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arXiv 2212.00533cond-mat.stat-mechcond-mat.str-el
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不同动力学区域中长程伊辛模型的热化:全计数统计方法

Thermalization of long range Ising model in different dynamical regimes: a full counting statistics approach

Nishan Ranabhat, Mario Collura

AI总结:

本文利用基于MPS的TDVP算法和全概率分布比较,研究幂律衰减长程横场伊辛链在量子淬火后的热化,发现强约束抑制热化而弱约束允许热化。

摘要:

我们研究了具有幂律衰减相互作用(约为1/r^α)的横场伊辛链,在横场发生全局量子淬火并进入两种不同动力学区域后的热化行为。我们通过比较演化态的完整概率分布函数(PDF)与 Gibbs 正则系综(GCE)给出的相应热态,来量化热化行为。为此,我们采用基于矩阵乘积态(MPS)的含时变分原理(TDVP)算法,同时模拟全局量子淬火后的实时演化以及有限温度密度算符。我们观察到,在所考虑的所有相互作用强度 α 下,强约束区域中的热化均受到强烈抑制,而弱约束区域中则会发生热化。

英文摘要:

We study thermalization of transverse field Ising chain with power law decaying interaction $\sim 1/r^α$ following a global quantum quench of the transverse field to two different dynamical regimes. We quantify the thermalization behavior by comparing the full probability distribution function (PDF) of the evolving states with the corresponding thermal state given by the Gibbs canonical ensemble (GCE). To this end, we use matrix product state (MPS) based time dependent variational principle (TDVP) algorithm to simulate both real time evolution following a global quantum quench and the finite temperature density operator. We observe that thermalization is strongly suppressed in the region with strong confinement for all the interaction strength $α$ considered whereas thermalization occurs in the region with weak confinement.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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