位置和密度的平均背弛。

IF 2.2 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS
Gabriel Knotz, Matthias Krüger
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引用次数: 0

摘要

相关函数是分析统计粒子轨迹的标准工具。最近,一种所谓的平均反向松弛(MBR)被引入,它与三个时间点的位置相关。其长期值与 1/2 的偏差已被证明是密闭粒子时间反向对称性破坏的标志。在这里,我们从几个方面扩展了对 MBR 的分析,包括讨论根据轨迹数据评估 MBR 时使用的截止长度。利用路径积分法,我们提供了多点密度相关性 MBR 的一般表达式。对于高斯系统,该表达式可得出 MBR 与均方位移之间的关系。最后,我们证明了 MBR 可用于粒子位置以外的其他随机观测值。将其用于微观密度时,它与 1/2 的偏差是密闭或大块系统中细节平衡被打破的标志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mean back relaxation for position and densities.

Correlation functions are a standard tool for analyzing statistical particle trajectories. Recently, a so-called mean back relaxation (MBR) has been introduced, which correlates positions at three time points. The deviation of its long-time value from 1/2 has been shown to be a marker for breakage of time-reversal symmetry for confined particles. Here, we extend the analysis of MBR in several ways, including discussion of a cutoff length used when evaluating MBR from trajectory data. Using a path integral approach, we provide a general expression for MBR in terms of multipoint density correlations. For Gaussian systems, this expression yields a relation between MBR and mean-squared displacement. We finally demonstrate that MBR can be applied to other stochastic observables besides particle position. Using it for microscopic densities, its deviation from 1/2 is a marker for broken detailed balance in confinement or in bulk systems.

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来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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