Unravelling the noise: the discrimination of wave function collapse models under time-continuous measurements

TL;DR

This paper investigates how continuous environmental monitoring can distinguish wave function collapse models from environmental noise by analyzing quantum Fisher information and measurement efficiencies.

Contribution

It introduces a method to estimate collapse-induced diffusion parameters using continuous measurements, considering realistic measurement efficiencies and identifying optimal measurement strategies.

Findings

Quantum Fisher information quantifies the advantage of monitoring.

Optimal measurements depend on limiting cases.

Performance assessed under realistic measurement efficiencies.

Abstract

Inspired by the notion that environmental noise is in principle observable, whilst fundamental noise due to spontaneous localisation would not be, we study the estimation of the diffusion parameter induced by wave function collapse models under continuous monitoring of the environment. We take into account finite measurement efficiencies and, in order to quantify the advantage granted by monitoring, we analyse the quantum Fisher information associated with such a diffusion parameter, identify optimal measurements in limiting cases, and assess the performance of such measurements in more realistic conditions.