Improving quantum parameter estimation by monitoring quantum trajectories

TL;DR

This paper introduces a theoretical framework for enhancing quantum parameter estimation by monitoring quantum trajectories, which helps mitigate noise effects and can recover Heisenberg scaling in certain cases.

Contribution

The authors develop a general approach for improving quantum parameter estimation through quantum trajectory monitoring, linking it to quantum error correction and demonstrating practical advantages.

Findings

Avoids exponential loss of precision over time

Can recover Heisenberg scaling in specific scenarios

Applicable to estimating spin-1/2 parameters under decoherence

Abstract

Quantum-enhanced parameter estimation has widespread applications in many fields. An important issue is to protect the estimation precision against the noise-induced decoherence. Here we develop a general theoretical framework for improving the precision for estimating an arbitrary parameter by monitoring the noise-induced quantum trajectorie (MQT) and establish its connections to the purification-based approach to quantum parameter estimation. MQT can be achieved in two ways: (i) Any quantum trajectories can be monitored by directly monitoring the environment, which is experimentally challenging for realistic noises; (ii) Certain quantum trajectories can also be monitored by frequently measuring the quantum probe alone via ancilla-assisted encoding and error detection. This establishes an interesting connection between MQT and the full quantum error correction protocol. Application of MQT to estimate the level splitting and decoherence rate of a spin-1/2 under typical decoherence channels demonstrate that it can avoid the long-time exponential loss of the estimation precision and, in special cases, recover the Heisenberg scaling.