Quantum Enhanced Machine Learning And Machine Learning Enhanced Quantum Physics
Abstract
This research will build on a recently-introduced Bayesian framework for the statistical construction and manipulation of quantum many-body systems, developed with previous support from AFOSR. It will capitalize on the breadth of its impact potential by constructing a two-way bridge between the domains of machine learning and quantum many-body systems, with rigorous foundations in both fields. Straddling this bridge will be the powerful Gaussian Process state model, and this project will exploit its dual perspective as a lens in both machine learning and quantum many-body theory contexts, enabling a transformative impact on both these broad areas. This cross-disciplinary endeavor will target applications ranging from first principles modelling of defective materials, to classical tasks in generative modelling and jammed non-equilibrium networks.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 20, 2023
- Source ID
- FA86552217011
Entities
People
- George H Booth
Organizations
- Air Force Office of Scientific Research
- United States Air Force