Physica A: Statistical Mechanics and its Applications最新文献

{"title":"Exploring asymmetric and symmetric pedestrian merging dynamics: Macro parameters and micro behavioral adaptations from single-file experiment","authors":"Hanchen Yu ,&nbsp;Nan Jiang ,&nbsp;Dongli Gao ,&nbsp;Jixin Shi ,&nbsp;Hongyun Yang ,&nbsp;Eric Wai Ming Lee ,&nbsp;Lizhong Yang","doi":"10.1016/j.physa.2025.130925","DOIUrl":"10.1016/j.physa.2025.130925","url":null,"abstract":"<div><div>Pedestrian merging flow is a critical aspect of urban mobility, shaping movement efficiency and safety in complex environments. Collective crowd behaviors are induced by complex local interactions among individuals. For a better understanding of pedestrian merging dynamics, it is necessary to further explore microscopic individual adaptations during the merging process as well as their potential impacts on macroscopic movement patterns that affect merging performance. This study conducts controlled experiments to investigate pedestrian merging behaviors in T-shaped single-file scenarios, comparing both asymmetric and symmetric layouts (differing in flow directions) under varying flow and speed levels. Macroscopic parameters (e.g., average velocity, merging path distance) and microscopic parameters (e.g., lateral deviation, headway distance, stepping characteristics) are analyzed, and the interconnections are discussed. Key findings reveal that the inconsistent upstream velocity adaptation could affect merging velocity, where a faster velocity decay and shorter adaptation time result in lower merging velocity. Variability in upstream lateral deviations contributes to discrepancies in merging paths, with greater lateral deviation leading to more pronounced merging path reductions. It is inferred that velocity adaptation is linked to deceleration strategies involving stepping dynamics (e.g., step length, step frequency), while lateral deviation originates from pedestrians’ preferences for the shortest-distance and right-side bias. Furthermore, a negative correlation is identified between the stability of lateral deviation and velocity decay in both symmetric and asymmetric layouts. Those results address specific correlations between macro parameters and micro behavioral adaptations during the merging process, which might create disparities of movement states and induce latent higher density and delays. This work provides insights into pedestrian merging behaviors from a new perspective, with applications in enhancing pedestrian flow designs and safety management strategies.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130925"},"PeriodicalIF":3.1,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903735","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 effects of cortical inputs on the oscillation and synchronization of the basal ganglia","authors":"Bei Bai ,&nbsp;Xia Shi ,&nbsp;Zihan Li","doi":"10.1016/j.physa.2025.130900","DOIUrl":"10.1016/j.physa.2025.130900","url":null,"abstract":"<div><div>The basal ganglia (BG) is critical for motor control, and its rhythmic oscillation is closely linked to movement disorders such as Parkinson’s disease (PD) etc. This study applied a dynamic model of the cortex (CTX) - BG network to investigate how distinct cortical inputs modulated network oscillations and synchronization of BG by focusing on the output activity of the internal globus pallidus (GPi). Cross-correlation analysis revealed that chattering-type cortical neurons produced the strongest resonance with GPi (correlation coefficient up to 0.52), especially when oscillating in the beta frequency band. Among the three major pathways, the direct pathway exerted the greatest influence on GPi oscillations (influence index <span><math><mi>R</mi></math></span> = 24.1), compared to the indirect and hyperdirect pathways. Principal component analysis showed that increasing the strength of the cortico-striatal connection enhanced GPi synchrony, and pathological input could trigger PD-like pathological beta oscillations. Importantly, selective disruption of cortical input to D1-type medium spiny neuron (D1-MSN) markedly reduced pathological oscillations in GPi, which suggested it was a potential therapeutic strategy. Specifically, our results revealed that targeted reduction of cortical input to the direct pathway might represent a novel therapeutic approach for attenuating pathological <span><math><mi>β</mi></math></span> synchronization in PD. These findings quantitatively elucidate how cortical input patterns and pathways regulate BG output, which provides new insights for targeted interventions in movement disorders.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130900"},"PeriodicalIF":3.