Pub Date : 2025-12-16DOI: 10.1016/j.physa.2025.131206
Sandro M. Reia , Dieter Pfoser , Paulo R.A. Campos
We present a model to study how adaptive and static hotspots shape cultural dynamics and group aggregation in spatial populations. Agents and hotspots are represented by cultural vectors, and agents move through a two-dimensional space according to their cultural similarity to nearby hotspots. Our results show that adaptive hotspots, which change their cultural vector to match the modal traits of their occupants, attract larger groups than static hotspots. At moderate and large mobility scales, hotspot occupancies follow heavy-tailed distributions consistent with multiplicative growth, producing lognormal-like patterns observed in firms, cities, and biological systems. This outcome arises from a feedback loop in which adaptive hotspots align neighboring agents who, after moving, are more likely to join them, reinforcing their advantage. Mobility regulates this process: higher mobility facilitates encounters across diverse groups, enhancing integration, while limited mobility constrains agents to suboptimal choices, fostering segregation. Overall, adaptive hotspots emerge as cultural hubs that promote convergence, in line with empirical evidence linking urban mobility to reduced segregation.
{"title":"Agent mobility and hotspot adaptability drive group aggregation","authors":"Sandro M. Reia , Dieter Pfoser , Paulo R.A. Campos","doi":"10.1016/j.physa.2025.131206","DOIUrl":"10.1016/j.physa.2025.131206","url":null,"abstract":"<div><div>We present a model to study how adaptive and static hotspots shape cultural dynamics and group aggregation in spatial populations. Agents and hotspots are represented by cultural vectors, and agents move through a two-dimensional space according to their cultural similarity to nearby hotspots. Our results show that adaptive hotspots, which change their cultural vector to match the modal traits of their occupants, attract larger groups than static hotspots. At moderate and large mobility scales, hotspot occupancies follow heavy-tailed distributions consistent with multiplicative growth, producing lognormal-like patterns observed in firms, cities, and biological systems. This outcome arises from a feedback loop in which adaptive hotspots align neighboring agents who, after moving, are more likely to join them, reinforcing their advantage. Mobility regulates this process: higher mobility facilitates encounters across diverse groups, enhancing integration, while limited mobility constrains agents to suboptimal choices, fostering segregation. Overall, adaptive hotspots emerge as cultural hubs that promote convergence, in line with empirical evidence linking urban mobility to reduced segregation.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131206"},"PeriodicalIF":3.1,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841548","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}
Pub Date : 2025-12-16DOI: 10.1016/j.physa.2025.131203
Jianxin Tang , Lijun Liu , Chenshuo Li , Xin Wang , Ping Wang
The influence maximization problem in multilayer social networks entails selecting seed nodes from each layer under a budget constraint to optimize the overall influence spread. However, the insufficient considerations of topological heterogeneity and cross-layer propagation synergy in existing methods result in imbalanced resource allocation and unsatisfying influence spread easily. To address such challenges, a cross-layer independent cascade model is designed to capture both intra-layer and inter-layer diffusion dynamics. Furthermore, a layer-weighted budget allocation and community-aware local dominance (LWCD) approach is proposed to address the issues of topological heterogeneity and optimal resource allocation in cross-layer propagation. It involves a three-stage process: a layer-weighted assignment method is introduced, where k-core centrality and jaccard overlap are used to quantify the importance of each layer; based on the computed layer weights, the infomap method is applied for community detection, and the budget is allocated proportionally to community sizes; finally, high-potential seed nodes within each community are identified using a local degree metric that captures node influence. Extensive experiments on synthetic and real-world multilayer networks confirm the effectiveness and stability of the proposed LWCD. Compared with state-of-the-art algorithms, LWCD achieves an average improvement of 60.68% in eight networks in terms of influence spread. The complete source code has been made publicly accessible at https://github.com/xiaogoudaidai/LWCDalgorithm to facilitate reproducibility and further research.
