Driven Lorentz model in discrete time

Dan Shafir, Alessio Squarcini, Stanislav Burov, Thomas Franosch
{"title":"Driven Lorentz model in discrete time","authors":"Dan Shafir, Alessio Squarcini, Stanislav Burov, Thomas Franosch","doi":"arxiv-2409.02696","DOIUrl":null,"url":null,"abstract":"We consider a tracer particle performing a random walk on a two-dimensional\nlattice in the presence of immobile hard obstacles. Starting from equilibrium,\na constant force pulling on the particle is switched on, driving the system to\na new stationary state. Our study calculates displacement moments in discrete\ntime (number of steps $N$) for an arbitrarily strong constant driving force,\nexact to first order in obstacle density. We find that for fixed driving force\n$F$, the approach to the terminal discrete velocity scales as $\\sim N^{-1}\n\\exp(- N F^2 / 16)$ for small $F$, differing significantly from the $\\sim\nN^{-1}$ prediction of linear response. Besides a non-analytic dependence on the\nforce and breakdown of Einstein's linear response, our results show that\nfluctuations in the directions of the force are enhanced in the presence of\nobstacles. Notably, the variance grows as $\\sim N^3$ (superdiffusion) for $F\n\\to \\infty$ at intermediate steps, reverting to normal diffusion ($\\sim N$) at\nlarger steps, a behavior previously observed in continuous time but\ndemonstrated here in discrete steps for the first time. Unlike the exponential\nwaiting time case, the superdiffusion regime starts immediately at $N=1$. The\nframework presented allows considering any type of waiting-time distribution\nbetween steps and transition to continuous time using subordination methods.\nOur findings are also validated through computer simulations.","PeriodicalId":501520,"journal":{"name":"arXiv - PHYS - Statistical Mechanics","volume":"10 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Statistical Mechanics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.02696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We consider a tracer particle performing a random walk on a two-dimensional lattice in the presence of immobile hard obstacles. Starting from equilibrium, a constant force pulling on the particle is switched on, driving the system to a new stationary state. Our study calculates displacement moments in discrete time (number of steps $N$) for an arbitrarily strong constant driving force, exact to first order in obstacle density. We find that for fixed driving force $F$, the approach to the terminal discrete velocity scales as $\sim N^{-1} \exp(- N F^2 / 16)$ for small $F$, differing significantly from the $\sim N^{-1}$ prediction of linear response. Besides a non-analytic dependence on the force and breakdown of Einstein's linear response, our results show that fluctuations in the directions of the force are enhanced in the presence of obstacles. Notably, the variance grows as $\sim N^3$ (superdiffusion) for $F \to \infty$ at intermediate steps, reverting to normal diffusion ($\sim N$) at larger steps, a behavior previously observed in continuous time but demonstrated here in discrete steps for the first time. Unlike the exponential waiting time case, the superdiffusion regime starts immediately at $N=1$. The framework presented allows considering any type of waiting-time distribution between steps and transition to continuous time using subordination methods. Our findings are also validated through computer simulations.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
离散时间中的驱动洛伦兹模型
我们考虑的是一个示踪粒子在二维网格上进行随机行走时遇到的不动硬障碍物。从平衡状态开始,粒子受到一个恒定力的牵引,驱动系统进入一个新的静止状态。我们的研究计算了任意强恒定驱动力在离散时间(步数 $N$)内的位移矩,精确到障碍物密度的一阶。我们发现,对于固定的驱动力$F$,在小$F$的情况下,接近终端离散速度的尺度为$\sim N^{-1}\exp(- N F^2 / 16)$,这与线性响应的预测值$\simN^{-1}$有很大不同。除了对力的非解析依赖和爱因斯坦线性响应的破坏之外,我们的结果还表明,在存在障碍物的情况下,力的方向波动会增强。值得注意的是,在中间步长的$F\to \infty$中,方差以$\sim N^3$(超扩散)的形式增长,而在更大的步长中则恢复为正常扩散($\sim N$),这种行为以前在连续时间中观察到过,但在这里首次在离散步长中得到了证明。与指数等待时间的情况不同,超扩散机制在 $N=1$ 时立即开始。我们提出的框架允许考虑步长之间任何类型的等待时间分布,并使用从属方法过渡到连续时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Mirages in the Energy Landscape of Soft Sphere Packings Shock propagation in a driven hard sphere gas: molecular dynamics simulations and hydrodynamics Thermal transport in long-range interacting harmonic chains perturbed by long-range conservative noise Not-so-glass-like Caging and Fluctuations of an Active Matter Model Graph Neural Network-State Predictive Information Bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1