结合随机热力学的退火性能,并应用于模拟退火

Yutong Luo, Yi-Zheng Zhen, Xiangjing Liu, Daniel Ebler, Oscar Dahlsten
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引用次数: 1

摘要

退火是逐渐降低系统温度以引导其达到最低能态的过程。在一篇随附的论文中[Y.]罗等人,物理学。Rev. E 108, L052105(2023)],我们通过将退火与随机热力学工具联系起来,推导出退火性能的一般界,包括熵产生状态转换的速度限制。我们在这里详细地描述了一般界的推导。此外,我们还深入分析了采用Glauber动力学进行模拟退火的情况。我们展示了如何绑定出现在边界中的两个特定情况的量,即活度,微状态跳跃数量的度量,以及状态与瞬时热状态之间的相对熵变化,这是由于温度变化引起的。我们通过对自旋玻璃的谢林顿-柯克帕特里克(SK)模型的数值模拟来举例说明这些论点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bound on annealing performance from stochastic thermodynamics, with application to simulated annealing
Annealing is the process of gradually lowering the temperature of a system to guide it towards its lowest energy states. In an accompanying paper [Y. Luo et al., Phys. Rev. E 108, L052105 (2023)], we derived a general bound on annealing performance by connecting annealing with stochastic thermodynamics tools, including a speed limit on state transformation from entropy production. We here describe the derivation of the general bound in detail. In addition, we analyze the case of simulated annealing with Glauber dynamics in depth. We show how to bound the two case-specific quantities appearing in the bound, namely the activity, a measure of the number of microstate jumps, and the change in relative entropy between the state and the instantaneous thermal state, which is due to temperature variation. We exemplify the arguments by numerical simulations on the Sherrington-Kirkpatrick (SK) model of spin glasses.
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