Physical review. E最新文献_第6页

Timescales of quantum and classical chaotic spin models evolving toward equilibrium. 量子和经典混沌自旋模型向平衡演化的时间尺度。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044210

Fausto Borgonovi, Felix M Izrailev, Lea F Santos

引用次数: 0

Exponential rate of epidemic spreading on complex networks. 复杂网络中流行病传播的指数速率。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044311

Samuel Cure, Florian G Pflug, Simone Pigolotti

引用次数: 0

Three-dimensional finite-time Lyapunov-exponent analysis of fluid dusty plasmas under weightlessness using a machine-learning particle reconstruction technique. 利用机器学习粒子重建技术对流体尘埃等离子体在失重状态下的三维有限时间李雅普诺夫指数分析。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.045214

André Melzer, Christina Knapek, Daniel Maier, Daniel Mohr, Stefan Schütt

引用次数: 0

Forced swarmalators that move in higher-dimensional spaces. 在高维空间中移动的强制蜂拥者。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044207

Md Sayeed Anwar, Dibakar Ghosh, Kevin O'Keeffe

引用次数: 0

Dynamical system response under Gaussian and Poisson white noises solved by deep neural network method with adaptive task decomposition and progressive learning strategy. 采用自适应任务分解和渐进式学习策略的深度神经网络方法求解高斯白噪声和泊松白噪声下的动力系统响应。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.045309

Wantao Jia, Xiaotong Feng, Yifan Zhao, Wanrong Zan

{"title":"Dynamical system response under Gaussian and Poisson white noises solved by deep neural network method with adaptive task decomposition and progressive learning strategy.","authors":"Wantao Jia, Xiaotong Feng, Yifan Zhao, Wanrong Zan","doi":"10.1103/PhysRevE.111.045309","DOIUrl":"https://doi.org/10.1103/PhysRevE.111.045309","url":null,"abstract":"The forward Kolmogorov equation corresponding to a system under the combined excitation of Gaussian and Poisson white noises is an integrodifferential equation (IDE). In our recent study, we introduced GL-PINNs, which integrates the Gauss-Legendre (GL) quadrature with the physics-informed neural networks (PINNs) framework for solving time-dependent IDEs. However, we observed that in scenarios such as insufficient learning of initial conditions or dynamical systems with strong temporal dependencies, GL-PINNs produced inaccurate solutions despite achieving low training loss values. This issue primarily stems from the GL-PINNs framework's failure to account for temporal causality. To address this limitation, we develop a deep neural network method called ATD-GLPINNs, which integrates adaptive task decomposition and progressive learning strategy. This approach decomposes the complex task along the time axis into an initial subtask and several extra tasks, which enable progressive learning through adaptive adjustment of task parameters. As an extension of the GL-PINNs, this algorithm adheres to temporal causality by prioritizing the training of early subtasks and dynamically allocating additional computational resources to subsequent ones. Numerical experiments demonstrate that our suggested method converges with significantly fewer training epochs compared to GL-PINNs, making it not only more efficient and robust, but also capable of reducing computational costs while improving prediction accuracy.","PeriodicalId":20085,"journal":{"name":"Physical review. E","volume":"111 4-2","pages":"045309"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144136256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Density-based recurrence measures from microstates. 基于密度的微观状态递归度量。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044212

Felipe Eduardo Lopes da Cruz, Thiago de Lima Prado, Sergio Roberto Lopes, Norbert Marwan, Jürgen Kurths

引用次数: 0

Anomalous thermodiffusion, absolute negative mobility, and reverse heat transport in a single quantum dot. 单量子点的异常热扩散、绝对负迁移率和反向热输运。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044112

Yanchao Zhang, Xiaolong Lü

引用次数: 0

Bayesian ecoevolutionary game dynamics. 贝叶斯生态进化博弈动力学。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044401

Arunava Patra, Joy Das Bairagya, Sagar Chakraborty

{"title":"Bayesian ecoevolutionary game dynamics.","authors":"Arunava Patra, Joy Das Bairagya, Sagar Chakraborty","doi":"10.1103/PhysRevE.111.044401","DOIUrl":"https://doi.org/10.1103/PhysRevE.111.044401","url":null,"abstract":"The symbiotic relationship between the frameworks of classical game theory and evolutionary game theory is well established. However, evolutionary game theorists have mostly tapped into the classical game of complete information where players are completely informed of all other players' payoffs. Of late, there is a surge of interest in ecoevolutionary interactions where the environment's state is changed by the players' actions which, in turn, are influenced by the changing environment. However, in real life, the information about the true environmental state must pass through some noisy channel (like the usually imperfect sensory apparatus of the players) before it is perceived by the players: The players naturally are prone to sometimes perceive the true state erroneously. Given the uncertain perceived environment, the players may adopt bet-hedging kind of strategies in which they play different actions in different perceptions. In a population of such ill-informed players, a player would be confused about the information state of her opponent, and an incomplete information situation akin to a Bayesian game surfaces. In short, we contemplate the possibility of the natural emergence of the symbiotic relationship between the frameworks of Bayesian games and ecoevolutionary games when the players are equipped with inefficient sensory apparatus. Herein, we illustrate this connection using a setup of infinitely large, well-mixed population of players equipped with two actions for exploiting a resource (the environment) at two different rates so that the resource state evolves accordingly. The state of the resource impacts every player's decision of playing particular action. We investigate the continuous state environment in the presence of a Gaussian noisy channel. Employing the formalism of deterministic replicator dynamics, we find that noisy information can be effective in preventing the resource from going extinct.","PeriodicalId":20085,"journal":{"name":"Physical review. E","volume":"111 4-1","pages":"044401"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144136309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distinguishing photon-count fluctuation characteristics of classical and quantum light sources using non-Markovian processes. 用非马尔可夫过程区分经典光源和量子光源的光子计数涨落特性。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.044138

Lian Seng Tey, S V Muniandy, Wu Yi Chong

引用次数: 0

Enhanced terahertz emission from the wakefield of CO_{2}-laser-created plasma. CO_{2}-激光产生的等离子体尾流场的增强太赫兹发射。

IF 2.4 3区物理与天体物理

Physical review. E Pub Date : 2025-04-01 DOI: 10.1103/PhysRevE.111.045205

Srimanta Maity, Garima Arora

引用次数: 0