MO4.R1.2

Quantum Illumination Advantage for Classification Among an Arbitrary Library of Targets

Ali Cox, University of Arizona, United States; Quntao Zhuang, University of Southern California, United States; Jeffrey Shapiro, Massachusetts Institute of Technology, United States; Saikat Guha, University of Arizona, United States

Session:
Quantum Information 2

Track:
6: Quantum Information and Coding Theory

Location:
Ballroom II & III

Presentation Time:
Mon, 8 Jul, 16:45 - 17:05

Session Chair:
Christoph Hirche, University of Hannover
Abstract
THIS PAPER IS ELIGIBLE FOR THE STUDENT PAPER AWARD. Quantum illumination (QI) is the task of querying a scene using a transmitter probe whose quantum state is entangled with a reference beam retained in ideal storage, followed by optimally detecting the target-returned light together with the stored reference, to make decisions on characteristics of targets at stand-off range, at precision that exceeds what is achievable with a classical transmitter of the same brightness and otherwise identical conditions. Using tools from perturbation theory, we show that in the limit of low transmitter brightness, high loss, and high thermal background, there is a factor of four improvement in the Chernoff exponent of the error probability of discriminating any number of apriori-known reflective targets when using a Gaussian-state entangled QI probe, over using classical coherent-state illumination (CI). While this advantage was known for detecting the presence or absence of a target, it had not been proven for the generalized task of discriminating between arbitrary target libraries. In proving our result, we derive simple general analytic expressions for the lowest-order asymptotic expansions of the quantum Chernoff exponents for QI and CI in terms of the signal brightness, loss, thermal noise, and the modal expansion coefficients of the target-reflected light's radiant exitance profiles when separated by a spatial mode sorter after entering the entrance pupil of the receiver's aperture.
Resources