Physica A: Statistical Mechanics and its Applications最新文献

{"title":"Formulating effective resistance in temporal networks: Models and empirical insights","authors":"Zhidong He ,&nbsp;Wen Du ,&nbsp;Cong Li","doi":"10.1016/j.physa.2025.130991","DOIUrl":"10.1016/j.physa.2025.130991","url":null,"abstract":"<div><div>Effective resistance is a fundamental metric for quantifying connectivity and transport efficiency in static networks, yet its generalization to temporal networks, where connectivity evolves over time, remains an open challenge. This paper addresses this gap by proposing and systematically investigating a suite of definitions for temporal effective resistance (TER). We introduce four distinct formulations based on averaging and aggregation, generalized multi-path costs, random walk commute times, and a principled energy minimization framework derived from electrical circuit theory. A key argument within our models is a “retention” mechanism that allows flow to be carried over between time steps at an energetic cost, explicitly analogous to buffering or storage. Through extensive numerical experiments on a diverse set of networks, we demonstrate that these TER definitions capture distinct and non-equivalent aspects of spatio-temporal connectivity. Our results show that while the metrics provide convergent assessments in well-connected networks, their values diverge significantly in sparse or fragmented systems. Proposing a conduction efficiency metric to assess the network’s overall transmission capability, we show that the retention factor is critical for performance in temporally fragmented networks. Our analysis reveals a fundamental trade-off between patience (waiting for further connections) and progress (traversing existing paths), where an optimal waiting strategy could maximize conduction efficiency. This work provides a versatile and principled toolkit for analyzing flow, diffusion, and resilience in time-varying networked systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130991"},"PeriodicalIF":3.1,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160207","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}

{"title":"A cost-constrained dismantling framework for hypergraph with dynamic cascading failure using deep reinforcement learning","authors":"Ting Jiang ,&nbsp;Kai Liu ,&nbsp;Bing-Bing Xiang ,&nbsp;Hai-Feng Zhang ,&nbsp;Huan Wang","doi":"10.1016/j.physa.2025.130988","DOIUrl":"10.1016/j.physa.2025.130988","url":null,"abstract":"<div><div>Network dismantling is a fundamental challenge in the study of complex networks, with significant real-world applications such as controlling the spread of diseases and disrupting terrorist networks. However, most existing studies focus on pairwise interaction networks and static dismantling strategies, often overlooking the dynamic nature of cascading failures and the associated cost constraints that are prevalent in real-world scenarios. These limitations restrict their ability to effectively capture the complexity of failure dynamics in systems with higher-order interactions. To overcome these challenges, we utilize hypergraphs to model higher-order relationships within complex systems and introduce a dynamic dismantling approach that explicitly accounts for cascading failures under cost constraints. Building on this foundation, we propose a novel hypergraph dismantling framework, C2HD-RL, which leverages deep reinforcement learning. The framework enables an agent to iteratively explore different node selection strategies in synthetic hypergraphs and adjust its behavior based on the rewards received, ultimately learning an optimal hypergraph dismantling strategy. Comprehensive evaluations on nine real-world hypergraph datasets, compared against seven baseline methods, demonstrate the effectiveness of our approach.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130988"},"PeriodicalIF":3.1,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160209","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}

