发表机构
Virginia Tech; University of Illinois Urbana-Champaign; Lawrence Berkeley National Laboratory（弗吉尼亚理工大学; 伊利诺伊大学厄巴纳-香槟分校; 劳伦斯伯克利国家实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种随时间变化的驱动-耗散协议，利用随机林德布拉德算符的经验平均将任意初始态驱动至低能态，混合时间仅依赖哈密顿量本征值分布，适用于冷启动。
AI 中文摘要
耗散协议为基态制备提供了一条无需与基态有较大初始重叠的途径。为了超越时间无关的林德布拉德算符以及从固定分布中采样的随机林德布拉德算符，我们研究了生成器随时间变化的驱动-耗散协议。我们的构造使用一族随机林德布拉德算符，其跳变算符通过对固定目标哈密顿量下随机矩阵的酉演化进行平均而获得。我们证明，这些林德布拉德算符的经验平均值能将任意初始密度矩阵驱动到低能态。所得的混合时间界限仅通过哈密顿量的本征值分布依赖于哈密顿量，并且即使在冷启动情况下也依然有效。
英文摘要
Dissipative protocols offer a route to ground state preparation that does not require a large initial overlap with the ground state. To move beyond time independent Lindbladians and randomized Lindbladians sampled from a fixed distribution, we study driven-dissipative protocols in which the generator varies over time. Our construction uses a family of randomized Lindbladians whose jump operators are obtained by averaging the unitary evolution of random matrices under a fixed target Hamiltonian. We show that empirical averages of these Lindbladians drive arbitrary initial density matrices to low energy states. The resulting mixing time bounds depend on the Hamiltonian only through its eigenvalue distribution and remain valid even for cold starts.
Comments53 pages, 7 figures
