Physica A: Statistical Mechanics and its Applications最新文献_第6页

Connected vehicle-based simulation of variable speed limit effects on highway mixed traffic flow 基于车联网的变限速对高速公路混合交通流影响模拟

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-06 DOI: 10.1016/j.physa.2026.131272

Zhihong Yao , Zhiyu Ma , Jinrun Wang , Yunxia Wu , Chenming Jiang

With the rapid development of connected vehicles (CVs) technology, variable speed limit (VSL) control based on CVs has gradually become a practical application on highways. This paper aims to thoroughly investigate the effectiveness of VSL control in mixed traffic flow on highways based on CVs. First, a cellular automaton (CA) model for multi-lane mixed traffic flow on highways was developed, incorporating the deterministic driving behaviors of CVs and considering the characteristics of CV communication, including the heterogeneous speed limits. Then, we systematically explore the influence patterns of the penetration rate of CVs, traffic density, and the strictness of speed limits on the characteristics of mixed traffic flow, and interpret the mechanism of CV speed regulation from the perspectives of traffic capacity and critical density. Finally, regression equations for the fundamental parameters of mixed traffic flow are fitted based on simulation data, quantitatively revealing the regulatory mechanism of CVs on mixed traffic flow. The results show that: (1) increasing the penetration rate of CVs can significantly improve traffic efficiency, effectively suppress traffic oscillations, and simultaneously reduce traffic congestion and fuel consumption; (2) the effectiveness of CV speed limits is closely related to road spatial resources, and only exerts significant regulatory effects under conditions of sufficient longitudinal space; (3) there exists a synergistic effect between CV speed limits and penetration rate, jointly influencing the VSL effectiveness in mixed traffic flow. This work validates the effectiveness of CV-based VSL control and provides theoretical support and practical guidance for highway traffic management in connected vehicle environments.

随着车联网技术的快速发展，基于车联网的变速限制控制逐渐成为高速公路上的实际应用。本文旨在深入研究基于cv的高速公路混合交通流VSL控制的有效性。首先，建立了高速公路多车道混合交通流元胞自动机（CA）模型，该模型考虑了CV的确定性驾驶行为，并考虑了CV通信的异构限速等特性；在此基础上，系统探讨了CV渗透率、交通密度和限速严格程度对混合交通流特征的影响规律，并从交通容量和临界密度的角度解读了CV调速机制。最后，基于仿真数据拟合混合交通流基本参数的回归方程，定量揭示了cv对混合交通流的调控机制。结果表明：(1)提高cv渗透率可显著提高交通效率，有效抑制交通振荡，同时减少交通拥堵和燃油消耗；(2) CV限速的有效性与道路空间资源密切相关，只有在纵向空间充足的情况下才能发挥显著的调节作用；(3) CV限速与渗透率之间存在协同效应，共同影响混合交通流中VSL的有效性。该工作验证了基于cv的车路控制的有效性，为车联网环境下的公路交通管理提供了理论支持和实践指导。

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引用次数: 0

Corridor geometry effects on the bidirectional pedestrian walking modeled as a multi-agent system 走廊几何对双向行人行走的影响建模为多智能体系统

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-06 DOI: 10.1016/j.physa.2025.131207

A.L. Ballinas-Hernández , M. Rangel-Galván , V. Rangel-Galván

We characterize how variations in corridor geometry affect bidirectional pedestrian dynamics modeled as a situated multi-agent system. Three environment configurations — corridors with side exits, crooked corridors, and patch-containing corridors — are compared against a standard straight corridor. These geometric modifications give rise to distinct collective patterns, revealing new features of self-organization and the system’s adaptive response to environmental constraints. We quantify the dynamics using four order parameters: average velocity, walking flow, velocity autocorrelation function, and informational entropy. Side exits enhance average velocity and autocorrelation while reducing entropy; crooked geometries increase flow, yield higher autocorrelation, and lower entropy; patch-containing corridors decrease both velocity and flow yet preserve autocorrelation. Furthermore, velocity–density, flow–density, and entropy–density relations exhibit clear phase transitions at critical densities. These findings provide a unified characterization of the effects of modified corridors, both on the walking dynamics and on the intrinsic decision making activity of agents in bidirectional pedestrian motion.