{"title":"From wars to dynamic waves: Scrutinizing connectedness between geopolitical risk index, green and non-green crypto volatility by quantile spillovers","authors":"Le Thanh Ha","doi":"10.1016/j.physa.2025.131001","DOIUrl":"10.1016/j.physa.2025.131001","url":null,"abstract":"<div><div>This research is crucial to determine if green cryptocurrencies are a geopolitical safe-haven or a speculative risk. This finding directly informs investor strategy, guides regulatory policy on financial stability, and advances financial theory by testing if ESG credentials provide resilience against systemic shocks. Our research uses a QVAR methodology to assess the network connectivity of nine metrics, which include the Geopolitical Risks Index (GPR), Cardano (ADA), NANO (XNO), Ripples (XRP), IOTA, Stellar Lumens (XLM), Bitcoin (BTC), Tron (TRX), and Ethereum (ETH). Our results show that when the complete dataset is considered, all of the analyzed variables are very moderately connected. This research specifically displays a temporal change in systemic connection as a result of the COVID-19 pandemic and the dispute between Ukraine and Russia. The results show that changes to the overall network could account for 68.83 % of the volatility in the framework of indicators being investigated. However, this figure has dramatically decreased to 61.47 % and 7.36 % both momentarily and over time. The net total directional connectivity across quantiles indicates that the Geopolitical Risks Index is a net transmitter of shocks throughout the 2020–2021 period below the 20 % quantile, while the Geopolitical Risks Index transmits most of the shocks in 2022 below the 20 % quantile. Ethereum is a primary net transmitter of shocks throughout our sample over quantiles. Dynamic net pairwise directional connectivity over a quantile indicates that unforeseeable occurrences like the COVID-19 outbreak or the tension between Ukraine and Russia affect Geopolitical Risks Indexs and green and non-green cryptocurrencies.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 131001"},"PeriodicalIF":3.1,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222132","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}

{"title":"Spatial dynamics of synchronized ants: A mobile oscillator model analysis","authors":"José F. Fontanari ,&nbsp;Paulo R.A. Campos","doi":"10.1016/j.physa.2025.130990","DOIUrl":"10.1016/j.physa.2025.130990","url":null,"abstract":"<div><div>Synchronized short-term activity cycles are a prominent feature in the nests of certain ant species, but their functional significance remains controversial. This study investigates whether synchronization enhances spatial accessibility within ant nests, a factor critical for efficient task performance and colony fitness. We use the mobile oscillator model, a computational framework that simulates ant movement and synchronous activity, to examine the effect of synchronization on the spatial distribution of inactive ants, which act as obstacles to the movement of active ants. Our analysis reveals no significant effect of synchronization on the size of inactive ant clusters or on direct measures of spatial accessibility, such as the number of steps and net displacement during ant activity periods. These findings suggest that within the mobile oscillator model, synchronization does not directly enhance spatial accessibility, highlighting the need for more complex models to elucidate the intricate relationship between synchronization and spatial dynamics in ant colonies.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130990"},"PeriodicalIF":3.1,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160208","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}

{"title":"Multi-hop centralized seeding strategy for influence maximization in information limited networks","authors":"Bo Gao ,&nbsp;Shiyi Gao ,&nbsp;Xi Wang ,&nbsp;Juan Zhang ,&nbsp;Fanyu Bu ,&nbsp;Yang Liu","doi":"10.1016/j.physa.2025.130967","DOIUrl":"10.1016/j.physa.2025.130967","url":null,"abstract":"<div><div>Maximizing influence in complex social networks represents a fundamental challenge in the field of information dissemination, particularly in real-world scenarios where network topology and propagation mechanisms are often unknown. Traditional methods, which rely on global network information, face significant limitations such as high data acquisition costs and substantial computational complexity, rendering them inadequate for dynamic and unknown networks. To address these challenges, we propose a Multi-Hop Strategy (MHS) framework based on multi-hop perception, which overcomes the limitations of one-hop approaches by integrating the friendship paradox in social networks with human perceptual capabilities. The developed method dynamically selects high-influence seed nodes using local perceptual data, eliminating the need for global topological information. To validate the effectiveness of the proposed framework, extensive experiments are conducted on 12 real world networks spanning diverse domains. Our results show that MHS significantly outperforms four random baseline strategies and the one-hop strategy across most networks, while exhibiting strong robustness to network sparsity and heterogeneity.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130967"},"PeriodicalIF":3.1,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120093","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}

