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

• URL: http://arxiv.org/abs/2309.06665v1
• Date: Wed, 13 Sep 2023 01:57:27 GMT
• Title: Hybrid algorithm simulating non-equilibrium steady states of an open quantum system
• Authors: Hongyi Zhou, Rui Mao, Xiaoming Sun
• Abstract summary: 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. 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.
• Score: 10.752869788647802
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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