{"title":"Optimizing influence spread in multilayer networks: A layer-weighted budget allocation and community-based local dominance approach","authors":"Jianxin Tang , Lijun Liu , Chenshuo Li , Xin Wang , Ping Wang","doi":"10.1016/j.physa.2025.131203","DOIUrl":"10.1016/j.physa.2025.131203","url":null,"abstract":"<div><div>The influence maximization problem in multilayer social networks entails selecting seed nodes from each layer under a budget constraint to optimize the overall influence spread. However, the insufficient considerations of topological heterogeneity and cross-layer propagation synergy in existing methods result in imbalanced resource allocation and unsatisfying influence spread easily. To address such challenges, a cross-layer independent cascade model is designed to capture both intra-layer and inter-layer diffusion dynamics. Furthermore, a layer-weighted budget allocation and community-aware local dominance (LWCD) approach is proposed to address the issues of topological heterogeneity and optimal resource allocation in cross-layer propagation. It involves a three-stage process: a layer-weighted assignment method is introduced, where k-core centrality and jaccard overlap are used to quantify the importance of each layer; based on the computed layer weights, the infomap method is applied for community detection, and the budget is allocated proportionally to community sizes; finally, high-potential seed nodes within each community are identified using a local degree metric that captures node influence. Extensive experiments on synthetic and real-world multilayer networks confirm the effectiveness and stability of the proposed LWCD. Compared with state-of-the-art algorithms, LWCD achieves an average improvement of 60.68% in eight networks in terms of influence spread. The complete source code has been made publicly accessible at <span><span>https://github.com/xiaogoudaidai/LWCDalgorithm</span><svg><path></path></svg></span> to facilitate reproducibility and further research.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131203"},"PeriodicalIF":3.1,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841553","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131222
Xinyu Han , Dongchi Wang , Feng Jiang , Michael Small
The readout-only training mechanism establishes reservoir computing (RC) as a prominent lightweight prediction model, but simultaneously compromises its ability to effectively capture the specific higher-order interaction inherent to complex dynamical systems. To address this issue, a novel RC input layer inspired by simplicial complexes is proposed. As the direct interface to the input time series, this input layer acts as a potential multi-order feature extractor for explicitly and directly modeling the complex interactions within dynamical systems. Specifically, the novel input layer is initialized as a set of random simplices with varying dimensions, each of which is responsible for representing the interaction features of the corresponding order. Like its original counterpart, the presented input layer requires no training, thereby fully preserving the hallmark low training cost of RC. Furthermore, a causality-based quantification method is developed to measure the multi-order information richness of RC. Numerical experiments are then conducted to systematically analyze how the simplex distribution in the new input layer and key RC hyperparameters affect the quantified richness metrics. Finally, the proposed input layer can be extended to various RC variants, and its effectiveness in enhancing RCs’ prediction performance is validated through prediction tasks involving both chaotic systems and real-world datasets.
{"title":"A general multi-order feature extractor for reservoir computing via simplicial complexes","authors":"Xinyu Han , Dongchi Wang , Feng Jiang , Michael Small","doi":"10.1016/j.physa.2025.131222","DOIUrl":"10.1016/j.physa.2025.131222","url":null,"abstract":"<div><div>The readout-only training mechanism establishes reservoir computing (RC) as a prominent lightweight prediction model, but simultaneously compromises its ability to effectively capture the specific higher-order interaction inherent to complex dynamical systems. To address this issue, a novel RC input layer inspired by simplicial complexes is proposed. As the direct interface to the input time series, this input layer acts as a potential multi-order feature extractor for explicitly and directly modeling the complex interactions within dynamical systems. Specifically, the novel input layer is initialized as a set of random simplices with varying dimensions, each of which is responsible for representing the interaction features of the corresponding order. Like its original counterpart, the presented input layer requires no training, thereby fully preserving the hallmark low training cost of RC. Furthermore, a causality-based quantification method is developed to measure the multi-order information richness of RC. Numerical experiments are then conducted to systematically analyze how the simplex distribution in the new input layer and key RC hyperparameters affect the quantified richness metrics. Finally, the proposed input layer can be extended to various RC variants, and its effectiveness in enhancing RCs’ prediction performance is validated through prediction tasks involving both chaotic systems and real-world datasets.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131222"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841557","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131189
