Scalable quantum field simulations of conditioned systems

TL;DR

This paper introduces a scalable stochastic simulation method for conditional quantum master equations, enabling efficient first-principles modeling of multimode bosonic fields under continuous measurement and feedback control.

Contribution

The authors develop a scalable simulation technique for quantum-field systems under measurement, significantly improving computational efficiency over previous methods.

Findings

Achieved a 53-fold speed increase in simulating feedback cooling of a single trapped particle.

Successfully simulated feedback cooling of a 32-mode quantum field, previously impractical.

Demonstrated the method's applicability to complex multimode quantum systems.

Abstract

We demonstrate a technique for performing stochastic simulations of conditional master equations. The method is scalable for many quantum-field problems and therefore allows first-principles simulations of multimode bosonic fields undergoing continuous measurement, such as those controlled by measurement-based feedback. As examples, we demonstrate a 53-fold speed increase for the simulation of the feedback cooling of a single trapped particle, and the feedback cooling of a quantum field with 32 modes, which would be impractical using previous brute force methods.