This award supports research in relativity and relativistic astrophysics and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. In the last five years, the LIGO-VIRGO collaboration has detected several gravitational wave signals from merging binary systems consisting of black holes and neutron stars. These observations are already yielding new insights into the assembly and evolution of stellar remnants in the Universe, which are currently limited by the low numbers of events. In this context, the award supports research that will push forward innovative methods to (a) understand and mitigate factors that limit the sensitivity of the searches, and (b) characterize the properties of the signals that are detected. This approach is complementary to hardware improvements that boost the sensitivity, and by helping to detect and characterize the faintest and most distant signals, will help maximize the scientific yield of the LIGO-VIRGO observations. The resultant rapid and robust understanding of the source properties will also help better guide subsequent observations. The program will also facilitate NSF’s long-term vision on expanding the gravitational wave community by developing broader expertise in analyzing the LIGO strain data, releasing more derived data products, engaging and involving local undergraduate and high school students in the research, and organizing a pedagogical workshop for the wider field.
The research plan has two components. The first aim is to characterize and better mitigate two systematics that have been proven to affect the noise background, and consequently affect the sensitivity of searches: very short time-scale glitches in the detector, which are known to be extremely localized in parameter space, and moderate to longer-term variations in the noise characteristics, which affect the precision on the recovered signal-to-noise ratios of events. These systematics have been previously identified, but with the expanded level of detail that would be achieved in this research, it is possible to develop simple measures to curb their impact that are natural extensions of existing methods (such as signal-quality vetos and re-weighted signal-to-noise ratios). The second aim is to improve existing parameter estimation pipelines to help rapidly and robustly infer the intrinsic and extrinsic properties of gravitational wave sources. The methods build on existing codes that exploit the frequency structure of the signals (i.e., the smooth behavior of their phase with frequency), and insights from the searches on how to insulate the detection process from localized instrumental artifacts, i.e., glitches.
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.
