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arXiv 2401.01239cond-mat.stat-mech
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相空间最大熵随机游走:物理轨迹的朗之万式系综

Phase space maximal entropy random walk: Langevin-like ensembles of physical trajectories

Jarek Duda

AI总结:

本文提出相空间最大熵随机游走(psMERW),在相空间中构建有限速度物理轨迹系综,推导并比较四种平稳分布预测方法,发现新方法在势阱中产生$\sin$分布,与量子力学$\sin^2$分布存在可实验区分的差异。

摘要:

正如统计学家乔治·博克斯所言:“所有模型都是错误的,但有些是有用的。”标准扩散推导或费曼路径系综使用了非物理的、具有无限速度和动能的、处处不可微的轨迹——这看似错误之处,可能只是我们为简化数学而做的近似。本文引入了一些基本工具来研究这一问题。为了考虑更具物理意义的有限速度轨迹系综,我们可以在$(x,v)$相空间中工作,如同朗之万方程中速度控制空间步长一样,这里也由空间势$V(x)$控制。文中推导并比较了4种预测平稳概率分布的方法:使用空间中的步/点的玻尔兹曼系综(GRW——一般随机游走)或相空间中的步/点的玻尔兹曼系综(psGRW),以及空间中的路径的玻尔兹曼系综(MERW——最大熵随机游走)和相空间中的路径的玻尔兹曼系综(psMERW),并推广到Lévy飞行。路径系综通常具有更强的类安德森局域化,MERW的平稳分布恰好等于量子基态。所提出的相空间中的新型MERW存在一些细微差异,这些差异可能通过实验加以区分。例如,对于一维无限深势阱:步系综的平稳分布为$\rho=1$,路径系综的平稳分布为$\rho\sim \sin^2$(如量子力学中),而所提出的光滑路径系综的平稳分布为$\rho\sim \sin$——由于随机获得的速度,粒子更频繁地接近势垒。

英文摘要:

As written by statistician George Box "All models are wrong, but some are useful", standard diffusion derivation or Feynman path ensembles use nonphysical infinite velocity/kinetic energy nowhere differentiable trajectories - what seems wrong, might be only our approximation to simplify mathematics. This article introduces some basic tools to investigate this issue. To consider ensembles of more physical finite velocity trajectories, we can work in $(x,v)$ phase space like in Langevin equation with velocity controlling spatial steps, here also controlled with spatial potential $V(x)$. There are derived and compared 4 approaches to predict stationary probability distributions: using Boltzmann ensemble of steps/points in space (GRW - generic random walk) or in phase space (psGRW), and analogously Boltzmann ensemble of paths in space (MERW - maximal entropy random walk) and in phase space (psMERW), also generalized to L{é}vy flights. Path ensembles generally have much stronger Anderson-like localization, MERW has stationary distribution exactly as quantum ground state. Proposed novel MERW in phase space has some slight differences, which might be distinguished experimentally. For example for 1D infinite potential well: $ρ=1$ stationary distribution for step ensemble, $ρ\sim \sin^2$ for path ensemble (as in QM), and $ρ\sim \sin$ for proposed smooth path ensembles - more frequently approaching the barriers due to randomly gained velocity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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