Yu-Liang Xu , Pan-Pan Zhang , Li-Zhen Hu , Xiang-Mu Kong , Zhong-Qiang Liu
The quantum coherence between non-nearest spin blocks in a one-dimensional random Heisenberg spin chain with Dzyaloshinskii–Moriya (DM) interaction at absolute zero temperature has been investigated. Using the quantum renormalization group method, we study the variation of quantum coherence with random coupling parameters and DM interaction especially when the size of the system becomes larger. The random coupling parameter follows the normal distribution, and its standard deviation reflects the disorder degree of the system. When the standard deviation is zero, the system is ordered. At the quantum critical point, the quantum coherence has a significant discontinuous change from zero to maximum. As the standard deviation becomes nonzero, the “smoothing” of the coherence near the quantum phase transition point is observed. When the standard deviation is large, the minimum value of the average quantum coherence is no longer zero, and there exists always quantum coherence in the random system. The larger the standard deviation, the larger the fluctuation range of quantum coherence. The fluctuation distribution of quantum coherence is becoming more and more asymmetric around the quantum phase transition point. When the average coherence is small, the fluctuation of coherence is larger, indicating that the effect of disorder is more obvious. Our results also show that the position of the maximum quantum coherence fluctuation can be used to indicate the critical point of quantum phase transition of the system.
{"title":"Quantum coherence at the quantum phase transition in a random Heisenberg spin system with Dzyaloshinskii–Moriya interaction","authors":"Yu-Liang Xu , Pan-Pan Zhang , Li-Zhen Hu , Xiang-Mu Kong , Zhong-Qiang Liu","doi":"10.1016/j.physa.2025.131189","DOIUrl":"10.1016/j.physa.2025.131189","url":null,"abstract":"<div><div>The quantum coherence between non-nearest spin blocks in a one-dimensional random Heisenberg spin chain with Dzyaloshinskii–Moriya (DM) interaction at absolute zero temperature has been investigated. Using the quantum renormalization group method, we study the variation of quantum coherence with random coupling parameters and DM interaction especially when the size of the system becomes larger. The random coupling parameter follows the normal distribution, and its standard deviation reflects the disorder degree of the system. When the standard deviation is zero, the system is ordered. At the quantum critical point, the quantum coherence has a significant discontinuous change from zero to maximum. As the standard deviation becomes nonzero, the “smoothing” of the coherence near the quantum phase transition point is observed. When the standard deviation is large, the minimum value of the average quantum coherence is no longer zero, and there exists always quantum coherence in the random system. The larger the standard deviation, the larger the fluctuation range of quantum coherence. The fluctuation distribution of quantum coherence is becoming more and more asymmetric around the quantum phase transition point. When the average coherence is small, the fluctuation of coherence is larger, indicating that the effect of disorder is more obvious. Our results also show that the position of the maximum quantum coherence fluctuation can be used to indicate the critical point of quantum phase transition of the system.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131189"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841551","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131218
Jin-Song von Storch
Fluctuations in systems maintained in dynamical equilibrium – spanning phenomena from Brownian motion to internal climate variability – are commonly analyzed through fluctuation–dissipation relations (FDRs) derived from the underlying microscopic dynamics. Such a derivation often relies on specific approximations or coarse-graining techniques, leaving the precise origin of FDRs and their connection to the governing differential equations conceptually unsettled. Using the Lorenz–63 model as a representative forced dissipative system, this paper identifies an integral fluctuation–dissipation relation (IFDR)—a FDR that constitutes (apart from a constant) the integrals of the system’s differential forcing without any approximation. The IFDR does not exist as a time rate of change and can hence not be embedded in the microscopic differential dynamics. It only emerges when the considered system is integrated forward in time. Macroscopic quantities such as variances and spectra result from the joint effect of the dissipation and fluctuation terms of the IFDR, and cannot be determined by the system’s differential forcing itself. Thus, equilibrium fluctuations of a system are governed by two principles that are complementary but not reducible to one another: the microscopic differential equations that govern individual trajectories and the IFDR that determine the macroscopic quantities. The identification of IFDR provides a deterministic foundation for equilibrium fluctuations – random solution arises internally from deterministic forward integration – and clarifies how macroscopic quantities arise intrinsically from time-integrated dynamics.