我们描述了走廊几何形状的变化如何影响作为定位多智能体系统建模的双向行人动力学。三种环境配置——有侧出口的走廊、弯曲的走廊和包含补丁的走廊——与标准的直走廊进行了比较。这些几何变化产生了独特的集体模式，揭示了自组织的新特征和系统对环境约束的适应性反应。我们使用四阶参数来量化动态：平均速度、行走流量、速度自相关函数和信息熵。侧出口增强了平均速度和自相关性，降低了熵；弯曲的几何形状增加了流量，产生了更高的自相关性和更低的熵；含斑块廊道降低了速度和流量，但保持了自相关性。此外，在临界密度下，速度-密度、流量-密度和熵-密度关系表现出明显的相变。这些发现提供了一个统一的特征，对步行动力学和双向行人运动中主体的内在决策活动的修改走廊的影响。

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引用次数: 0

The impact of spatial redundancy and merging conflicts on crowd movement patterns: An empirical study 空间冗余和融合冲突对人群运动模式影响的实证研究

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-03 DOI: 10.1016/j.physa.2026.131269

Haonan Ma , Wenhang Li , Jianhua Gong , Yabin Li , Cheng Qin , Jingyi Zhang

Modern urbanization has led to increased crowd gatherings, heightening crowd safety risks in public infrastructure. To enhance safety management, investigating crowd flow patterns in typical building structures is crucial. Merging scenarios are frequently scrutinized as dangerous bottlenecks prone to severe crowd accidents. Extensive research on corridor structural design and merging patterns’ effects on merging flows has attempted high-density designs to ensure the emergence of merging phenomena, while few studies have focused on the effect of redundant space on pedestrian decision-making processes. Spatial redundancy is a relative concept, determined jointly by the available space within the corridor and the number of pedestrians. Under high spatial redundancy, pedestrian decisions are less constrained by spatial pressure, enabling more behavioral emergence and helping to more comprehensively understand pedestrian decision-making processes, which has important research significance. To address this, we conducted a controlled crowd experiment featuring corridors with two main-corridor widths and three merging angles, examining pedestrian flows under two regimes: with and without merging. We observed that a layered-flow pattern with low inter-stream coupling emerged under high spatial redundancy, whereas an interwoven-flow pattern with pronounced trajectory overlap appeared under low spatial redundancy. Additionally, merging induced anticipatory avoidance phenomena, with trajectories shifting significantly toward one side. Density and speed analyses revealed that high spatial redundancy design in the merging area reduces density aggregation effects caused by merging, thereby effectively enhancing traffic efficiency. These findings offer new insights into pedestrian movement strategies and provide an empirical basis for optimizing corridor design and calibrating crowd simulation models.

现代城市化导致人群聚集增多，公共基础设施人群安全风险加大。为了加强安全管理，研究典型建筑结构的人群流动模式至关重要。合并场景经常被视为容易导致严重人群事故的危险瓶颈。大量关于廊道结构设计和归并模式对归并流影响的研究尝试了高密度设计来保证归并现象的出现，而很少有研究关注冗余空间对行人决策过程的影响。空间冗余是一个相对的概念，由走廊内的可用空间和行人数量共同决定。在高空间冗余的情况下，行人决策受空间压力的约束较小，使行为涌现更多，有助于更全面地理解行人决策过程，具有重要的研究意义。为了解决这个问题，我们进行了一个控制人群的实验，在两个主要走廊宽度和三个合并角度的走廊上，研究了两种情况下的行人流量：合并和不合并。研究发现，在高空间冗余条件下，形成了低流间耦合的分层流型，而在低空间冗余条件下，形成了轨迹重叠明显的交织流型。此外，合并引起预期回避现象，轨迹明显向一侧移动。密度和速度分析表明，合并区域的高空间冗余设计降低了合并带来的密度聚集效应，有效提高了交通效率。这些研究结果为行人运动策略的研究提供了新的见解，并为优化走廊设计和校准人群模拟模型提供了经验依据。

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引用次数: 0

Structure of transfer entropy 传递熵结构

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-03 DOI: 10.1016/j.physa.2025.131257

