(PECASE) QUANTUM OPTIMIZATION WITH RYDBERG ATOMS
Abstract
Predicting the collective behavior of many interacting quantum particles poses a formidable challenge to the capabilities of classical computers. This difficulty suggests that certain computational problems with no efficient classical solution might become tractable if they can be encoded in a suitable quantum mechanical form. Notably, a wide range of hard -- and technologically relevant -- optimization problems can be mapped to the problem of minimizing the energy of a collection of spins with specified interactions. In the proposed work, we will control the interactions among laser-cooled atoms to realize physical encodings of two classes of optimization problems, known as (1) max-cut problems and (2) subset sum problems. Key to our approach will be the ability to controllably excite atoms to Rydberg states yielding interatomic interactions that extend over distances of several microns, large compared to the spatial resolution attainable in optically addressing and imaging. We will test several methods of energy minimization, including the theoretically well studied quantum approximate optimization algorithm and a novel approach harnessing Grover s search algorithm. A byproduct of our effort will be to yield efficient methods of preparing quantum states that are themselves resources for applications beyond computation. Notably, the ground states of the interacting spin models to be realized in our experiments include entangled quantum states with applications to enhancing precision sensing and time-keeping.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010059
Entities
People
- Monika Schleier-Smith
Organizations
- Air Force Office of Scientific Research
- Stanford University
- United States Air Force