随机能模型中的极端协同作用
Vudtiwat Ngampruetikorn1,2, David J Schwab2
1School of Physics, <a href="https://ror.org/0384j8v12">University of Sydney</a>, Sydney, NSW 2006, Australia.
Physical review letters
|January 3, 2025
概括
随机能量模型 (REM) 展示了极端的协同作用,使一个新的安全的秘密共享方案成为可能. 这种统计物理模型提供了最佳的信息编码,并将物理与计算联系起来.
科学领域:
- 统计物理 统计物理
- 信息理论 信息理论
- 计算科学 计算科学
背景情况:
- 随机能量模型 (REM) 是一种可解决的旋转玻璃模型,具有广泛的应用.
- 以前的应用包括蛋白质折叠,组合优化和多体定位.
- 探索了REM和秘密分享之间的新连接.
研究的目的:
- 导出REM子系统之间相互信息的分析表达式.
- 根据REM相关性制定一个秘密共享方案.
- 在REM框架内确定安全秘密共享的条件.
主要方法:
- 分析表达式的导出,以获得相互信息.
- 使用REM制定一个秘密共享计划.
- 对温度和秘密长度参数进行分析,以确保安全.
- 针对最佳信息编码的特殊点的研究.
主要成果:
- REM相关性表现出极端的协同作用,类似于安全的秘密共享.
- 确定了用于REM安全的特定温度和秘密长度范围.
- 在REM阶段图中发现了一个物理最优的信息编码点.
- 热力学极限结果与有限系统模拟质量一致.
结论:
- 雷姆提供了一个安全的秘密共享的框架,具有最佳的编码属性.
- 多体系统中的协同相关性可以使用这种新语言来描述.
- 信息理论作为统一的概念,将统计物理学和计算联系在一起.
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