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896451","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-scale trajectory reconstruction for freeway traffic via deep reinforcement learning under heterogeneous data","authors":"Yuhang Gao ,&nbsp;Jiandong Zhao ,&nbsp;Zhixin Yu ,&nbsp;Honglu Cao ,&nbsp;Meng Liu","doi":"10.1016/j.physa.2025.130904","DOIUrl":"10.1016/j.physa.2025.130904","url":null,"abstract":"<div><div>Precise vehicle trajectory data is essential for traffic flow modeling, trajectory prediction, and energy consumption estimation. However, fixed detectors yield only sparse point-based observations, while mobile detectors such as probe vehicles (PVs) provide complete but low-frequency trajectories, making it difficult to directly capture full vehicle trajectories. To address this challenge, this study proposes a multi-scale trajectory reconstruction framework that focuses on lane-level spatiotemporal trajectories, leveraging macroscopic traffic states to guide the reconstruction of microscopic vehicle trajectories via deep reinforcement learning (DRL). First, an improved adaptive smoothing algorithm is developed to address data imbalance between fixed and mobile detectors, constructing a macroscopic velocity field that serves as both the decision environment and the reward reference for the DRL agent. Second, based on the two-dimensional intelligent driver model (2D-IDM) and its extended version, a set of bidirectional candidate trajectories incorporating driver stochasticity is generated by jointly considering the upstream and downstream PV behaviors, providing physically plausible microscopic priors. The DRL agent then learns an optimal trajectory fusion policy by minimizing the deviation between the fused velocity and the macroscopic field. The proposed framework is evaluated on NGSIM dataset under both free-flow and congested conditions. Experimental results show that the proposed method reduces speed errors by over 30.97 % and position errors by more than 20.12 % compared to baseline models, consistently achieving superior accuracy, stability, and generalization.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130904"},"PeriodicalIF":3.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888871","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":"Information capacitance in Ni2MnGa Heusler alloy: A study of the martensitic transformation","authors":"Giulio Arias ,&nbsp;Hans Nowak ,&nbsp;Alejandro A. Heredia-Guevara ,&nbsp;Justiniano Quispe-Marcatoma ,&nbsp;Víctor A. Peña-Rodríguez ,&nbsp;Carlos V. Landauro","doi":"10.1016/j.physa.2025.130913","DOIUrl":"10.1016/j.physa.2025.130913","url":null,"abstract":"<div><div>Information capacitance is a new measure of complexity that is applicable, in principle, to an arbitrary physical system, which makes it interesting for the study of systems near phase transitions. In this context, the Ni<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>MnGa Heusler alloy is of special interest as it exhibits two coupled phase transitions (structural and magnetic). Thus questions arise about how each of them contributes to the complexity of the system; i.e., to the information capacitance. To answer this question, we employ a Hamiltonian model together with a Monte Carlo-Metropolis procedure to calculate the magnetization, the tetragonal (structural) distortion and, mainly, the entropy of the system, since the latter quantity is associated with the information capacitance. The Hamiltonian has three parts: magnetic, elastic (where the Blume–Emery–Griffiths model is used to describe the degree of freedom of the atomic displacements in the lattice), and the magnetoelastic part (which accounts for the interdependence of the magnetic and elastic subsystems). Additionally, entropies (total and partial) were calculated using the interrelation between the thermal entropy, calculated by the specific heat, and the Gibbs definition to study the effects of correlation on the phase transformations that are included in the Monte Carlo calculations. The results show that each phase transition contributes differentially to the correlation, depending on the temperature. This allows us to analyze, for example, the degree of coupling between the magnetic and structural subsystems during different stages of the martensitic phase transitions present in the Ni<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>MnGa system. By extension, this richness of analysis is inherited by the information capacitance. Furthermore, this measure of complexity, along with its marginal form (C<span><math><msub><mrow></mrow><mrow><mi>s</mi><mi>u</mi><mi>m</mi></mrow></msub></math></span>), highlights the distinct phase transitions within the considered magneto-structural model.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130913"},"PeriodicalIF":3.