{"title":"Long-range and non-decaying Ising model mapping of effective interactions in multilayer graphene within a microcavity","authors":"Arian Gorza,&nbsp;Facundo Arreyes,&nbsp;Juan Sebastián Ardenghi","doi":"10.1016/j.physa.2025.130927","DOIUrl":"10.1016/j.physa.2025.130927","url":null,"abstract":"<div><div>In this work, the effective interactions of <span><math><mi>N</mi></math></span> graphene layers within a microcavity are analyzed using the Schrieffer–Wolff transformation. Considering the vacuum fluctuations of the cavity field, electrons in different layers get coupled through Heisenberg-type interactions. Applying a mean-field approximation for the ground state energy, we obtain the set of measurable parameters at which the free energy is minimum, and we analyze the critical parameters at which phase transitions occur, where we consider an initial configuration where electrons are randomly distributed in the valence and conduction band. In particular, different geometrical and dynamical configurations are considered, such as <span><math><mi>N</mi></math></span> electrons with identical momentum and alternate momentum and alternate angles. The critical temperature as a function of the electron momentum angles and energies was obtained, showing a nontrivial dependence with the modes of oscillation. Finally, we discuss the critical temperature dependence with respect to the energy gap between electrons in different layers and for random angles.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130927"},"PeriodicalIF":3.1,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120095","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}

{"title":"A physics-based deep learning method for longitudinal trajectories prediction of platoon on highways","authors":"Zeying Ma,&nbsp;Zhihao Zhu,&nbsp;Rongjun Cheng","doi":"10.1016/j.physa.2025.130992","DOIUrl":"10.1016/j.physa.2025.130992","url":null,"abstract":"<div><div>In recent years, with the popularization of autonomous vehicles and the development of vehicle networking technology, the demand for accurate prediction of vehicle behavior has become increasingly urgent. However, most current studies focus on single-vehicle trajectory prediction, lacking effective extraction and capture of vehicle behavior interaction features at the platoon scale. In terms of platoon-level trajectory prediction, especially in traffic fluctuation scenarios, the prediction accuracy still needs to be improved. More importantly, while ensuring high prediction accuracy, it is also necessary not to lose physical interpretability. To this end, this paper proposes a physics-based deep learning network CNN-Int-LSTM-IDM to predict the longitudinal trajectories of all vehicles in a following platoon on a highway. Specifically, the constraints of the physical model are used to prevent the pure data model from generating trajectories that violate physical laws, especially in traffic congestion scenarios, and the physical parameters are calibrated in advance on the trajectory dataset. In addition, this paper adopts a planned sampling mechanism in the model training process to prevent the error from accumulating and propagating over time, while considering the interaction behavior of all vehicles in the entire platoon to optimize the trajectory generation accuracy of the entire platoon. Besides, a convolutional neural network (CNN) is used in advance to extract the interaction features between vehicles in the platoon, and Int-LSTM then processes the temporal dependencies of these features. Finally, the proposed CNN-Int-LSTM-IDM is trained on the highD and NGSIM (Next Generation Simulation) dataset. The prediction experimental results show that the prediction error of CNN-Int-LSTM-IDM is significantly smaller than that of the three baseline models Int-LSTM, CNN-Int-LSTM, and Int-LSTM-IDM. Compared with these three baseline models, the mean square error of CNN-Int-LSTM-IDM on the highD dataset is reduced by 33 %, 21 %, and 18 %, respectively. In addition, in the simulation experiment, the performance of CNN-Int-LSTM-IDM is also more robust.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130992"},"PeriodicalIF":3.1,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120094","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}