Huiyun Wan, Sen Li, Haiying Wang, Changgui Gu, Huijie Yang

In current methods for causality detection, a causal relationship is deduced from its effect. Even the causality keeps unchanged, its effect may display complicated behavior, i.e., it is sometimes very strong, sometimes very weak or even absent, depending strongly on the present and historical states of and the coupling strength between the causal and influential variables. This complicated behavior of the causal effect is called the structure of causality, which is merged completely into a scalar quantity in the statistical procedure shared by the causality detection methods, i.e., it is lost. In this work, this structure is preserved and described by the transitions from all the historical states to all the present states, which form a state transition network. Technically, the structure of transfer entropy is defined as a typical example for this approach, whose performance is shown by means of the coupled logistic maps and the coupled Hénon maps. It is found that a small fraction of the historical states and a small number of the transitions from historical to present states carry the substantial information, called accordingly the dominant states and the dominant transitions, all of which form a dominant state transition network. Structures of causalities in several empirical cases are then shown in detail.

在目前的因果关系检测方法中，因果关系是从其效果推导出来的。即使因果关系保持不变，其影响也可能表现出复杂的行为，即有时很强，有时很弱，甚至不存在，这在很大程度上取决于因果变量和影响变量的现在和历史状态以及它们之间的耦合强度。因果效应的这种复杂行为被称为因果结构，它在因果检测方法共有的统计过程中被完全合并为一个标量，即丢失。在这项工作中，这种结构通过从所有历史状态到所有当前状态的转换来保存和描述，从而形成一个状态转换网络。从技术上讲，将传递熵的结构定义为该方法的一个典型例子，并通过耦合逻辑映射和耦合hsamnon映射来展示该方法的性能。研究发现，一小部分历史状态和一小部分从历史状态到现在状态的转变携带着大量的信息，这些信息被称为主导状态和主导转变，它们共同构成了一个主导状态转变网络。在几个经验案例中，因果关系的结构被详细地展示出来。

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引用次数: 0

Solving Fokker–Planck–Kolmogorov equation by distribution self-adaptation normalized physics-informed neural networks 分布自适应归一化物理信息神经网络求解Fokker-Planck-Kolmogorov方程

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-02 DOI: 10.1016/j.physa.2025.131251

Yi Zhang , Yiting Duan , Xiangjun Wang , Zhikun Zhang

Stochastic dynamical systems provide essential mathematical frameworks for modeling complex real-world phenomena. The Fokker–Planck–Kolmogorov (FPK) equation governs the evolution of probability density functions associated with stochastic system trajectories. Developing robust numerical methods for solving the FPK equation is critical for understanding and predicting stochastic behavior. Here, we introduce the distribution self-adaptive normalized physics-informed neural networks (DSN-PINNs) for solving time-dependent FPK equations through the integration of soft normalization constraints with adaptive resampling strategies. Specifically, we employ a normalization-enhanced PINNs model in a pretraining phase to establish the solution’s global structure and scale, generating a reliable prior distribution. Subsequently, guided by this prior, we dynamically reallocate training points via weighted kernel density estimation, concentrating computational resources on regions most representative of the underlying probability distribution throughout the learning process. The key innovation lies in our method’s ability to exploit the intrinsic structural properties of stochastic dynamics while maintaining computational accuracy and implementation simplicity. We demonstrate the framework’s effectiveness through comprehensive numerical experiments and comparative analyses with existing methods, including validation on real-world economic datasets.

随机动力系统为模拟复杂的现实世界现象提供了必要的数学框架。Fokker-Planck-Kolmogorov （FPK）方程控制与随机系统轨迹相关的概率密度函数的演化。开发求解FPK方程的鲁棒数值方法对于理解和预测随机行为至关重要。在此，我们引入分布自适应归一化物理信息神经网络（dsn - pinn），通过集成软归一化约束和自适应重采样策略来求解时变FPK方程。具体来说，我们在预训练阶段采用了一种归一化增强的pinn模型来建立解决方案的全局结构和规模，从而产生可靠的先验分布。随后，在此先验的指导下，我们通过加权核密度估计动态重新分配训练点，将计算资源集中在整个学习过程中最能代表潜在概率分布的区域上。关键的创新在于我们的方法能够利用随机动力学的内在结构特性，同时保持计算精度和实现简单性。我们通过全面的数值实验和与现有方法的比较分析，包括对现实世界经济数据集的验证，证明了该框架的有效性。

