Amplified Quantum Dynamics and Enhanced Parameter Sensitivity via Coherent Feedback in Collective Atomic Spin Systems

TL;DR

This paper investigates how coherent feedback in collective atomic spin systems can amplify spin observables and improve quantum parameter estimation, potentially achieving Heisenberg-limited sensitivity without spin-squeezing.

Contribution

It introduces an effective model for large atomic spin systems with positive feedback, enhancing quantum metrology techniques without requiring spin-squeezing.

Findings

Amplified spin observable values via coherent feedback.

Potential to reach Heisenberg scaling in magnetometry.

Developed a Gaussian state-based quantum estimator with numerical validation.

Abstract

We consider the effective dynamics obtained by double-passing a far-detuned laser probe through a large atomic spin system. The net result of the atom-field interaction is a type of coherent positive feedback that amplifies the values of selected spin observables. An effective equation of motion for the atomic system is presented, and an approximate 2-parameter model of the dynamics is developed that should provide a viable approach to modeling even the extremely large spin systems, with N>>1 atoms, encountered under typical laboratory conditions. Combining the nonlinear dynamics that result from the positive feedback with continuous observation of the atomic spin offers an improvement in quantum parameter estimation. We explore the possibility of reaching the Heisenberg uncertainty scaling in atomic magnetometry without the need for any appreciable spin-squeezing by analyzing our system via the quantum Cramer-Rao inequality. Finally, we develop a realistic quantum parameter estimator for atomic magnetometry that is based on a two-parameter family of Gaussian states and investigate the performance of this estimator through numerical simulations. In doing so, we identify several issues, such as numerical convergence and the reduction of estimator bias, that must be addressed when incorporating our parameter estimation methods into an actual laboratory setting.