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Research Spending & Results

Award Detail

Doing Business As Name:University of Washington
  • Joey Key
  • (425) 352-5497
Award Date:12/13/2019
Estimated Total Award Amount: $ 399,997
Funds Obligated to Date: $ 79,999
  • FY 2020=$79,999
Start Date:12/15/2019
End Date:11/30/2024
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.049
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CAREER: Gravitational Wave Discovery Space
Federal Award ID Number:1944412
DUNS ID:605799469
Parent DUNS ID:042803536
Program Officer:
  • Pedro Marronetti
  • (703) 292-7372

Awardee Location

Street:4333 Brooklyn Ave NE
Awardee Cong. District:07

Primary Place of Performance

Organization Name:University of Washington Bothell
Street:11136 NE 180th St
Cong. District:01

Abstract at Time of Award

We have learned from the history of astronomy to expect the unexpected when opening a new window with which to observe our universe. In order to maximize the discovery potential for the new field of gravitational wave astronomy, we need to make progress in our data analysis methods to identify and characterize gravitational wave signals. This project supports research in critical areas of gravitational wave data analysis for the LIGO, NANOGrav, and LISA collaborations while training undergraduate students who are typically underrepresented in the fields of physics and astronomy in gravitational wave astronomy research methods and science communication skills. The research objectives for this project are to develop Bayesian data analysis methods for astrophysical searches for LIGO, NANOGrav, and LISA. By coordinating and combining analyses across the full gravitational wave spectrum, ranging over 12 decades in frequency, this project will accomplish science beyond what could be done in any individual band alone. LIGO: development of a Bayesian search for gravitational wave signals from cosmic string cusps, detector characterization and instrument noise studies including optimization of data analysis for the full network of ground based gravitational wave observatories, and a comprehensive data analysis method for detecting and characterizing unexpected gravitational wave signals. NANOGrav: apply Bayesian analysis methods developed for LIGO data analysis to NANOGrav searches including noise and signal modeling. LISA: application of Bayesian analysis methods to optimize the science capabilities and discovery potential for the LISA mission including Extreme Mass Ratio Inspiral (EMRI) signals. The PI provides opportunities for students at a primarily undergraduate institution who are traditionally underrepresented in physics and astronomy to engage in forefront scientific research and outreach programs. The breadth of potential research projects for undergraduate students is critical for the educational experience, with interdisciplinary research teams supported through peer mentoring and student leadership roles. Student educational experiences will be assessed to inform and evaluate the undergraduate research and outreach experiences. 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.

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