Measuring Functions with Quantum Sensor Networks

Presenting Author: Jacob Bringewatt, University of Maryland Joint Quantum Institute
Contributing Author(s): Timothy Qian, Igor Boettcher, Przemyslaw Bienias, Pradeep Niroula, Alexey V. Gorshkov

We study the problem of optimally measuring analytic functions of field amplitudes with quantum sensor networks with a focus on the effects of interdependence between the various quantities involved in the measurement scheme. We consider such interdependence both at the level of correlations between field amplitudes [Qian et. al., Phys. Rev. A. 103, L030601 (2021)] and at the level of correlations between the functions of these field amplitudes we seek to measure [Bringewatt et. al., Phys. Rev. Res. 3, 033011 (2021)]. In either case, correlations enable more freedom in choosing measurement protocols relative to simpler formulations of the problem. Taking advantage of this interdependence involves common mathematical themes related to the optimal choice of a basis for the problem at hand and reveals connections between ultimate information theoretic bounds and their saturating protocols via linear programming. In addition, our work greatly expands the scope of such protocols to practically relevant settings.

Read this article online: https://doi.org/10.1103/PhysRevA.103.L030601, https://doi.org/10.1103/PhysRevResearch.3.033011

(Session 4 : Friday from 10:30am-10:50am)


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