{"title":"Principles of equilibrium fluctuations","authors":"Jin-Song von Storch","doi":"10.1016/j.physa.2025.131218","DOIUrl":"10.1016/j.physa.2025.131218","url":null,"abstract":"<div><div>Fluctuations in systems maintained in dynamical equilibrium – spanning phenomena from Brownian motion to internal climate variability – are commonly analyzed through fluctuation–dissipation relations (FDRs) derived from the underlying microscopic dynamics. Such a derivation often relies on specific approximations or coarse-graining techniques, leaving the precise origin of FDRs and their connection to the governing differential equations conceptually unsettled. Using the Lorenz–63 model as a representative forced dissipative system, this paper identifies an integral fluctuation–dissipation relation (IFDR)—a FDR that constitutes (apart from a constant) the <em>integrals</em> of the system’s differential forcing without any approximation. The IFDR does not exist as a time rate of change and can hence not be embedded in the microscopic differential dynamics. It only emerges when the considered system is integrated forward in time. Macroscopic quantities such as variances and spectra result from the joint effect of the dissipation and fluctuation terms of the IFDR, and cannot be determined by the system’s differential forcing itself. Thus, equilibrium fluctuations of a system are governed by two principles that are complementary but not reducible to one another: the microscopic differential equations that govern individual trajectories and the IFDR that determine the macroscopic quantities. The identification of IFDR provides a deterministic foundation for equilibrium fluctuations – random solution arises internally from deterministic forward integration – and clarifies how macroscopic quantities arise intrinsically from time-integrated dynamics.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131218"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841558","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131219
Douglas F. de Albuquerque
We investigate the critical properties of the spin- transverse Ising model (TIM) on 1D linear, 2D honeycomb, square, Kagomé, and triangular, as well as 3D simple cubic lattices using a combined approach of the effective-field renormalization group (EFRG) method and the discretized path-integral representation (DPIR). This framework treats quantum fluctuations exactly within the path-integral formalism while incorporating cluster-based renormalization for accuracy beyond mean-field approximations. Applying this framework to 1D linear, 2D honeycomb, square, Kagomé, triangular, and 3D simple cubic lattices using finite clusters (), we compute critical temperatures and quantum critical fields as functions of transverse field strength. On frustrated Kagomé and triangular lattices, quantum fluctuations enhance spin-liquid stabilization and short-range correlations, contrasting robust ordering on bipartite linear, honeycomb, square, and simple cubic lattices. Our EFRG-DPIR approach achieves 3–8% accuracy compared to DMRG and quantum Monte Carlo benchmarks, significantly improving upon previous MFRG-DPIR estimates. The method successfully captures universality shifts toward spin-liquid phases in frustrated geometries, providing a powerful computational tool for exploring quantum phase transitions in complex magnetic systems.