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913942","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":"Data-driven configurable scenario generation for testing autonomous driving systems in highway environments","authors":"Cheng Wei ,&nbsp;Kenan Mu ,&nbsp;Fei Hui ,&nbsp;Asad Jan Khattak","doi":"10.1016/j.physa.2025.130923","DOIUrl":"10.1016/j.physa.2025.130923","url":null,"abstract":"<div><div>Human-like traffic flow provides a test environment suitable for evaluating the safety of autonomous driving systems. Currently, simulation testing based on data injection faces the problems of small data volumes and high acquisition costs. Although previous studies have been conducted on scenario generation, the following shortcomings remain: the inability to conduct continuous-scenario generation, lack of real-time simulations, and reliance on simulations oriented toward a single-function scenario. To address these shortcomings, this study proposed the concept of behavior incentives as a basis for configurable continuous-scenario generation. First, to better extract the behavioral characteristics of a vehicle, a sampling method was proposed to dimensionally homogenize vehicles’ sequence data. Second, using these processed data, the type of behavior incentive and its numerical format were determined, and a unified behavior incentive framework was developed and populated. Additionally, to complete the lane changing information in the behavior incentive, the vehicle motion and trajectory data were resampled, a velocity-trajectory generation neural network was proposed, and the lane changing trajectory for the behavior incentive framework was generated. After completing all behavior incentive frames, the proposed method was simulated in real time using the Simulation of Urban Mobility traffic-flow simulation software, and the key parameters and functions of the simulation were identified. The simulation results show that the proposed method can not only effectively generate continuous test scenarios, but can also facilitate the addition and modification of parameters to generate configurable test scenarios comprising different states, providing an excellent basis for testing autonomous driving systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130923"},"PeriodicalIF":3.1,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895943","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":"Optimum performance characteristics and maximum power output of a low-dissipation quantum heat engine","authors":"Jingyi Chen ,&nbsp;Junyi Wang ,&nbsp;Yuzhuo Pan ,&nbsp;Shanhe Su ,&nbsp;Jincan Chen","doi":"10.1016/j.physa.2025.130916","DOIUrl":"10.1016/j.physa.2025.130916","url":null,"abstract":"<div><div>This study presents a low-dissipation quantum heat engine cycle and analyzes its performance characteristics. Based on the slow driven perturbation theory, the analytic expansion of heat in powers of time is derived. Employing the method of Lagrange multiplier, we establish a constraint relation between the efficiency and the power output. The performances of the low-dissipation heat engine are optimally analyzed by considering the different objective functions. The results underscore the significance of operating the low-dissipation quantum heat engine cycle within the optimal region to attain the large power output and high efficiency simultaneously. These findings contribute to the understanding and optimization of low-dissipation quantum heat engines, providing insights for the development of efficient energy conversion technologies.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130916"},"PeriodicalIF":3.1,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913943","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 mathematical model of delay discounting with bi-faceted impulsivity","authors":"Shanu Shukla ,&nbsp;Trambak Bhattacharyya","doi":"10.1016/j.physa.2025.130891","DOIUrl":"10.1016/j.physa.2025.130891","url":null,"abstract":"<div><div>Existing mathematical models of delay discounting (e.g., exponential model, hyperbolic model, and those derived from nonextensive statistics) consider impulsivity as a single quantity. However, the present article derives a novel mathematical model of delay discounting considering impulsivity as a multi-faceted quantity. It considers impulsivity to be represented by two positive and fluctuating quantities (e.g., these facets may be trait and state impulsivity). To derive the model, the superstatistics method, which has been used to describe fluctuating physical systems like a thermal plasma, has been adapted. According to the standard practice in behavioural science, we first assume that the total impulsivity is a mere addition of the two facets. However, we also explore the possibility beyond an additive model and conclude that facets of impulsivity may also be combined in a nonadditive way. We name this group of models the Extended Effective Exponential Model or E<span><math><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup></math></span>M. We find a good agreement between our model and experimental data.