Physica A: Statistical Mechanics and its Applications最新文献

{"title":"A link prediction algorithm based on convolutional neural network","authors":"Weilun Chen,&nbsp;Huangrong Zou,&nbsp;Yinzuo Zhou","doi":"10.1016/j.physa.2025.130922","DOIUrl":"10.1016/j.physa.2025.130922","url":null,"abstract":"<div><div>Link prediction is a fundamental problem in complexity science, focusing on forecasting the emergence of new links or identifying missing links within a given network. In this paper, we propose a novel link prediction method named Link Prediction Based on Convolutional Neural Networks (LPCNN). The approach introduces an innovative feature construction technique and leverages the LeNet-LP convolutional neural network architecture, specifically tailored for link prediction tasks. To assess the performance of LPCNN, extensive experiments were conducted on four publicly available datasets. The experimental results demonstrate that the proposed method significantly enhances link prediction accuracy, highlighting its effectiveness and practical applicability.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"678 ","pages":"Article 130922"},"PeriodicalIF":3.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027318","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":"Entropic stochastic resonance of inertial self-propelled particles","authors":"Weihao Yue ,&nbsp;Chaorun Li ,&nbsp;Congju Liu ,&nbsp;Wei Guo ,&nbsp;Luchun Du","doi":"10.1016/j.physa.2025.130907","DOIUrl":"10.1016/j.physa.2025.130907","url":null,"abstract":"<div><div>In recent years, self-propelled particles have been favored by researchers because of their unique dynamical properties and many potential applications. Self-propelled particles with macroscopic size or moving in a gaseous medium typically display underdamped dynamics, which leads to finite relaxation time and inertial delay between the orientation and velocity of the particles. We investigated inertial effects on the entropic stochastic resonance (ESR) by simulating the signal power amplification and the mean free flying time. The self-propulsion velocity and transverse bias force exhibit a double-edged sword effect: while initially enhancing the ESR, further increases ultimately suppress it. Compared with the over-damped system, inertial effects significantly result in the transformation of the response curve from a broad-peak form to a bell-shaped curve. Our results have potential applications for manipulating self-propelled particles whose inertial effects cannot be ignored.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130907"},"PeriodicalIF":3.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144921795","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":"Recurrent neural networks for hierarchical time series forecasting: An application to the S&P 500 market value","authors":"Jackson Ndoto Munyao ,&nbsp;Lillian Achola Oluoch ,&nbsp;Hasnain Iftikhar ,&nbsp;Paulo Canas Rodrigues","doi":"10.1016/j.physa.2025.130869","DOIUrl":"10.1016/j.physa.2025.130869","url":null,"abstract":"<div><div>This paper investigates the use of Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures, for hierarchical time series forecasting in financial markets. Using market value data from the top 70 companies in the S&amp;P 500 index, we evaluate forecasts across three hierarchical levels: company, sector, and market total, applying various reconciliation strategies to ensure coherence. The proposed framework is compared with traditional models (Autoregressive Integrated Moving Average and Exponential Smoothing) under multiple reconciliation methods, including Middle-Out with forecast proportions. Results show that RNN-based models outperform statistical benchmarks in terms of accuracy across levels, particularly when combined with Middle-Out reconciliation. We also discuss practical aspects such as computational cost and implementation trade-offs, highlighting the relevance of deep learning methods for structured financial forecasting tasks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"678 ","pages":"Article 130869"},"PeriodicalIF":3.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989520","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":"Parity-breaking Ising-like model with Spin-Exchange dynamics","authors":"A. Arul Anne Elden ,&nbsp;M. Ponmurugan","doi":"10.1016/j.physa.2025.130938","DOIUrl":"10.1016/j.physa.2025.130938","url":null,"abstract":"<div><div>We investigate a parity-breaking Ising-like model with Spin-Exchange dynamics using Wang–Landau algorithm. The computed density of states permits the analysis of thermodynamic observables in equilibrium and transport behavior analogous to symmetric simple exclusion process. We observed a density dependent phase transition, where the transition temperature having a minimum at a critical density <span><math><mrow><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub><mo>≈</mo><mn>0</mn><mo>.</mo><mn>4</mn></mrow></math></span>. Below <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span> the system shows a diffusive and weakly localized behavior, while above <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span> strongly localized behavior due to the particle mobility. The parity breaking term increases the fluctuations in particle current at <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>, which suggests competing transport mechanisms. The spin exchange dynamics alone can induce a non zero particle current even in equilibrium. As temperature increases, the particle current behavior transits from an oscillatory regime to a steady state where transport is stabilized. Furthermore, the increase of the parity breaking interaction parameter raises the transition temperature (<span><math><msub><mrow><mi>T</mi></mrow><mrow><mi>C</mi></mrow></msub></math></span>), which supports the role of interaction driven effects. The specific heat capacity for different number of particles diverges near <span><math><msub><mrow><mi>T</mi></mrow><mrow><mi>C</mi></mrow></msub></math></span>. The canonical energy distribution shows single-peaked distribution, combined with this continuous energy change and entropy change, and divergence near <span><math><msub><mrow><mi>T</mi></mrow><mrow><mi>C</mi></mrow></msub></math></span> in specific heat confirms a second order phase transition.