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引用次数: 0

Analyzing human-driven vehicles’ following behavior in response to autonomous vehicles under different traffic conditions 分析不同交通条件下无人驾驶汽车对自动驾驶汽车的跟随行为

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-02 DOI: 10.1016/j.physa.2026.131267

Fang Zong , Kun Zhao , Huan Wu , Hui-Yong Zhang , Meng Zeng , Jin-Jun Tang

The car-following behavior of human-driven vehicles (HDVs) in traffic flows mixed with autonomous vehicles (AVs) is highly complex, shaped by macroscopic traffic conditions, microscopic vehicle interactions, and drivers' subjective perceptions and driving habits. Analyzing how HDVs follow AVs in such context is critical for enhancing the efficiency of mixed traffic systems. This study employed field experiments and questionnaire surveys to analyze car-following behavior under the combined influence of traffic conditions and leading vehicle types. A machine learning-based car-following model was developed, incorporating both internal (driver-related) and external factors. Simulations confirmed the feasibility of the developed model for mixed traffic flows. Furthermore, strategies to enhance the efficiency of mixed traffic were proposed, with a focus on AV penetration rates and drivers’ trust in AVs. The results indicate that traffic conditions and leading vehicle types jointly influence drivers' AV-following behavior. The efficiency of mixed traffic first decreases and then increases as AV penetration rises, with critical thresholds of 70 % and 60 % observed under uncongested and congested conditions, respectively. Additionally, higher driver trust in AVs leads to greater traffic efficiency in mixed platoons. The developed model—integrating both internal and external (traffic condition/vehicle type-related) factors—achieved fitting accuracy exceeding 93.27 % for speed and 89.14 % for acceleration, outperforming both machine learning models that neglect internal factors and the Intelligent Driver Model (IDM). The findings present a reproducible car-following simulation model for mixed traffic across diverse conditions, alongside management strategies to boost efficiency and reduce congestion. Collectively, this work offers theoretical and model support for simulating and optimizing car-following behavior in mixed traffic scenarios.

在与自动驾驶汽车混合的交通流中，人类驾驶车辆（HDVs）的跟车行为是高度复杂的，受宏观交通条件、微观车辆交互以及驾驶员的主观感知和驾驶习惯的影响。在这种情况下，分析hdv如何跟随自动驾驶汽车，对于提高混合交通系统的效率至关重要。本研究采用现场实验和问卷调查相结合的方法，对交通状况和领先车型共同影响下的跟车行为进行分析。开发了一个基于机器学习的汽车跟随模型，结合了内部（驾驶员相关）和外部因素。仿真结果验证了所建立的混合交通流模型的可行性。在此基础上，提出了提高混合交通效率的策略，重点关注自动驾驶汽车普及率和驾驶员对自动驾驶汽车的信任。结果表明，交通条件和领先车型共同影响驾驶员自动驾驶跟随行为。随着自动驾驶汽车普及率的增加，混合交通效率先降低后提高，在非拥堵和拥堵情况下，混合交通效率的临界阈值分别为70 %和60 %。此外，驾驶员对自动驾驶汽车的信任度也会提高混合车队的交通效率。开发的模型集成了内部和外部（交通状况/车辆类型相关）因素，在速度方面的拟合精度超过93.27 %，在加速度方面的拟合精度超过89.14 %，优于忽略内部因素的机器学习模型和智能驾驶员模型（IDM）。研究结果为不同条件下的混合交通提供了一个可重复的汽车跟随模拟模型，以及提高效率和减少拥堵的管理策略。总的来说，这项工作为混合交通场景下汽车跟随行为的模拟和优化提供了理论和模型支持。

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引用次数: 0

Experimental analysis of firefighter movement characteristics in fire complex environments 火灾复杂环境下消防员运动特性的实验分析

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-02 DOI: 10.1016/j.physa.2026.131266

