Physica A: Statistical Mechanics and its Applications最新文献

{"title":"Synchronization transition induced in a partial resetting oscillator system with adaptive coupling","authors":"Tianyu Li,&nbsp;Ying Xie,&nbsp;Dong Yu,&nbsp;Yipeng Hu,&nbsp;Ya Jia,&nbsp;Lijian Yang","doi":"10.1016/j.physa.2025.130903","DOIUrl":"10.1016/j.physa.2025.130903","url":null,"abstract":"<div><div>Explosive synchronization has gained significant attention due to its potential applications in understanding complex dynamic systems. This study systematically examines the impacts of partial resetting and adaptive coupling on the synchronization transition in globally coupled Kuramoto oscillators by employing the self-consistent equation and Ott-Antonsen ansatz under three scenarios. The critical coupling strength is determined by the stability of the incoherent solution. Near the critical coupling strength, perturbation analysis reveals that a sufficient resetting proportion is key to inducing explosive synchronization. A non-zero mean of the oscillator's natural frequency distribution is the next dominant factor of explosive synchronization. Increasing the resetting frequency shrinks the hysteresis region, which may ultimately yield a continuous transition. The numerical simulations align well with theoretical analysis.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130903"},"PeriodicalIF":3.1,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827727","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":"Modeling mixed traffic stability with connected automated vehicle platoon","authors":"Yunxia Wu,&nbsp;Qiufan Gu,&nbsp;Yangsheng Jiang,&nbsp;Zhihong Yao","doi":"10.1016/j.physa.2025.130905","DOIUrl":"10.1016/j.physa.2025.130905","url":null,"abstract":"<div><div>To investigate the impact of platoon characteristic parameters on the mixed traffic stability, this paper proposes a mixed traffic stability analysis framework that considers both maximum platoon size and platoon intensity. First, considering the spatial distribution of vehicles in mixed traffic flow, a Markov chain-based platoon model is developed from the perspective of platoon intensity. Considering the platoon, the vehicle types and proportions in the mixed traffic flow have been determined. Then, stability discriminant criteria for mixed traffic flow considering both maximum platoon size and platoon intensity are derived, and the effects of maximum platoon size, platoon intensity, and CAV penetration rate on traffic stability are analyzed. Finally, simulation experiments are designed to validate the theoretical model. The results indicate that (1) platoon intensity positively affects mixed traffic stability. As platoon intensity increases, the stable speed intervals of mixed traffic flow expand. (2) The smaller platoons are beneficial to the traffic stability. As the platoon size increases, the unstable speed intervals expand while the expansion rate slows down, but its effect depends on platoon intensity. (3) Platoon management modes can enhance mixed traffic stability compared to conventional management modes. The stability is optimal when all CAVs travel in platoons of a certain size. Therefore, the findings of this paper guide platoon management in mixed traffic flow.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130905"},"PeriodicalIF":3.1,"publicationDate":"2025-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827726","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 influence of entropic forces and pressure on the motion of a topological soliton in a carbon nanotube lying on a flat substrate","authors":"Alexander V. Savin","doi":"10.1016/j.physa.2025.130878","DOIUrl":"10.1016/j.physa.2025.130878","url":null,"abstract":"<div><div>With the help of the molecular mechanics method it is shown that for each flat substrate there is a definite interval of diameters at which single-walled carbon nanotubes on the substrate are bistable. They have two stable stationary states: open and closed (collapsed) states. With the help of molecular dynamic modeling it is shown that the transition region between these states in the nanotube is spatially localized and has the properties of a topological soliton (kink or antikink). The soliton dynamics can be described as the directional motion of a quasiparticle in a viscous medium under the action of three forces: a constant force related to the energy difference of the stationary states, an entropic force that depends linearly on temperature and force associated with external hydrostatic pressure (this force always acts against the entropic force). The magnitude of the velocity and direction of motion of the soliton depend on the diameter of the nanotube, on the temperature of the thermostat (temperature increase can lead to a change in the direction of motion) and on the pressure. It is shown that a one-dimensional model of a harmonic chain lying in a double-well asymmetric potential can be used to describe the soliton motion.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130878"},"PeriodicalIF":3.1,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828286","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":"Synergistic effects of spatial connections in shaping social contagions on higher-order lattice networks","authors":"Anbin Liu,&nbsp;Wenbin Gu,&nbsp;Tao Yang,&nbsp;Lanzhi Deng,&nbsp;Fangjun Chen,&nbsp;Wei Wang","doi":"10.1016/j.physa.2025.130877","DOIUrl":"10.1016/j.physa.2025.130877","url":null,"abstract":"<div><div>Extensive studies revealed that the spatial networks exhibits low-order (pairwise interaction) and higher-order interaction (multiple interaction), which markedly affect the spreading dynamics. However, theoretical studies about the synergistic effects of the two interactions shaping social contagions (e.g., behavior spreading) are still lacking. To this end, we propose a social contagion model to describe the behavior dynamics on higher-order lattice networks. Through extensive simulations and the finite-size scaling method, the giant connected cluster of the global behavior adoption exhibits discontinuous and continuous phase transitions, which depend on the spatial network structures. Specifically, the system exhibits a discontinuous (continuous) phase transition when there are many long-range (short-range) hyperedges. We further calculate the relative contribution ratio of low-order and high-order contagions contributed by the two types of interactions, and reveal four distinct regions: Region I and Region IV exhibit absolute dominance of higher-order and low-order spread, respectively; Region II displays relative dominance of higher-order spread, while Region III shows relative dominance of low-order spread. A reduction in the low-order contagion threshold decreases the critical mass for the global behavior adoption, enhances the relative contributions of low-order contagion, and leads to an expansion of Region IV and a contraction of Region I.