Public Abstract

DE-SC0010008: Research in Theoretical High Energy Physics

Award Status: Active

Institution: Rutgers, The State University of New Jersey, New Brunswick, NJ
UEI: M1LVPE5GLSD9
DUNS: 001912864

Most Recent Award Date: 08/27/2025
Number of Support Periods: 13
PM: Kilgore, William

Current Budget Period: 04/01/2025 - 03/31/2026
Current Project Period: 04/01/2025 - 03/31/2028
PI: Moore, Gregory

Supplement Budget Period: N/A

Public Abstract

Rutgers University Research in Theoretical High Energy Physics Gregory Moore (PI), Matthew Buckley (Co-PI), Eric Gawiser (Co-PI), Saurabh Jha (Co-PI), David Shih (Co-PI) Project Summary/Abstract: This award supports work on fundamental physics at the energy and cosmic frontiers. Research topics in String theory and Supersymmetric Field theories and their underlying mathematical structures as well their relation to Physical Mathematics will be investigated. New ideas for investigating the origin and identity of Dark Matter as well as for measuring its local distribution within the galaxy through gravitational e_ects will be pursued. Novel ideas for exploiting the discovery potential of the Large Hadron Collider to uncover evidence of New Physics will be investigated and deployed. Machine Learning techniques applied to the investigation of Funda- mental Physics will be developed. Research topics in dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) include studies to improve statistics and reduce systematic errors in the large-scale structure and type-Ia supernova analyses, following key projects identified in the LSST Dark Energy Science Collaboration science roadmap.

Rutgers University Research in Theoretical High Energy Physics

Gregory Moore (PI), Matthew Buckley (Co-PI), Eric Gawiser (Co-PI), Saurabh Jha (Co-PI), David Shih (Co-PI)

Project Summary/Abstract:

This award supports work on fundamental physics at the energy and cosmic frontiers. Research topics in String theory and Supersymmetric Field theories and their underlying mathematical structures as well their relation to Physical Mathematics will be investigated. New ideas for investigating the origin and identity of Dark Matter as well as for measuring its local distribution within the galaxy through gravitational e_ects will be pursued. Novel ideas for exploiting the discovery potential of the Large Hadron Collider to uncover evidence of New Physics will be investigated and deployed. Machine Learning techniques applied to the investigation of Funda- mental Physics will be developed. Research topics in dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) include studies to improve statistics and reduce systematic errors in the large-scale structure and type-Ia supernova analyses, following key projects identified in the LSST Dark Energy Science Collaboration science roadmap.