ecosystem for gravitational — NSF Award to University of Minnesota-T
Since the first direct observation of gravitational waves in 2015, a new field of astronomy has fundamentally changed how the universe can be explored. A gravitational wave is a ripple in spacetime produced when two extremely dense objects, such as black holes or neutron stars, collide. The detectors that observe these
| Award title | Collaborative Research: Frameworks: ML4GW, a machine learning ecosystem for gravitational |
|---|---|
| Award ID | 2609004 |
| Awardee | University of Minnesota-Twin Cities |
| City | MINNEAPOLIS |
| State | MN |
| Amount obligated | $880,650 |
| Principal investigator | Ali Anwar |
| Program | NAIRR-Nat AI Research Resource, Software Institutes, PHYSICS AT THE INFO FRONTIER |
| Start date | 10/01/2026 |
| Abstract | Since the first direct observation of gravitational waves in 2015, a new field of astronomy has fundamentally changed how the universe can be explored. A gravitational wave is a ripple in spacetime produced when two extremely dense objects, such as black holes or neutron stars, collide. The detectors that observe these signals now record hundreds of such events per year, and the rate is expected to grow to several events per day within the next few years. Sifting through this flood of data to fi |
| Source | NSF Awards |
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