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130877"},"PeriodicalIF":3.1,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828287","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 predictive failure indicator to detect impending macroscopic fracture during compression in ultra high performance concrete","authors":"Kashif Naukhez,&nbsp;R. Vidya Sagar,&nbsp;J.M. Chandra Kishen","doi":"10.1016/j.physa.2025.130879","DOIUrl":"10.1016/j.physa.2025.130879","url":null,"abstract":"<div><div>In recent years, there has been growing interest in applying statistical physics principles to understand the fracture behaviour in cementitious materials. This approach provides valuable insights into the underlying mechanisms governing the material response under stress. In this study, an experimental investigation was conducted to study the compressive fracture process in ultra-high-performance concrete (UHPC) under the framework of non-extensive statistical mechanics (NESM). The acoustic emission (AE) waveform parameters were recorded during compressive loading. The occurrence of AE inter-event time of successive hits was analysed using a <span><math><mi>q</mi></math></span>-exponential function. We examined a descriptor known as the Tsallis entropic index or <span><math><mi>q</mi></math></span>-index and correlated its variation with damage progression in UHPC at various loading stages. A <span><math><mi>q</mi></math></span>-index greater than unity indicated long-range microcrack interactions, while a <span><math><mi>q</mi></math></span> approaching unity suggested enhanced short-range interactions. The toughening mechanism provided by steel fibres and coarse aggregate enhances long-range microcrack interaction forces by redistributing stresses over a larger area, resulting in an increased <span><math><mi>q</mi></math></span>-index. Conversely, a decrease in <span><math><mi>q</mi></math></span>-index towards unity was associated with the transition from long-range to short-range interaction forces, leading to macroscopic failure, aligned with Boltzmann–Gibbs statistics. Therefore, the <span><math><mi>q</mi></math></span>-index could be used as a predictive failure indicator to detect imminent failure of cementitious materials.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130879"},"PeriodicalIF":3.1,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827630","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":"Supervised and unsupervised protocols for hetero-associative neural networks","authors":"Andrea Alessandrelli ,&nbsp;Adriano Barra ,&nbsp;Andrea Ladiana ,&nbsp;Andrea Lepre ,&nbsp;Federico Ricci-Tersenghi","doi":"10.1016/j.physa.2025.130871","DOIUrl":"10.1016/j.physa.2025.130871","url":null,"abstract":"<div><div>This paper introduces a learning framework for Three-Directional Associative Memory (TAM) models, extending the classical Hebbian paradigm to both supervised and unsupervised protocols within an hetero-associative setting. These neural networks consist of three interconnected layers of binary neurons interacting via generalized Hebbian synaptic couplings that allow learning, storage and retrieval of structured triplets of patterns. By relying upon glassy statistical mechanical techniques (mainly replica theory and Guerra interpolation), we analyze the emergent computational properties of these networks, at work with random (Rademacher) datasets and at the replica-symmetric level of description: we obtain a set of self-consistency equations for the order parameters that quantify the critical dataset sizes (i.e. their thresholds for learning) and describe the retrieval performance of these networks, highlighting the differences between supervised and unsupervised protocols. Numerical simulations validate our theoretical findings and demonstrate the robustness of the captured picture about TAMs also at work with structured datasets. In particular, this study provides insights into the cooperative interplay of layers, beyond that of the neurons within the layers, with potential implications for optimal design of artificial neural network architectures.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130871"},"PeriodicalIF":3.1,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828284","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":"Modeling territorial disputes with Hawk–Dove games","authors":"Daniel Rodrigues ,&nbsp;Ian Braga ,&nbsp;Lucas Wardil","doi":"10.1016/j.physa.2025.130875","DOIUrl":"10.1016/j.physa.2025.130875","url":null,"abstract":"<div><div>We investigate the evolutionary dynamics of territorial contests by extending the classical Hawk–Dove game to explicitly incorporate site exchange into the game’s payoff structure. In our model, individuals occupy sites on a square lattice, with a fixed fraction designated as high-value territories that confer fitness benefits. Territorial disputes are resolved through Hawk–Dove interactions, and site occupation changes accordingly. Our analysis shows that, although the average payoff matrix remains the same as in traditional models, coupling of payoff determination with site exchanges reduces the prevalence of non-aggressive strategies. We also examine how the spatial distribution of valuable sites affects outcomes, showing that structured patterns – such as chessboard-like arrangements – can sustain Doves under specific dynamic regimes. Furthermore, when both Hawks incur conflict costs, Doves can persist even in resource-rich