插曲随机循环矩阵的光谱统计及其对随机循环图的应用
Sunidhi Sen1, Himanshu Shekhar1, Santosh Kumar1
1Shiv Nadar Institution of Eminence, Department of Physics, Gautam Buddha Nagar, Uttar Pradesh 201314, India.
Physical review. E
|April 18, 2025
概括
这项研究引入了一个灵活的矩阵模型 (A+iB) 与真实随机循环矩阵,产生精确的高斯联合概率密度函数. 该模型允许通过模拟和随机循环图谱证实各种自值分布之间的插值.
科学领域:
- 数学物理 数学物理
- 随机矩阵理论 随机矩阵理论
- 复杂的系统复杂的系统.
背景情况:
- 研究形式为A+iB的矩阵模型,其中A和B是真实随机循环矩阵.
- 专注于具有独立,非相同分布的高斯项的矩阵.
研究的目的:
- 导出矩阵模型的联合概率密度函数的确切结果.
- 通过调整矩阵输入参数,探索不同固有值分布之间的插值.
- 分析随机实数和复杂循环矩阵之间的交叉.
主要方法:
- 联合概率密度函数的分析推导.
- 任意顺序边际密度的计算.
- 蒙特卡洛模拟用于验证.
- 与随机循环图形相邻矩阵的光谱进行比较.
主要成果:
- 发现联合概率密度函数是一个多变量高斯函数.
- 调整高斯元素的平均值和差异,可以在各种固有值分布中进行插值.
- 分析结果显示,在大维限中,与随机循环图谱的频谱有很好的一致性.
结论:
- 拟议的矩阵模型为研究自身值分布提供了一个多功能框架.
- 该模型准确地捕捉了随机循环图的光谱特性,即使输入分布不同.
- 为理解复杂矩阵行为及其应用提供了强大的方法.
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