Yixi Tao , Xuehua Song , Weiguo Song , Karel Lambert , Bart Merci

Firefighter casualties regularly occur in complex fire environments, yet the movement behavior of firefighters under such conditions remains insufficiently studied. This behavior is governed by the coupled effects of individual characteristics, building structures, and environmental conditions. In this study, a coupled experimental environment integrating dense smoke, darkness, multiple obstacles, and narrow corridors was constructed using firefighter training facilities to conduct firefighter movement experiments. Results show that even along the same route, movement times vary considerably, primarily influenced by wayfinding behaviors, obstacle-crossing speeds, and individual differences. Spatial constraints from different obstacles reduce movement speed, compared to an average of 0.48 m/s in unobstructed conditions: 0.28 m/s for unstable obstacles, 0.25 m/s for continuous obstacles, 0.22 m/s for large-scale obstacles, 0.19 m/s for height-restricted obstacles, and 0.10 m/s for lateral obstacles. Variations in crossing posture further amplified these effects. Correlation analysis indicates that movement time is jointly affected by psychological, physiological, and experiential factors, with fear of smoke, darkness, and unknown environments strongly associated with increased movement time. Moreover, total air consumption increases approximately linearly with movement time. This study enhances the realism of simulated firefighting conditions and contributes to a deeper understanding of firefighter movement behavior in complex fire environments.

在复杂的火灾环境中经常发生消防员伤亡，但消防员在这种情况下的运动行为研究尚不充分。这种行为受个体特征、建筑结构和环境条件的耦合影响。本研究利用消防员训练设施，构建了一个浓烟、黑暗、多障碍物、狭窄走廊相结合的耦合实验环境，进行消防员运动实验。结果表明，即使在相同的路线上，移动时间也有很大差异，主要受寻路行为、过障速度和个体差异的影响。不同障碍物的空间约束降低了移动速度，相比之下，无障碍物条件下的平均移动速度为0.48 m/s：不稳定障碍物为0.28 m/s，连续障碍物为0.25 m/s，大型障碍物为0.22 m/s，高度限制障碍物为0.19 m/s，横向障碍物为0.10 m/s。穿越姿势的变化进一步放大了这些影响。相关分析表明，运动时间受心理、生理和经验因素的共同影响，对烟雾、黑暗和未知环境的恐惧与运动时间的增加密切相关。此外，总空气消耗量随运动时间近似线性增加。该研究提高了模拟消防条件的真实性，有助于更深入地了解复杂火灾环境中消防员的运动行为。

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引用次数: 0

Curvature-induced operational regime transitions in computer quantum stirling cycles: A Shannon vs. Tsallis entropy perspective 计算机量子斯特林循环中曲率诱导的操作状态转换：Shannon vs. Tsallis熵的观点

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-02 DOI: 10.1016/j.physa.2025.131263

Xiang Nan , Ying Chen , Jie Zhang

We investigate the entropy–temperature relationship in a quantum Stirling cycle employing a quantum harmonic oscillator confined to a circular geometry, analyzing both Shannon and Tsallis entropies across the spatial curvature parameter

(λ)

. Entropy increases monotonically with temperature, with Tsallis values consistently exceeding Shannon values at fixed curvature, reflecting nonextensive statistical sensitivity. Our results indicate that variations in the spatial curvature parameter have a more pronounced impact than the choice of entropic formalism: Shannon entropy at

λ = 4

surpasses Tsallis entropy at

λ = 9

, highlighting geometric confinement effects. Under the conditions of a hot-to-cold reservoir temperature ratio

\frac{T_{h}}{T_{c}} = 2

, fixed compression curvature

λ_{1} = 1

, and varying expansion curvature

λ ₂

, the cycle transitions through engine, accelerator, heater, and refrigerator regimes, with the boundaries between these regimes dependent on the entropy measure. Efficiency analyses demonstrate curvature asymmetry (

λ ₁

vs.

λ ₂

) enhances performance, with Tsallis entropy achieving higher efficiency at low curvature via non-Markovian effects, while Shannon prevails in high-curvature regimes. Temperature ratio studies show persistent accelerator modes under fixed curvatures, underscoring geometry's supremacy over thermal gradients.

