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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.16286 |
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| _version_ | 1866908871100989440 |
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| author | Zhu, Hao Wang, Ding-Zu Ran, Shi-Ju Zhang, Guo-Feng |
| author_facet | Zhu, Hao Wang, Ding-Zu Ran, Shi-Ju Zhang, Guo-Feng |
| contents | Simulating the dynamics of quantum many-body systems with disorder is a fundamental challenge. In this work, we propose a general approach -- the statistics-encoded tensor network (SeTN) -- to study such systems. By encoding disorder into an auxiliary layer and averaging separately, SeTN restores translational invariance, enabling a well-defined transfer matrix formulation. We derive a universal criterion, $n \gg α^2 t^2$, linking discretization $n$, disorder strength $α$, and evolution duration $t$. This sets the resolution required for faithful disorder averaging and shows that encoding is most efficient in the weak-disorder, typically chaotic regime. Applied to the disordered transverse-field Ising model, SeTN shows that the spectral form factor is governed by the leading transfer-matrix eigenvalue, in contrast to the kicked Ising model. SeTN thus provides a novel framework for probing the disorder-driven dynamical phenomena in many-body quantum systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_16286 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Statistics-encoded tensor network approach in disordered quantum many-body spin chains Zhu, Hao Wang, Ding-Zu Ran, Shi-Ju Zhang, Guo-Feng Quantum Physics Simulating the dynamics of quantum many-body systems with disorder is a fundamental challenge. In this work, we propose a general approach -- the statistics-encoded tensor network (SeTN) -- to study such systems. By encoding disorder into an auxiliary layer and averaging separately, SeTN restores translational invariance, enabling a well-defined transfer matrix formulation. We derive a universal criterion, $n \gg α^2 t^2$, linking discretization $n$, disorder strength $α$, and evolution duration $t$. This sets the resolution required for faithful disorder averaging and shows that encoding is most efficient in the weak-disorder, typically chaotic regime. Applied to the disordered transverse-field Ising model, SeTN shows that the spectral form factor is governed by the leading transfer-matrix eigenvalue, in contrast to the kicked Ising model. SeTN thus provides a novel framework for probing the disorder-driven dynamical phenomena in many-body quantum systems. |
| title | Statistics-encoded tensor network approach in disordered quantum many-body spin chains |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2508.16286 |