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Updated: Jan 8, 2026

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通过零模式测量器固定切断循环张量网络
Ihor Sokolov1,2, Yintai Zhang1,3, Jacek Dziarmaga1,2
1Jagiellonian University, Institute of Theoretical Physics, Faculty of Physics, Astronomy and Applied Computer Science, ul. Łojasiewicza 11, 30-348 Kraków, Poland.
Physical review. E
|December 23, 2025
概括
循环张量网络由于内部相关性而被低效地压缩. 本研究介绍了一种局部键优化方法,该方法通过利用循环相关性来改善压缩,以获得更好的截断,优于标准初始化.
科学领域:
- 凝聚物质物理学 凝聚物质物理学
- 量子信息理论就是量子信息理论.
- 物理学中的数值方法.
背景情况:
- 循环张量网络,如无限投影纠对状态 (iPEPS) 和周期矩阵产物状态 (pMPS),表现出复杂的内部相关性.
- 这些相关性往往导致标准压缩技术的低效,阻碍了准确的数值模拟.
研究的目的:
- 为循环张量网络开发一种改进的压缩方法.
- 通过优化债券尺寸来提高张量网络算法的效率和准确性.
主要方法:
- 提出了一种新的局部债券优化技术,利用局部循环相关性.
- 该方法涉及切割债券来定义状态,利用它们的线性依赖性进行切断.
- 线性依赖是使用状态的度量张数的零模式来解决的.
主要成果:
- 与标准初始化技术相比,拟议的方法显示了较好的初始截断错误.
- 在张量重规范化组 (TRG) 中成功应用到无限预测纠对状态 (iPEPS) 和周期矩阵积分状态 (pMPS).
- 通过各种说明性示例进行验证,以展示卓越的性能.
结论:
- 局部键优化为压缩循环张量网络提供了更有效的方法.
- 该方法为张量网络状态的初始截断精度提供了显著的改进.
- 这种技术提高了涉及复杂量子系统的数值模拟的效率.
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