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130938"},"PeriodicalIF":3.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144919663","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":"Two-state paramagnetism: The effect of temperature fluctuations","authors":"Nassima Adimi ,&nbsp;Kamel Ourabah","doi":"10.1016/j.physa.2025.130926","DOIUrl":"10.1016/j.physa.2025.130926","url":null,"abstract":"<div><div>In this Letter, we investigate the impact of temperature fluctuations on the induced magnetization of a simple paramagnetic two-state system. These fluctuations are considered within the framework of superstatistics. We specifically examine three temperature distributions resulting from additive or multiplicative random processes: the <span><math><msup><mrow><mi>χ</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>, inverse-<span><math><msup><mrow><mi>χ</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>, and log-normal distributions. Our analysis reveals that fluctuations generally lead to a reduction in magnetization and an increase in mean energy compared to scenarios without fluctuations. In essence, these fluctuations act as an effective temperature.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130926"},"PeriodicalIF":3.1,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917908","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 flocking to condensation: Collective dynamics in binary chiral active matter","authors":"Divya Kushwaha,&nbsp;Shradha Mishra","doi":"10.1016/j.physa.2025.130897","DOIUrl":"10.1016/j.physa.2025.130897","url":null,"abstract":"<div><div>Many microswimmers are inherently chiral, and this chirality can introduce fascinating behaviors in a collection of microswimmers. The dynamics become even more intriguing when two types of microswimmers with distinct chirality are mixed. Our study examines a mixture of self-propelled particles with opposite chirality, investigating how the system’s characteristics evolve as the magnitude of chirality is varied. In weakly chiral systems, the particles exhibit similar behavior, leading to a globally flocking phase where both types of particles are well-mixed. However, in an intermediate range of chirality, the condensates of different particles are formed as a result of a competition between chirality and self-propulsion. This competition results in interesting phases within the system. We explore the characteristics of these distinct phases in detail, focusing on the roles of self-propulsion speed and chirality.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130897"},"PeriodicalIF":3.1,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913944","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":"Decision model based on driving-mode misidentification for mixed AV–HDV straight–left conflict interactions at two-phase signalized intersections","authors":"Jiawen Wang ,&nbsp;Liping Zhou ,&nbsp;Chengcheng Yang","doi":"10.1016/j.physa.2025.130943","DOIUrl":"10.1016/j.physa.2025.130943","url":null,"abstract":"<div><div>The coexistence of autonomous vehicles (AVs) and human-driven vehicles (HDVs) has complicated the interaction between left-turning and straight-moving vehicles at intersections. Existing studies predominantly assumed the type of interacting vehicle was known, failing to account for the uncertainty in the identification of vehicle types by human drivers and their differentiated decision-making toward AVs versus HDVs. This study explores the potential impact of AVs on driver decision-making by proposing a hybrid game-based dynamic decision-making framework for human-machine mixed driving at intersections, simulating the challenges human drivers face in identifying interacting vehicle types and the interactive behaviors under different vehicle combinations in mixed-traffic flows, thereby revealing the potential influence of AVs on human decisions and mixed-traffic flows. Case analyses indicate that 1) accurate identification of AVs by human drivers can reduce average vehicle delay by 30 % and collision risk by 54.4 %, with higher interaction efficiency observed when the left-turning vehicle is an HDV; and 2) as AV penetration rates and driver recognition accuracy improve, vehicle delay and collision risk decrease significantly, with the enhancement of recognition accuracy exhibiting the most pronounced effect on intersection performance at low AV penetration rates. This study provides a novel theoretical framework for analyzing vehicle interaction mechanisms in complex mixed-traffic environments during the early stages of AV adoption, offering new theoretical foundations for addressing straight-left conflicts at intersections in mixed driving conditions.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130943"},"PeriodicalIF":3.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926208","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":"The event-triggered scaled consensus of multi-agent systems with semi-Markov switching topologies under partially unknown rates","authors":"Binbin Tian ,&nbsp;Hui Peng ,&nbsp;Tiao Kang","doi":"10.1016/j.physa.2025.130921","DOIUrl":"10.1016/j.physa.2025.130921","url":null,"abstract":"<div><div>For multi-agent systems(MASs), the continuous information interaction behavior between agents is normally necessary for acquiring the control feedback at each operating instant, allowing for achieving the scaled consensus in the presence of switching topologies randomly. However, consecutive communication results in high resource consumption due to frequent updating of the controllers, which poses a challenge in scenarios with limited communication resources. To address this issue, a novel error-based event-triggering scheme(ETS) with a sampling-periodic framework is developed. This ETS is formulated by defining a group of error terms, with the purpose