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    Lindbladian Simulation with Logarithmic Precision Scaling via Two Ancillas

    Wenjun Yu1,*, Xiaogang Li2,3,*, Qi Zhao1,†, and Xiao Yuan2,3,‡

    • 1QICI Quantum Information and Computation Initiative, School of Computing and Data Science, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
    • 2Center on Frontiers of Computing Studies, Peking University, Beijing 100871, China
    • 3School of Computer Science, Peking University, Beijing 100871, China

    • *These authors contributed equally to this work.
    • †Contact author: zhaoqi@cs.hku.hk
    • ‡Contact author: xiaoyuan@pku.edu.cn

    Phys. Rev. Lett. 135, 160602 – Published 15 October, 2025

    DOI: https://doi.org/10.1103/2cx4-b82c

    Abstract

    Quantum computers promise efficient simulation of Lindbladian dynamics in open quantum systems, with broad applications in quantum chemistry, quantum error correction, and quantum state preparation. However, simulating open systems is more challenging than simulating closed systems, inherently requiring nonunitary operations. Existing approaches face unique challenges: methods with higher theoretical efficiency demand numerous ancillae and multiqubit operations that are experimentally challenging, while more experimentally feasible methods incur deep quantum circuits to control simulation errors. Here, we introduce a powerful framework, the linear combinations of superoperators, to systematically compensate for simulation errors and overcome these challenges. Utilizing simple gates and experimentally accessible Trotter decompositions, our approach achieves an exponential reduction in circuit depth with respect to the simulation precision, if only two ancillas are allowed to be used. We further extend the approach to time-dependent Lindbladians, achieving for the first time logarithmic depth in precision. Numerical simulations demonstrate significant performance advantages, establishing our method as a practical and scalable solution for simulating open quantum systems on near-term quantum hardware.

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