Hybrid algorithm simulating non-equilibrium steady states of an open quantum system

TL;DR

This paper introduces a resource-efficient variational quantum algorithm for simulating non-equilibrium steady states in open quantum systems, utilizing operator-sum representation and random measurement techniques to reduce qubit requirements and enable gradient-based optimization.

Contribution

The novel algorithm simulates steady states more efficiently by reducing qubit needs and proving a parameter shift rule, advancing quantum simulation methods for open systems.

Findings

Accurate simulations of dissipative quantum models.

Reduced qubit resources by half compared to prior methods.

Effective gradient-based parameter updates enabled.

Abstract

Non-equilibrium steady states are a focal point of research in the study of open quantum systems. Previous variational algorithms for searching these steady states have suffered from resource-intensive implementations due to vectorization or purification of the system density matrix, requiring large qubit resources and long-range coupling. In this work, we present a novel variational quantum algorithm that efficiently searches for non-equilibrium steady states by simulating the operator-sum form of the Lindblad equation. By introducing the technique of random measurement, we are able to estimate the nonlinear cost function while reducing the required qubit resources by half compared to previous methods. Additionally, we prove the existence of the parameter shift rule in our variational algorithm, enabling efficient updates of circuit parameters using gradient-based classical algorithms. To demonstrate the performance of our algorithm, we conduct simulations for dissipative quantum transverse Ising and Heisenberg models, achieving highly accurate results. Our approach offers a promising solution for effectively addressing non-equilibrium steady state problems while overcoming computational limitations and implementation challenges.