OPTIMIZING ENTANGLEMENT TO ATTAIN QUANTUM LIMIT OF LONG-BASELINE IMAGING
Abstract
This grant focuses on fundamental research on one of the potentially-strongest use-cases of distributed entanglement---that of enhancing the performance of a network of sensors trying to work together solve one task---specifically in the context of long-baseline imaging. Our research objectives are- (1) to explore the use of distributed multi-site entanglement and local quantum operations and measurements (at individual telescope sites) to attain recently-quantified quantum limits of estimation accuracy of any predefined parameter in a passive imaging task involving incoherent broadband radiation by a given long-baseline telescope system in the traditionally unresolvable regime, and (2) to design an explicit system design that approaches the aforesaid quantum limit for problems of interest to the AF such as discriminating prior-known objects under dimly-lit conditions but using readily available technology, e.g., Spontaneous parametric downconversion (SPDC) -based photonic entanglement sources, Silicon vacancy (SiV) color-center based quantum memories, volumetric spatial mode sorters, optical fibers, switches, and shot-noise-limited single photon detectors. The highest impact is anticipated when the scene features of interest are highly sub-Rayleigh with respect to the baseline.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502210180
Entities
People
- Saikat Guha
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Arizona