of ensuring that the agents in MASs can realize the scaled consensus performance with either the average or proportional values, while effectively reducing the frequency of information broadcasting among agents. Specifically, the scaled consensus problem is initially transformed into a stability consideration of the reduced-order system through model transformation. Additionally, the transition rate(Tr) in semi-Markov switching process(SMSP) is considered to be incompletely unknown to capture more topology random dynamics due to the unexpected nature of the actual environment, facilitating to derive the stability conditions with reduced conservatism. And the sufficient conditions(SCs) of event-triggered scaled consensus(ETSC) are obtained in terms of linear matrix inequalities(LMIs) by employing the Lyapunov functions appropriately. Meanwhile, the scaled consensus controller(SCC) and the event-triggered matrices(ETMs) in ETS with switching sequence of topology are co-designed efficaciously to manage both the agent’s behavior and its triggering frequency. Finally, the feasibility of theoretical results is verified by using a numerical example, and the comparative results demonstrate the effectiveness of proposed method in this paper.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130921"},"PeriodicalIF":3.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913945","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":"Role of spatial embedding and planarity in shaping the topology of the Street Networks","authors":"Aradhana Singh ,&nbsp;Ritish Khetarpal ,&nbsp;Amod Rai","doi":"10.1016/j.physa.2025.130901","DOIUrl":"10.1016/j.physa.2025.130901","url":null,"abstract":"<div><div>The topology of city street networks (SNs) is bounded by spatial embedding, which enforces non-crossing links and prohibits random node placement or overlap. This raises a fundamental question: how do such spatial constraints shape network topology? To address this, we analyze the SNs of 33 Indian cities. All studied networks exhibit small-world properties characterized by high clustering and efficiency. Notably, the efficiency of the empirical networks exceeds that of corresponding degree-preserved random networks. This elevated efficiency is attributed to the right-skewed distribution of Dijkstra’s path lengths, a pattern also observed in random planar networks. While the average Dijkstra path length scales with the mean street length, the overall distribution is more strongly influenced by geometric structure and planarity than by scaling alone. Furthermore, we observe a clear preference for length-based connectivity: shorter streets preferentially connect to other short streets and longer ones to longer counterparts, which is more pronounced in empirical SNs than in degree-preserved or random planar networks. However, planar networks, preserving the spatial coordinates of empirical networks, replicate this connectivity pattern, pointing to the role of spatial embedding. Finally, the resilience of the Indian SNs to edge-based random errors and targeted attacks remains independent of the SN’s size, indicating that other factors, such as geographical constraints, substantially influence network stability. Our findings provide insights into how spatial constraints shape the topology and function of urban street networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130901"},"PeriodicalIF":3.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913941","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":"Impact of the spatial distribution of CAVs on stochastic traffic oscillations in mixed traffic flow","authors":"Zeqi Xu ,&nbsp;Yi Wang ,&nbsp;Ronghui Liu ,&nbsp;Yunxia Wu ,&nbsp;Yangsheng Jiang ,&nbsp;Zhihong Yao","doi":"10.1016/j.physa.2025.130940","DOIUrl":"10.1016/j.physa.2025.130940","url":null,"abstract":"<div><div>Existing studies have demonstrated the potential of Connected and Automated Vehicles (CAVs) to optimise traffic flow and suppress disturbances. However, most current mixed traffic flow models adopt idealised deterministic approaches for modelling Human-Driven Vehicles (HDVs), and overlook the influence of the spatial distribution of CAVs on system performance. To address these limitations, this study introduces a novel metric (i.e., platoon intensity) to quantify the spatial clustering characteristics of CAVs within mixed traffic flow. This indicator enables a unified characterisation of CAV distribution patterns across various penetration rates, and theoretical bounds on pairwise vehicle probabilities under different traffic conditions are derived accordingly. A mixed traffic flow model is further developed, incorporating stochastic car-following behaviour of HDVs, behavioural degradation of CAVs, and a constraint on maximum platoon size. By introducing stochastic differential equations, the model successfully reproduces velocity fluctuations triggered by endogenous disturbances. Based on this framework, a series of systematic numerical experiments are conducted to comprehensively analyse traffic efficiency, stability, and energy consumption under varying CAV penetration rates and spatial distribution patterns. A quantitative relationship is established between platoon intensity and macroscopic traffic performance indicators. The main findings of this paper are as follows: (1) The spatial distribution of vehicles significantly impacts macroscopic traffic performance, with maximum differences of 9.70 %, 145.20 %, and 7.58 % observed in average speed, coefficient of variation of speed, and average energy consumption, respectively. (2) At a fixed CAV penetration rate, increasing platoon intensity enhances traffic efficiency and reduces average energy consumption, but exacerbates traffic instability. This research provides theoretical insights and practical implications for future CAV deployment strategies and traffic management measures.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130940"},"PeriodicalIF":3.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895944","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}