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arXiv 2602.20256cond-mat.stat-mechcond-mat.dis-nnquant-ph
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量子多体哈密顿量的谱分解

Spectral Decimation of Quantum Many-Body Hamiltonians

International School for Advanced Studies (SISSA)(高等研究院);INFN Sezione di Trieste(意大利国家核物理研究所的里雅斯特分部)

Feng He, Arthur Hutsalyuk, Giuseppe Mussardo, Andrea Stampiggi

AI总结:

提出谱分解理论,通过特征对称扇区(CSS)量化统计混合谱中的涌现对称性,并应用于希尔伯特空间碎片化和无序诱导的多体局域化。

摘要:

我们发展了量子多体哈密顿量谱分解的系统理论,并表明它为统计混合谱中的涌现对称性提供了定量探针。基于统计混合的分析描述,我们推导了特征对称扇区(CSS)大小的显式表达式,CSS定义为表现出非泊松关联的最大能级子序列。CSS维度被证明是底层对称扇区的有偏平均,建立了谱统计与希尔伯特空间结构之间的直接联系。我们将此框架应用于两个典型场景:希尔伯特空间碎片化和无序诱导的多体局域化(MBL)。在碎片化系统中,即使全谱接近泊松分布,CSS也能复现混合预测并分离出相关子扇区。在无序海森堡链中,谱分解通过缩小的CSS揭示了可积性的逐渐涌现,其统计特征与局域运动积分一致。我们引入特征对称熵(CSE)作为有限尺寸标度可观测量,并在可访问系统尺寸内提取交叉指数。我们的结果确立了谱分解作为一种可控、无偏且计算成本低廉的诊断方法,用于揭示多体谱中的隐藏结构,能够区分混沌动力学、统计混合和涌现可积性。

英文摘要:

We develop a systematic theory of spectral decimation for quantum many-body Hamiltonians and show that it provides a quantitative probe of emergent symmetries in statistically mixed spectra. Building on an analytical description of statistical mixtures, we derive an explicit expression for the size of a characteristic symmetry sector (CSS), defined as the largest subsequence of levels exhibiting non-Poissonian correlations. The CSS dimension is shown to be the size-biased average of the underlying symmetry sectors, establishing a direct link between spectral statistics and Hilbert-space structure. We apply this framework to two paradigmatic settings: Hilbert-space fragmentation and disorder-induced many-body localization (MBL). In fragmented systems, the CSS reproduces the mixture prediction and isolates correlated subsectors even when the full spectrum appears nearly Poissonian. In the disordered Heisenberg chain, spectral decimation reveals the gradual emergence of integrability through a shrinking CSS, whose statistics exhibit signatures consistent with local integrals of motion. We introduce a characteristic symmetry entropy (CSE) as a finite-size scaling observable and extract, within accessible system sizes, the crossover exponents. Our results establish spectral decimation as a controlled, unbiased and computationally inexpensive diagnostic of hidden structure in many-body spectra, capable of distinguishing between chaotic dynamics, statistical mixtures, and emergent integrability.

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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