论文标题

部分可观测时空混沌系统的无模型预测

Beyond islands: A free probabilistic approach

论文作者

Wang, Jinzhao

论文摘要

在Penington-Shenker-Stanford-Yang(PSSY)模型的背景下,我们提供了一个免费的概率建议,以计算任意体积辐射状态的细粒辐射熵,其中可以通过完全控制实现重力路径积分。我们观察到,复制技巧引力路径积分是在引力部门和物质扇区之间分别匹配的自由乘法卷积。即使在岛公式未能应用的情况下,卷积公式也可以准确地计算辐射熵。它还有助于将这种引力复制技巧视为可溶的豪斯多夫时刻问题。然后,我们可以使用自由谐波分析来评估如何评估自由卷积公式,这还为解决可分离的样品协方差矩阵谱系提供了新的免费概率处理。自由卷积公式表明,在有限的von neumann代数中,可以将竞争量子极端表面中编码的量子信息建模为自由随机变量。使用自由概率和随机矩阵理论之间的紧密联系,我们表明PSSY模型可以描述为一个随机矩阵模型,它本质上是对Page模型的概括。然后表明,只有当卷积以一杆熵为特征的政权分配时,岛公式才适用。我们进一步表明,卷积公式可以根据相对熵重组为广义熵公式。

We give a free probabilistic proposal to compute the fine-grained radiation entropy for an arbitrary bulk radiation state, in the context of the Penington-Shenker-Stanford-Yang (PSSY) model where the gravitational path integral can be implemented with full control. We observe that the replica trick gravitational path integral is combinatorially matching the free multiplicative convolution between the spectra of the gravitational sector and the matter sector respectively. The convolution formula computes the radiation entropy accurately even in cases when the island formula fails to apply. It also helps to justify this gravitational replica trick as a soluble Hausdorff moment problem. We then work out how the free convolution formula can be evaluated using free harmonic analysis, which also gives a new free probabilistic treatment of resolving the separable sample covariance matrix spectrum. The free convolution formula suggests that the quantum information encoded in competing quantum extremal surfaces can be modelled as free random variables in a finite von Neumann algebra. Using the close tie between free probability and random matrix theory, we show that the PSSY model can be described as a random matrix model that is essentially a generalization of Page's model. It is then manifest that the island formula is only applicable when the convolution factorizes in regimes characterized by the one-shot entropies. We further show that the convolution formula can be reorganized to a generalized entropy formula in terms of the relative entropy.

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