我们利用一个局限于圆形几何的量子谐振子研究了量子斯特林循环中的熵-温度关系，分析了跨越空间曲率参数λ的Shannon和Tsallis熵。熵随温度单调增加，在固定曲率下Tsallis值始终超过Shannon值，反映了非广泛的统计灵敏度。我们的研究结果表明，空间曲率参数的变化比熵形式选择的影响更明显：λ=4时的Shannon熵超过λ=9时的Tsallis熵，突出了几何约束效应。在冷热库温比ThTc=2、压缩曲率λ1=1和膨胀曲率λ 2变化的条件下，循环在发动机、加速器、加热器和制冷机系统之间转换，这些系统之间的边界取决于熵测度。效率分析表明，曲率不对称（λ 1 vs λ 2）可以提高性能，Tsallis熵通过非马尔可夫效应在低曲率下实现更高的效率，而Shannon熵在高曲率下更有效。温度比研究表明，在固定曲率下，持续的加速器模式，强调了几何对热梯度的优势。

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引用次数: 0

Longitudinal-field fidelity susceptibility analysis of the J1-J2 transverse-field Ising model around J2/J1≈0.5 J2/J1≈0.5附近J1-J2横场Ising模型纵场保真度敏感性分析

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2026-01-02 DOI: 10.1016/j.physa.2025.131245

Yoshihiro Nishiyama

The square-lattice

J_{1}

-

J_{2}

transverse-field (TF) Ising model was investigated with the exact diagonalization (ED) method. In order to analyze the TF-driven phase transition, we applied the longitudinal-field fidelity susceptibility

χ_{F}^{(h)}

, which is readily evaluated via the ED scheme. Here, the longitudinal field couples with the absolute value of the magnetic moment

| M |

rather than the raw

M

so that the remedied fidelity susceptibility exhibits a peak around the critical point; note that the spontaneous magnetization does not appear for the finite-size systems. As a preliminary survey, the modified fidelity susceptibility

χ_{F}^{(h)}

is applied to the analysis of criticality for

J_{2} = 0

, where a number of preceding results are available. Thereby, properly scaling the distance from the multi-criticality,

η = 0.5 - J_{2}

, the

χ_{F}^{(h)}

data were cast into the crossover-scaling formula, and the multi-critical exponent for

χ_{F}^{(h)}

is estimated. The result is cross-checked by the numerically evaluated

β

-function behavior.

用精确对角化（ED）方法研究了方晶格J1-J2横场（TF） Ising模型。为了分析tf驱动的相变，我们采用了纵向场保真度敏感性χF(h)，这很容易通过ED方案进行评估。在这里，纵向场与磁矩的绝对值|M|而不是原始的M耦合，使得修复的保真度磁化率在临界点附近出现峰值；注意，对于有限大小的系统，自发磁化不会出现。作为初步调查，修正的保真度敏感性χF(h)应用于J2=0的临界分析，其中许多先前的结果是可用的。因此，适当缩放与多临界的距离，η=0.5−J2，将χF(h)数据转化为交叉缩放公式，并估计χF(h)的多临界指数。数值计算的β函数行为验证了这一结果。

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引用次数: 0

Magnetocaloric effect and magnetization in a rotating 2D quantum ring: Analytical investigation from statistical point of view 旋转二维量子环中的磁热效应和磁化：从统计角度的分析研究

IF 3.1 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications

Pub Date : 2025-12-31 DOI: 10.1016/j.physa.2025.131261

R. Khordad

A two-dimensional GaAs quantum ring is considered in a rotating frame in the presence of an external magnetic field. The energy levels and wave functions of the system are analytically derived by solving the Schrödinger equation. Then, by using statistical formalism in the canonical ensemble, the analytical expressions are derived for the partition function, entropy, magnetization, and magnetocaloric effect (MCE). Then, the effects of rotation frequency, temperature, and magnetic field are investigated on magnetization, entropy, and MCE. According to the results, it is found that the entropy is reduced by increasing the rotation frequency in the presence of magnetic field and temperature. This is due to less localization of the electron in the circular motion about the magnetic field. The system shows a diamagnetization behavior. The smallest magnetization is associated with low temperatures and rotation frequencies. Also, the system displays a normal MCE.

考虑了一个二维砷化镓量子环在外加磁场作用下的旋转框架。通过求解Schrödinger方程，解析导出了系统的能级和波函数。然后，利用正则系综的统计形式，导出了配分函数、熵、磁化和磁热效应的解析表达式。然后，研究了旋转频率、温度和磁场对磁化强度、熵和MCE的影响。结果表明，在有磁场和温度存在的情况下，增加旋转频率可以减小熵。这是由于电子在绕磁场作圆周运动时的局部化程度较低。该系统具有抗磁化特性。最小的磁化强度与低温和低旋转频率有关。MCE显示正常。

引用次数: 0