利用有效场重整化群（EFRG）方法和离散路径积分表示（DPIR）相结合的方法，研究了一维线性、二维蜂窝、正方形、kagom栅格和三角形以及三维简单立方晶格上自旋- s =1/2横向Ising模型（TIM）的临界性质。该框架在路径积分形式中精确地处理量子涨落，同时结合基于聚类的重整化以获得超越平均场近似的精度。将该框架应用于使用有限簇（N ' =1，N=2）的一维线性、二维蜂窝、正方形、kagom、三角形和三维简单立方晶格，我们计算了临界温度Tc和量子临界场ϵc=Ωc/J作为横向场强的函数。在受挫的kagom格和三角格上，量子涨落增强了自旋-液体稳定性和短程相关性，对比了二部线性格、蜂窝格、方形格和简单立方格上的鲁棒有序。与DMRG和量子蒙特卡罗基准相比，我们的EFRG-DPIR方法达到了3-8%的精度，显着提高了以前的MFRG-DPIR估计。该方法成功捕获了受挫几何中自旋液相的普适位移，为探索复杂磁系统中的量子相变提供了强大的计算工具。
{"title":"Hybrid EFRG-DPIR approach to quantum criticality in the spin-1/2 transverse Ising model: Frustration effects on Tc and Ωc in 1D-3D lattices","authors":"Douglas F. de Albuquerque","doi":"10.1016/j.physa.2025.131219","DOIUrl":"10.1016/j.physa.2025.131219","url":null,"abstract":"<div><div>We investigate the critical properties of the spin-<span><math><mrow><mi>S</mi><mo>=</mo><mn>1</mn><mo>/</mo><mn>2</mn></mrow></math></span> transverse Ising model (TIM) on 1D linear, 2D honeycomb, square, Kagomé, and triangular, as well as 3D simple cubic lattices using a combined approach of the effective-field renormalization group (EFRG) method and the discretized path-integral representation (DPIR). This framework treats quantum fluctuations exactly within the path-integral formalism while incorporating cluster-based renormalization for accuracy beyond mean-field approximations. Applying this framework to 1D linear, 2D honeycomb, square, Kagomé, triangular, and 3D simple cubic lattices using finite clusters (<span><math><mrow><msup><mrow><mi>N</mi></mrow><mrow><mo>′</mo></mrow></msup><mo>=</mo><mn>1</mn><mo>,</mo><mspace></mspace><mi>N</mi><mo>=</mo><mn>2</mn></mrow></math></span>), we compute critical temperatures <span><math><msub><mrow><mi>T</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span> and quantum critical fields <span><math><mrow><msub><mrow><mi>ϵ</mi></mrow><mrow><mi>c</mi></mrow></msub><mo>=</mo><msub><mrow><mi>Ω</mi></mrow><mrow><mi>c</mi></mrow></msub><mo>/</mo><mi>J</mi></mrow></math></span> as functions of transverse field strength. On frustrated Kagomé and triangular lattices, quantum fluctuations enhance spin-liquid stabilization and short-range correlations, contrasting robust ordering on bipartite linear, honeycomb, square, and simple cubic lattices. Our EFRG-DPIR approach achieves 3–8% accuracy compared to DMRG and quantum Monte Carlo benchmarks, significantly improving upon previous MFRG-DPIR estimates. The method successfully captures universality shifts toward spin-liquid phases in frustrated geometries, providing a powerful computational tool for exploring quantum phase transitions in complex magnetic systems.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131219"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841029","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131204
Felipe P. Abreu, Welles A.M. Morgado
The thermodynamics of mesoscopic systems driven by time-varying temperatures is crucial for understanding biological systems, designing nanoscale engines, and performing micro-particle cooling. In this work, we analyze an underdamped Brownian particle in a harmonic trap under a sinusoidal thermal protocol. Through analytical methods and numerical simulations, we analyze the system’s dynamics and heat statistics. We report the emergence of resonant position–velocity correlations and a non-Gaussian, asymmetric heat distribution consistent with the Fluctuation Theorem. We demonstrate that inertia is a key parameter, damping the system’s response and slowing its relaxation to a periodic non-equilibrium steady state. Our results show that oscillatory thermal driving is a powerful tool for controlling nanoscale energy flow.
