# A Variance Reduction Technique for the Stochastic Liouville-von Neuman Equation

## TL;DR

This paper introduces a variance reduction sampling strategy for the stochastic Liouville-von Neumann equation, significantly improving simulation efficiency for quantum systems with dissipative interactions.

## Contribution

It proposes a novel sampling method that reduces non-unitary terms via convex optimization, enhancing scalability with dissipative interaction strength.

## Key findings

- Improved scaling with dissipation strength
- Reduced variance in stochastic simulations
- Enhanced efficiency over previous methods

## Abstract

The Stochastic Liouville-von Neumann equation provides an exact numerical simulation strategy for quantum systems interacting with Gaussian reservoirs [J.T. Stockburger & H. Grabert, PRL 88, 170407 (2002)]. Its scaling with the extension of the time interval covered has recently improved dramatically through time-domain projection techniques [J.T. Stockburger, EPL 115, 40010 (2016)]. Here we present a sampling strategy which results in a significantly improved scaling with the strength of the dissipative interaction, based on reducing the non-unitary terms in sample propagation through convex optimization techniques.