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130891"},"PeriodicalIF":3.1,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887285","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":"Solving multi-dimensional fractional Black–Scholes model using deep learning","authors":"Junjia Guo,&nbsp;Hongyan Feng,&nbsp;Yue Kai","doi":"10.1016/j.physa.2025.130908","DOIUrl":"10.1016/j.physa.2025.130908","url":null,"abstract":"<div><div>In this paper, we propose the multi-dimensional fractional Black–Scholes model (MDFBSM) with correlations between different assets for the first time and solve the MDFBSM employing deep learning method by using the reformulation of the backward stochastic differential equations (BSDEs). The fractional Black–Scholes model (FBSM) is an extension of the traditional Black–Scholes model, which adopts the fractional Brownian motion (FBM) to describe the dynamic changes of asset prices, so as to capture the long-term memory, thick tail, autocorrelation and hidden dynamic changes in the financial market. Its complexity and “curse of dimensionality” makes the MDFBSM very difficult to solve. Thus, this paper uses BSDEs to reformulate the partial differential equations (PDEs). Combining the TensorFlow framework with the gradient of the solution as the policy function and the error between the solution of the BSDE and the prescribed terminal condition as the loss function, we approximate the policy function of the model by minimizing the residuals of the PDEs through a neural network approach, thus overcoming the “curse of dimensionality” problem. To verify the validity of this paper, the historical data of 67 futures contracts in China are used for empirical analysis. And then, we find that our results can truly reflect the dynamics of asset prices in the real market.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130908"},"PeriodicalIF":3.1,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863982","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":"Lane-changing strategies of autonomous vehicles and social dilemmas in mixed traffic: A simulation study","authors":"Nikita V. Bykov,&nbsp;Maksim A. Kostrov","doi":"10.1016/j.physa.2025.130909","DOIUrl":"10.1016/j.physa.2025.130909","url":null,"abstract":"<div><div>This study investigates the impact of different lane-changing strategies of autonomous vehicles (AVs) on traffic dynamics and social efficiency in mixed traffic conditions. We introduce a multi-agent traffic model based on a cellular automaton framework, incorporating human-driven vehicles (HDVs) and three types of AVs: non-lane-changing (AV), cooperative (AV-C), and permissive (AV-D). Each AV type follows distinct longitudinal and lateral rules under Adaptive Cruise Control (ACC) or Cooperative ACC (CACC). The simulation results reveal that non-lane-changing AVs maximize traffic flow but struggle with obstacle avoidance. AV-C agents maintain platoon integrity, while AV-D agents improve maneuverability at the cost of platoon stability. We analyze the emergence of social dilemmas using the Social Efficiency Deficit (SED) metric and identify conditions under which individual rationality conflicts with global traffic performance. The findings highlight the need for hybrid control strategies and external incentives to support early-stage AV deployment and ensure cooperative equilibria.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130909"},"PeriodicalIF":3.1,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864024","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":"Adaptive longitudinal and lateral car-following control for multi-platoon with parameter uncertainties and external disturbance","authors":"Junhong Xie ,&nbsp;Jianzhong Chen ,&nbsp;Zekai Lv ,&nbsp;Zhihe Xu","doi":"10.1016/j.physa.2025.130919","DOIUrl":"10.1016/j.physa.2025.130919","url":null,"abstract":"<div><div>Cooperative vehicle formation improves traffic conditions, while cooperative vehicle platoon formation can further enhance traffic efficiency, reduce exhaust emissions, and ensure driving safety. Hence, this paper proposes an adaptive longitudinal and lateral car-following control algorithm for cooperative vehicle formation and vehicle platoon formation with parameter uncertainties and external disturbance. Integrating the sign function, the adaptive laws are developed to eliminate the effects of parameter uncertainties and external disturbance on vehicle driving to ensure the robustness of vehicle platoon. Considering the longitudinal and lateral movements, the distributed car-following control laws are designed for the leading vehicle and following vehicle within a platoon, respectively. The stability of cooperative vehicle formation and vehicle platoon formation, as well as the boundedness of closed-loop signals, are rigorously proved by the Lyapunov stability theory. Simulation results demonstrate that the proposed adaptive car-following control algorithm can effectively compensate for parameter uncertainties and external disturbance, while achieving the consensus and stability of intra-platoon and inter-platoon. Compared to the consensus-based control algorithm, the proposed adaptive control algorithm presents faster convergence and superior stability, with the longitudinal position error of CAV 5 reduced from 1.185 m to 0.051 m, and the lateral position error reduced from 0.007 m to 0.001 m.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"677 ","pages":"Article 130919"},"PeriodicalIF":3.1,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144888979","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}