{"title":"Impact of periodic thermal driving on heat fluctuations in a harmonic system","authors":"Felipe P. Abreu, Welles A.M. Morgado","doi":"10.1016/j.physa.2025.131204","DOIUrl":"10.1016/j.physa.2025.131204","url":null,"abstract":"<div><div>The thermodynamics of mesoscopic systems driven by time-varying temperatures is crucial for understanding biological systems, designing nanoscale engines, and performing micro-particle cooling. In this work, we analyze an underdamped Brownian particle in a harmonic trap under a sinusoidal thermal protocol. Through analytical methods and numerical simulations, we analyze the system’s dynamics and heat statistics. We report the emergence of resonant position–velocity correlations and a non-Gaussian, asymmetric heat distribution consistent with the Fluctuation Theorem. We demonstrate that inertia is a key parameter, damping the system’s response and slowing its relaxation to a periodic non-equilibrium steady state. Our results show that oscillatory thermal driving is a powerful tool for controlling nanoscale energy flow.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131204"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841550","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131216
Mônica V. Prates , Arthur A.B. Pessa , Sebastian Gonçalves , Matjaž Perc , Haroldo V. Ribeiro
Political corruption is inherently an affiliation process linking agents to corruption cases; yet it is often studied via one-mode projections that connect co-offenders within the same scandal, implying a loss of information that potentially confounds properties of agents and cases. Here, we adopt a bipartite representation to analyze datasets of corruption scandals in Brazil and Spain spanning nearly three decades. By tracking the temporal growth of these networks, we quantify density and redundancy measures to capture partner reuse and co-occurrence across cases. Networks in both countries become progressively sparser over time, and agent redundancy is systematically higher than case redundancy, indicating a small cadre of recidivists who recombine largely with novice partners rather than forming durable co-offending ties. These networks exhibit near-exponential degree distributions, reflecting low recidivism and likely high coordination costs and secrecy constraints of large-scale scandals. Our bipartite view further reveals a moderate cross-mode disassortative degree mixing between agents and cases, with high-degree agents distributing their activity across small cases and large scandals mainly comprising low-degree participants. Finally, identifying atypical individuals within the bipartite structure reveals criminal trajectories marked by a gradual rise in network embeddedness that can appear ordinary in agent-projected networks.
{"title":"Bipartite structure and dynamics of political corruption networks","authors":"Mônica V. Prates , Arthur A.B. Pessa , Sebastian Gonçalves , Matjaž Perc , Haroldo V. Ribeiro","doi":"10.1016/j.physa.2025.131216","DOIUrl":"10.1016/j.physa.2025.131216","url":null,"abstract":"<div><div>Political corruption is inherently an affiliation process linking agents to corruption cases; yet it is often studied via one-mode projections that connect co-offenders within the same scandal, implying a loss of information that potentially confounds properties of agents and cases. Here, we adopt a bipartite representation to analyze datasets of corruption scandals in Brazil and Spain spanning nearly three decades. By tracking the temporal growth of these networks, we quantify density and redundancy measures to capture partner reuse and co-occurrence across cases. Networks in both countries become progressively sparser over time, and agent redundancy is systematically higher than case redundancy, indicating a small cadre of recidivists who recombine largely with novice partners rather than forming durable co-offending ties. These networks exhibit near-exponential degree distributions, reflecting low recidivism and likely high coordination costs and secrecy constraints of large-scale scandals. Our bipartite view further reveals a moderate cross-mode disassortative degree mixing between agents and cases, with high-degree agents distributing their activity across small cases and large scandals mainly comprising low-degree participants. Finally, identifying atypical individuals within the bipartite structure reveals criminal trajectories marked by a gradual rise in network embeddedness that can appear ordinary in agent-projected networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131216"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841552","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}
Pub Date : 2025-12-15DOI: 10.1016/j.physa.2025.131213
Ronald Benjamin
We investigate the role of inertia on the performance of a shifting Brownian motor through extensive numerical simulations of the Langevin equation. The motor consists of a Brownian particle subjected alternately to two spatially asymmetric and piecewise-linear potentials whose extrema are shifted relative to each other. Our results reveal several distinctive features absent in previous overdamped models. In the deterministic, overdamped, and adiabatic regime, the motor exhibits giant transport coherence (Peclet number () with negligible dispersion and maximum efficiency (). Transport coherence degrades monotonically with increasing particle mass, temperature, and in the non-adiabatic limit. At higher temperatures, we identify an optimal mass () maximizing both work output and thermodynamic efficiency, reflecting a balance between thermal activation and inertial momentum. A counterintuitive, non-monotonic temperature dependence of the effective diffusion coefficient emerges at large masses, which we explain through coexisting locked and running states of motion. Our analytical predictions for current, efficiency, and energy input in the overdamped-deterministic-adiabatic limit show excellent agreement with numerical results. These findings provide design principles for optimizing nanoscale motors and offer insights into the complex interplay between deterministic forces, thermal fluctuations, and inertial dynamics in non-equilibrium transport.
