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arXiv:2503.22099 · PRX Quantum

Towards Robust Variational Quantum Simulation of Lindblad Dynamics via Stochastic Magnus Expansion

Jia-Cheng Huang, Hao-En Li, Yi-Cheng Wang, Guang-Ze Zhang, Jun Li, Han‐Shi Hu

Published Sep 16, 2025• 3 citations
arXivHTMLPDF

Abstract

In this paper, we introduce a novel and general framework for the variational quantum simulation of Lindblad equations. Building on the close relationship between the unraveled Lindblad dynamics, stochastic Magnus integrators, and variational quantum simulation, we propose a high-order scheme for solving the quantum state diffusion equation using exponential integrators. This formulation facilitates the simulation of wavefunction trajectories within the established framework of variational quantum algorithms for time evolution. Our algorithm significantly enhances robustness in two key aspects: the stability of the simulation with large time steps, and the reduction in the number of quantum trajectories required to accurately simulate the Lindblad dynamics in terms of the ensemble average. We demonstrate the effectiveness of our algorithm through numerical examples in both classical and quantum implementations, including the transverse-field Ising model (TFIM) with damping, the Fenna-Matthews-Olson (FMO) complex, and the radical pair model (RPM). The simulation accuracy can be systematically improved, and the algorithm remains reliable even in highly oscillatory regimes. These methods are expected to be applicable to a broader class of open quantum systems beyond the specific models considered in this study.

DOI
10.1103/yyln-q22s

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Quantum simulation of dynamics in open quantum systems is crucial but poses a significant challenge due to the non-Hermitian nature leading to nonunitary evolution and the limited quantum resources on current quantum computers. Here we introduce a variational hybrid quantum-classical algorithm designed for simulating the time evolution governed by the Lindblad master equation. Our approach involves on a stochastic unveiling of the density matrix, transforming the Lindblad equation into a wave function-based quantum state diffusion (QSD) method with the aim of reducing qubit requirements. We then apply variational quantum simulation (VQS) to efficiently capture the nonunitary evolution in QSD. We demonstrate our QSD-VQS algorithm by investigating the quantum dynamics in a two-level system subjected to an amplitude damping channel and a four-level transverse field Ising model within a dissipative environment including time-independent and periodic Hamiltonian cases. The results reveal its promising utility with upcoming hardware in the near future.
We investigate dynamical quantum phase transitions (DQPTs) in Markovian open quantum systems using a variational quantum simulation (VQS) algorithm based on quantum state diffusion (QSD). This approach reformulates the Lindblad master equation as an ensemble of pure-state trajectories, enabling efficient simulation of dissipative quantum dynamics with effectively reduced quantum resources. Focusing on the one-dimensional transverse-field Ising model (TFIM), we simulate quench dynamics under both local and global Lindblad dissipation. The QSD-VQS algorithm accurately captures the nonanalytic cusps in the Loschmidt rate function, and reveals their modulation by dissipation strength and system size. Notably, DQPTs are gradually suppressed under strong local dissipation, while they persist under strong global dissipation due to collective environmental effects. Benchmarking against exact Lindblad solutions confirms the high accuracy and scalability of our method.
Variational quantum algorithms have been proposed to solve static and dynamic problems of closed many-body quantum systems. Here we investigate variational quantum simulation of three general types of tasks-generalized time evolution with a non-Hermitian Hamiltonian, linear algebra problems, and open quantum system dynamics. The algorithm for generalized time evolution provides a unified framework for variational quantum simulation. In particular, we show its application in solving linear systems of equations and matrix-vector multiplications by converting these algebraic problems into generalized time evolution. Meanwhile, assuming a tensor product structure of the matrices, we also propose another variational approach for these two tasks by combining variational real and imaginary time evolution. Finally, we introduce variational quantum simulation for open system dynamics. We variationally implement the stochastic Schrödinger equation, which consists of dissipative evolution and stochastic jump processes. We numerically test the algorithm with a 6-qubit 2D transverse field Ising model under dissipation.
Simulating non-Markovian open quantum dynamics is crucial for understanding complex quantum systems, yet it poses significant challenges for standard quantum hardware. These challenges stem from the non-Hermitian nature of such dynamics, which results in nonunitary evolution, as well as constraints imposed by limited quantum resources. To address this, we propose a hybrid quantum-classical algorithm designed for simulating dissipative dynamics in systems coupled to non-Markovian environments. Our approach includes formulating a non-Markovian Stochastic Schrödinger equation with complex frequency modes (cNMSSE) where the non-Markovianity is characterized by the mode excitation. We then employ variational quantum simulation to capture the nonunitary evolution within the cNMSSE framework, leading to a substantial reduction in qubit requirements. To demonstrate our approach, we investigated dissiaptive dynamics in the spin-boson model (SBM) and excitation energy transfer processes in both a prototype dimer system and the biologically relevant Fenna-Matthews-Olson (FMO) complex.
The simulation of many-body open quantum systems is key to solving numerous outstanding problems in physics, chemistry, material science, and in the development of quantum technologies. Near-term quantum computers may bring considerable advantage for the efficient simulation of their static and dynamical properties, thanks to hybrid quantum-classical variational algorithms to approximate the dynamics of the density matrix describing the quantum state in terms of an ensemble average. Here, a variational quantum algorithm is developed to simulate the real-time evolution of the density matrix governed by the Lindblad master equation, under the assumption that the quantum state has a bounded entropy along the dynamics, entailing a low-rank representation of its density matrix. The algorithm encodes each pure state of the statistical mixture as a parametrized quantum circuit, and the associated probabilities as additional variational parameters stored classically, thereby requiring a significantly lower number of qubits than algorithms where the full density matrix is encoded in the quantum memory. Two variational ansatze are proposed, and their effectiveness is assessed in the simulation of the dynamics of a 2D dissipative transverse field Ising model. The results underscore the algorithm's efficiency in simulating the dynamics of open quantum systems in the low-rank regime with limited quantum resources on a near-term quantum device.