Quantum Enhanced Classical Sensor Networks

TL;DR

This paper analyzes the limits of quantum-enhanced classical sensor networks, deriving optimal error bounds and showing how noise impacts the potential quantum sensing gains.

Contribution

It derives the optimal mean squared error bounds and demonstrates the effect of noise on the quantum sensing advantage in classical sensor networks.

Findings

Without noise, error decays as 1/(K N_e^2 r)

With noise, error decays as 1/K, negating quantum gains

Quantum enhancement benefits are nullified by classical noise

Abstract

The quantum enhanced classical sensor network consists of $K$ clusters of $N_e$ entangled quantum states that have been trialled $r$ times, each feeding into a classical estimation process. Previous literature has shown that each cluster can {ideally} achieve an estimation variance of $1/N_e^2r$ for sufficient $r$. We begin by deriving the optimal values for the minimum mean squared error of this quantum enhanced classical system. We then show that if noise is \emph{absent} in the classical estimation process, the mean estimation error will decay like $\Omega(1/KN_e^2r)$. However, when noise is \emph{present} we find that the mean estimation error will decay like $\Omega(1/K)$, so that \emph{all} the sensing gains obtained from the individual quantum clusters will be lost.