Distributed quantum sensing enhanced by continuous-variable error correction

TL;DR

This paper demonstrates that continuous-variable error correction codes can improve the robustness and scalability of distributed quantum sensing protocols, enabling simultaneous quadrature measurements and restoring Heisenberg scaling under realistic noise conditions.

Contribution

It introduces a novel distributed sensing protocol utilizing continuous-variable error correction to enhance noise resilience and enable simultaneous quadrature sensing.

Findings

Error correction codes restore Heisenberg scaling under noise.

Protocol allows simultaneous measurement of both quadratures.

Enhanced robustness against loss and noise in quantum sensing.

Abstract

A distributed sensing protocol uses a network of local sensing nodes to estimate a global feature of the network, such as a weighted average of locally detectable parameters. In the noiseless case, continuous-variable multipartite entanglement shared by the nodes can improve the precision of parameter estimation relative to the precision attainable by a network without shared entanglement; for an entangled protocol, the root-mean-square estimation error scales like $1/M$ with the number $M$ of sensing nodes, the so-called Heisenberg scaling, while for protocols without entanglement, the error scales like $1/\sqrt{M}$. However, in the presence of loss and other noise sources, although multipartite entanglement still has some advantages for sensing displacements and phases, the scaling of the precision with $M$ is less favorable. In this paper, we show that using continuous-variable error correction codes can enhance the robustness of sensing protocols against imperfections and reinstate Heisenberg scaling up to moderate values of $M$. Furthermore, while previous distributed sensing protocols could measure only a single quadrature, we construct a protocol in which both quadratures can be sensed simultaneously. Our work demonstrates the value of continuous-variable error correction codes in realistic sensing scenarios.