Compressively characterizing high-dimensional entangled states with complementary, random filtering
Abstract
The resources needed to conventionally characterize a quantum system are overwhelmingly large for high- dimensional systems. This obstacle may be overcome by abandoning traditional cornerstones of quantum measurement, such as general quantum states, strong projective measurement, and assumption-free characterization. Following this reasoning, we demonstrate an efficient technique for characterizing high-dimensional, spatial entanglement with one set of measurements. We recover sharp distributions with local, random filtering of the same ensemble in momentum followed by position---something the uncertainty principle forbids for projective measurements. Exploiting the expectation that entangled signals are highly correlated, we use fewer than 5,000 measurements to characterize a 65, 536-dimensional state. Finally, we use entropic inequalities to witness entanglement without a density matrix. Our method represents the sea change unfolding in quantum measurement where methods influenced by the information theory and signal-processing communities replace unscalable, brute-force techniques---a progression previously followed by classical sensing.
Cite
@article{arxiv.1605.04792,
title = {Compressively characterizing high-dimensional entangled states with complementary, random filtering},
author = {Gregory A. Howland and Samuel H. Knarr and James Schneeloch and Daniel J. Lum and John C. Howell},
journal= {arXiv preprint arXiv:1605.04792},
year = {2016}
}
Comments
13 pages, 7 figures