非交换概率与乘级联

IF 3.9 1区 数学 Q1 STATISTICS & PROBABILITY Statistical Science Pub Date : 2021-04-01 DOI:10.1214/20-STS780
I. McKeague
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引用次数: 0

摘要

正如Furey(2015)所建议的那样,标准模型粒子物理的各个方面可以用一个适当丰富的代数来解释。本文发展了大型因果树图的渐近性,这些因果树图在这样的代数中结合了自由独立的元素。Marčenko–Pastur定律和Wigner半圆定律被证明是在分配给因果树边缘的非负元素的路径上的归一化和的极限。这些结果是在非对易概率的情况下建立的。具有经典独立正边权的树(随机乘法级联)最初由Mandelbrot提出,作为显示湍流分形特征的模型。本工作的新颖之处在于使用非对易(自由)概率来允许边缘权重取代数中的值。还讨论了它在理论神经科学中的应用。
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Noncommutative Probability and Multiplicative Cascades
Various aspects of standard model particle physics might be explained by a suitably rich algebra acting on itself, as suggested by Furey (2015). The present paper develops the asymptotics of large causal tree diagrams that combine freely independent elements in such an algebra. The Marčenko–Pastur law and Wigner’s semicircle law are shown to emerge as limits of normalized sum-over-paths of nonnegative elements assigned to the edges of causal trees. These results are established in the setting of noncommutative probability. Trees with classically independent positive edge weights (random multiplicative cascades) were originally proposed by Mandelbrot as a model displaying the fractal features of turbulence. The novelty of the present work is the use of noncommutative (free) probability to allow the edge weights to take values in an algebra. An application to theoretical neuroscience is also discussed.
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来源期刊
Statistical Science
Statistical Science 数学-统计学与概率论
CiteScore
6.50
自引率
1.80%
发文量
40
审稿时长
>12 weeks
期刊介绍: The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.
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