{"title":"A new traders’ game? — Empirical analysis of response functions in a historical perspective","authors":"Cedric Schuhmann,&nbsp;Benjamin Köhler,&nbsp;Anton J. Heckens,&nbsp;Thomas Guhr","doi":"10.1016/j.physa.2025.130981","DOIUrl":"10.1016/j.physa.2025.130981","url":null,"abstract":"<div><div>Traders on financial markets generate non-Markovian effects in various ways, particularly through their competition with one another which can be interpreted as a game between different (types of) traders. To quantify the market mechanisms, we empirically analyze self-response functions for pairs of different stocks and the corresponding trade sign correlators. While the non-Markovian dynamics in the self-responses is liquidity-driven, it is expectation-driven in the cross-responses which is related to the emergence of correlations. We empirically study the non-stationarity of these responses over time. In our previous data analysis, we only investigated the crisis year 2008. We now considerably extend this by also analyzing the years 2007, 2014 and 2021. To improve statistics, we also work out averaged response functions for the different years. We find significant variations over time revealing changes in the traders’ game.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130981"},"PeriodicalIF":3.1,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160206","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}

{"title":"Complex system and PS-LSTM prediction of cryptocurrencies, stocks, bonds, exchange rates and commodities","authors":"Yunxiang Wang ,&nbsp;Mohd Fahmi Ghazali ,&nbsp;Ruzanna Ab Razak ,&nbsp;Mohd Azlan Shah Zaidi","doi":"10.1016/j.physa.2025.130976","DOIUrl":"10.1016/j.physa.2025.130976","url":null,"abstract":"<div><div>This study applies Phase Space Reconstruction and Phase Space LSTM to analyze Bitcoin’s interactions with Gold, S&amp;P 500, U.S. Bonds, EUR/USD, and Crude Oil, revealing hidden dependencies and chaotic structures in financial markets. Study implement a multi-method validation framework combining the Rosenstein algorithm for Lyapunov exponent estimation, <span><math><mrow><mn>0</mn><mo>−</mo><mn>1</mn></mrow></math></span> test for chaos and BDS test to provide robust evidence for deterministic chaos. Results indicate that most assets exhibit deterministic chaos, with price evolution highly sensitive to liquidity conditions and macroeconomic forces. Phase space analysis conducted in optimal four-dimensional embeddings uncovers stronger predictive linkages between Bitcoin and U.S. Bonds, reinforcing its growing dependence on global financial conditions. The application of PS-LSTM significantly enhances forecasting accuracy, demonstrated through rigorous validation including statistical significance testing and economic significance evaluation using risk-adjusted performance metrics. These findings suggest that cryptocurrencies are not isolated assets but deeply entangled with systemic financial fluctuations, necessitating a reassessment of market stability and risk propagation through the lens of statistical mechanics and econophysics.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130976"},"PeriodicalIF":3.1,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120096","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}

{"title":"Mixed-wet percolation on a dual square lattice","authors":"Jnana Ranjan Das ,&nbsp;Santanu Sinha ,&nbsp;Alex Hansen ,&nbsp;Sitangshu B. Santra","doi":"10.1016/j.physa.2025.130957","DOIUrl":"10.1016/j.physa.2025.130957","url":null,"abstract":"<div><div>We present a percolation model that is inspired by recent works on immiscible two-phase flow in a mixed-wet porous medium made of a mixture of grains with two different wettability properties. The percolation model is constructed on a dual lattice where the sites on the primal lattice represent the grains of the porous medium, and the bonds on the dual lattice represent the pores in between the grains. The bonds on the dual lattice are occupied based on the two adjacent sites on the primal lattice, which represent the pores where the capillary forces average to zero. The spanning cluster of the bonds, therefore, represents the flow network through which the two immiscible fluids can flow without facing any capillary barrier. It turns out to be a percolation transition of the perimeters of a site percolation problem. We study the geometrical properties at the criticality of the perimeter system numerically. A scaling theory is developed for these properties, and their scaling relations with the respective density parameters are studied. We also verified their finite-size scaling relations. Though the site clusters and their perimeters look very different compared to ordinary percolation, the singular behaviour of the associated geometrical properties remains unchanged. The critical exponents are found to be those of the ordinary percolation.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"679 ","pages":"Article 130957"},"PeriodicalIF":3.1,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110120","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}