environments. These findings highlight the importance of coupling mobility, spatial structure, and payoff mechanisms in understanding the evolution of conflict and cooperation in territorial systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130875"},"PeriodicalIF":3.1,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860741","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 k-shell decomposition structural entropy of complex networks","authors":"Yishu Xian ,&nbsp;Meizhu Li ,&nbsp;Qi Zhang","doi":"10.1016/j.physa.2025.130859","DOIUrl":"10.1016/j.physa.2025.130859","url":null,"abstract":"<div><div>Structural entropy is a powerful tool for quantifying the structural complexity of complex networks and answering the question of how complex these networks are. In this paper, a new structural entropy measure for complex networks, based on the k-shell method, is proposed to fill the gaps left by traditional node-based structural entropy and statistical physics entropy, quantifying the structural complexity of networks based on the distribution of nodes among different shells. The effectiveness of k-shell decomposition structural entropy is validated in networks with different structures generated by the Erdős–Rényi and Barabási–Albert models. We find that networks generated by the Barabási–Albert model tend to have higher k-shell decomposition structural entropy. In contrast, networks generated by the Erdős–Rényi model exhibit oscillations in k-shell decomposition structural entropy, which gradually stabilize as the network size increases. We also find that the frequency of these oscillations in the k-shell decomposition structural entropy for networks generated by the Erdős–Rényi model is related to the linking probability in the model. These oscillations arise due to ’phase transitions’ in the distribution of nodes among shells during the network’s growth process, a phenomenon distinct from existing entropy measures of complex networks. This finding shows that the proposed k-shell decomposition structural entropy is fundamentally different from degree-based and betweenness-based structural entropy. Additionally, the k-shell decomposition structural entropy has been applied to measure the structural complexity of real-world networks. We find that even though the Yeast Interaction network and the Twitter social network have different sizes and originate from different systems, they exhibit very similar k-shell decomposition structural entropy. In other words, the k-shell decomposition structural entropy provides unique insights into structural changes during network growth. Unlike traditional measures, k-shell decomposition structural entropy is not extensive with network size growth and focuses on the shell-topological structure of networks. All of these results demonstrate that the k-shell decomposition structural entropy is a new and useful tool for the structural analysis of complex networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130859"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893299","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":"Learning phase transitions by siamese neural network","authors":"Jianmin Shen ,&nbsp;Shiyang Chen ,&nbsp;Feiyi Liu ,&nbsp;Wei Li ,&nbsp;Youju Liu","doi":"10.1016/j.physa.2025.130857","DOIUrl":"10.1016/j.physa.2025.130857","url":null,"abstract":"<div><div>The wide application of machine learning (ML) techniques in statistics physics has presented new avenues for research in this field. In this paper, we introduce a semi-supervised learning method based on Siamese Neural Networks (SNN), trying to explore the potential of neural network (NN) in the study of critical behaviors beyond the approaches of supervised and unsupervised learning. By focusing on the (1+1) dimensional bond directed percolation (DP) model of nonequilibrium phase transition and the 2 dimensional Ising model of equilibrium phase transition, we use the SNN to predict the critical values and critical exponents of the systems. Different from traditional ML methods, the input of SNN is a set of configuration data pairs and the output prediction is similarity, which prompts to find an anchor point of data for pair comparison during the test. In our study, during test we set different bond probability <span><math><mi>p</mi></math></span> or temperature <span><math><mi>T</mi></math></span> as anchors, and discuss the impact of the configurations at this anchors on predictions. In addition, we use an iterative method to find the optimal training interval to make the algorithm more efficient, and the prediction results are comparable to other ML methods.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130857"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842667","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":"Phase diagram of the antiferromagnetic 3-state Potts model on a bcc lattice with competing interactions","authors":"D.R. Kurbanova,&nbsp;M.A. Magomedov,&nbsp;M.R. Dzhamaludinov,&nbsp;M.K. Ramazanov,&nbsp;A.K. Murtazaev","doi":"10.1016/j.physa.2025.130870","DOIUrl":"10.1016/j.physa.2025.130870","url":null,"abstract":"<div><div>The antiferromagnetic 3-state Potts model on a body-centered cubic lattice with competing interactions of the first (<em>J</em>₁) and second (<em>J</em>₂) nearest-neighbor was studied by the Monte Carlo method. A phase diagram was plotted. The competition of exchange interactions in the range −2/3 &lt; <em>J</em>₂ &lt; 0 was determined to result in a phase separation. In the low-temperature region, an ordered phase, lying inside the phase with broken sublattice symmetry, was found. The second nearest-neighbor interactions leads to a change in the phase transition order. In addition, at <em>J</em>₂ ≤ −2/3, a phase with broken sublattice symmetry state of a different type arises. Such features are not observed at the ferro-antiferromagnetic interaction. The critical exponents for the second-order phase transition are estimated using scaling relations.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"676 ","pages":"Article 130870"},"PeriodicalIF":3.1,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828283","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}