Sherrington–Kirkpatrick模型中的临界慢化

无需登录。完整内容与个人兴趣标记的公开阅读入口,可直接交给 GPT 阅读。

公开快照同步: · 内容整理:2026-10-20T09:58:44+08:00

OpenAI论文 / 概率与统计 · 2026-09-24

Sherrington–Kirkpatrick模型中的临界慢化

Critical slowing down in the Sherrington–Kirkpatrick model

OpenAI 数学仓库收录的研究手稿。展开查看英文摘要,或标记后让我进一步解释。

具体内容

稿件研究零场高斯Sherrington–Kirkpatrick模型在临界逆温度β=1时的热浴动力学混合行为。作者声称从典型平衡构型固定为初始态出发,对每个确定性序列t_n=o(n^{2/3})(每站点速率一时间),初始态中时间t_n总变差距离超过1/4的Gibbs质量以趋于1的概率在无序上成立;对均匀站点更新尝试的整数序列k_n=o(n^{5/3})也有相同结论。该结果对自旋玻璃临界动力学提供了数学描述。

AI 产生的研究手稿;收录不表示已完成独立审查或同行评议。

英文原始摘要

At the critical inverse temperature β = 1, we prove slow mixing for zero-field Gaussian Sherrington–Kirkpatrick heat-bath dynamics from typical equilibrium configurations held fixed as initial states. For every deterministic sequence $`t_n=o(n^{2/3})`$ in rate-one-per-site time, the Gibbs mass of initial states whose time-tn total-variation distance from equilibrium exceeds 1/4 tends to one in probability over the disorder. The same statement holds for every deterministic integer sequence $`k_n=o(n^{5/3})`$ of uniform-site update attempts.

用户标记:未标记

固定编号:b1a16a2200b31c51

原文来源