{"title":"A study of inertial effects on the efficiency and transport coherence of a shifting Brownian Motor","authors":"Ronald Benjamin","doi":"10.1016/j.physa.2025.131213","DOIUrl":"10.1016/j.physa.2025.131213","url":null,"abstract":"<div><div>We investigate the role of inertia on the performance of a shifting Brownian motor through extensive numerical simulations of the Langevin equation. The motor consists of a Brownian particle subjected alternately to two spatially asymmetric and piecewise-linear potentials whose extrema are shifted relative to each other. Our results reveal several distinctive features absent in previous overdamped models. In the deterministic, overdamped, and adiabatic regime, the motor exhibits giant transport coherence (Peclet number (<span><math><mrow><mi>P</mi><mi>e</mi><mo>></mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>5</mn></mrow></msup></mrow></math></span>) with negligible dispersion and maximum efficiency (<span><math><mrow><mo>∼</mo><mn>8</mn><mtext>%</mtext></mrow></math></span>). Transport coherence degrades monotonically with increasing particle mass, temperature, and in the non-adiabatic limit. At higher temperatures, we identify an optimal mass (<span><math><mrow><mo>∼</mo><mi>M</mi><mo>=</mo><mn>1</mn></mrow></math></span>) maximizing both work output and thermodynamic efficiency, reflecting a balance between thermal activation and inertial momentum. A counterintuitive, non-monotonic temperature dependence of the effective diffusion coefficient emerges at large masses, which we explain through coexisting locked and running states of motion. Our analytical predictions for current, efficiency, and energy input in the overdamped-deterministic-adiabatic limit show excellent agreement with numerical results. These findings provide design principles for optimizing nanoscale motors and offer insights into the complex interplay between deterministic forces, thermal fluctuations, and inertial dynamics in non-equilibrium transport.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131213"},"PeriodicalIF":3.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841556","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}
Flight delays have been a persistent issue in the civil aviation industry, with the boarding process recognized as a major contributing factor. Although the boarding processes of modern aircraft have been extensively investigated, how a significantly larger cabin influences the boarding process of future blended wing body aircraft remains unexplored. In this study, a blended wing body aircraft boarding simulation model was developed to evaluate the effects of overtaking happening on the aisles of the blended wing body aircraft. An experiment was also performed to evaluate how passengers react to opportunities for overtaking in real life. When combined with an appropriate boarding strategy such as Outside-in and Double Outside-in, a moderate increase in aisle width (20–30 cm) can significantly improve the boarding speed while reducing the standard deviation of boarding time. While increasing the aisle width naturally increases the chance of overtaking, overtaking can also happen more because of limited carry-on baggage and encouragement.
{"title":"Boarding strategies of blended wing body passenger aircraft considering pedestrian overtaking behavior","authors":"Yuming Dong , Xiaolu Jia , Claudio Feliciani , Daichi Yanagisawa , Katsuhiro Nishinari","doi":"10.1016/j.physa.2025.131212","DOIUrl":"10.1016/j.physa.2025.131212","url":null,"abstract":"<div><div>Flight delays have been a persistent issue in the civil aviation industry, with the boarding process recognized as a major contributing factor. Although the boarding processes of modern aircraft have been extensively investigated, how a significantly larger cabin influences the boarding process of future blended wing body aircraft remains unexplored. In this study, a blended wing body aircraft boarding simulation model was developed to evaluate the effects of overtaking happening on the aisles of the blended wing body aircraft. An experiment was also performed to evaluate how passengers react to opportunities for overtaking in real life. When combined with an appropriate boarding strategy such as <em>Outside-in</em> and <em>Double Outside-in</em>, a moderate increase in aisle width (20–30 cm) can significantly improve the boarding speed while reducing the standard deviation of boarding time. While increasing the aisle width naturally increases the chance of overtaking, overtaking can also happen more because of limited carry-on baggage and encouragement.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"683 ","pages":"Article 131212"},"PeriodicalIF":3.1,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841554","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}
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