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A novel regional traffic control strategy for mixed traffic system with the construction of congestion warning communities Physica A (IF 3.3) Pub Date : 2024-03-11 Xiaoning Gu, Chao Chen, Tao Feng, Baozhen Yao
Large-scale congestion can lead to traffic paralysis, which severely hampers the flow of vehicles and disrupts the normal functioning of urban traffic. Traffic optimization strategies can effectively improve the performance of road networks, but often ignore the impact of regional traffic conditions and equity. This paper presents a novel traffic strategy to solve regional traffic congestion in large
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Collision avoidance behaviours of luggage-laden pedestrians Physica A (IF 3.3) Pub Date : 2024-03-11 Zhigang Shi, Jun Zhang, Zhigang Shang, Weiguo Song
Understanding how pedestrians move and avoid collisions is essential for ensuring safety in crowded environments. In this study, we conducted detailed experiments, focusing on variables such as movement type (walking and running), encounter angles (90 and 180 degrees), and pedestrian characteristics. We analyzed a total of 168 trajectories to gain insights into the collision avoidance strategies employed
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Modeling heterogenous crowd evacuation on stairs in high-rise buildings using a fine discrete floor field cellular automaton model: Accounting for speed and boundary layer variations Physica A (IF 3.3) Pub Date : 2024-03-11 Qi Huang, Tianyu Qin, Lin Luo, Gaobo Yang, Zhijian Fu, Xiaobo Liu
The article investigates the impact of crowd heterogeneities on stair evacuation dynamics in high-rise building. Using a fine discrete floor field cellular automaton () model, the study explores the often-overlooked influence of crowd variations in mobility and behaviors. The simulation, set in a 21-story staircase, incorporates variations in speeds and boundary layer widths to replicate the heterogenous
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Measuring User Influence in Real-Time on Twitter Using Behavioural Features Physica A (IF 3.3) Pub Date : 2024-03-08 Md Ahsan Ul Hasan, Azuraliza Abu Bakar, Mohd Ridzwan Yaakub
Identifying influential users in online social networks, specifically Twitter, has drawn considerable research interest due to their profound influence on real-world events. Existing studies have primarily focused on topological aspects to identify influential users, which necessitate a complete network structure and ignore the behavioural aspects of the users. However, real-world network structure
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Non-extensive (Tsallis) q-statistics and auroral glow Physica A (IF 3.3) Pub Date : 2024-03-04 A.A. Chernyshov, B.V. Kozelov, M.M. Mogilevsky
It is well-known that the auroral region of the magnetosphere–ionosphere interaction is an open, nonlinear dissipative system far from the equilibrium state. It is in this region that auroras are regularly observed, demonstrating not only a wide variety of dynamic forms but also a wide range of temporal and spatial scales. Due to the memory effects and fractal properties of auroral plasma, as well
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Eco-driving-based mixed vehicular platoon control model for successive signalized intersections Physica A (IF 3.3) Pub Date : 2024-03-04 Pangwei Wang, Xindi Wang, Rongsheng Ye, Yuanzhe Sun, Cheng Liu, Juan Zhang
Electric vehicles have been considered into effective solutions to address energy problems in urban traffic systems for their remarkable performance in energy costs and carbon emissions reduction. However, the energy-saving effect of electric vehicles in urban traffic systems is restricted due to the complexities arising from mixed traffic conditions. To improve energy efficiency, this paper proposes
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Stability and dynamics of self-bound state of spin–orbit coupled spin-1 Bose–Einstein condensates Physica A (IF 3.3) Pub Date : 2024-03-03 Jie Wang, Jun-Cheng Liang, An-Qing Zhang, Ai-Xia Zhang, Ju-Kui Xue
We study self-bound state of spin–orbit (SO) coupled spin-1 BECs under the action of the SO coupling and the density-dependent and spin-dependent interactions. The phase transition conditions from the magnetized phase to the unmagnetized phase are analytically obtained in the self-bound state, and the physical mechanism of the phase transition is revealed. The distinct properties of self-bound state
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Vehicle group identification and evolutionary analysis using vehicle trajectory data Physica A (IF 3.3) Pub Date : 2024-03-03 Cailin Lei, Yuxiong Ji, Qiangqiang Shangguan, Yuchuan Du, Siby Samuel
Vehicles often move forward in groups on the highways, especially when speed and density are high simultaneously. Abnormal maneuvers of a vehicle in a group influence multiple vehicles surrounding it, potentially leading to traffic accidents. We propose an approach to identify vehicle groups and analyse the factors influencing their evolutions using vehicle trajectory data. The proposed approach quantifies
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Evaluating and enhancing the safety performance of automated longitudinal control at on-ramp merging bottleneck: a simulation study in the framework of Kerner’s three-phase traffic theory Physica A (IF 3.3) Pub Date : 2024-03-02 Haifei Yang, Enze Zhao, Yi Zhao, Yishun Li
The adaptive cruise control (ACC) system, an essential component of commercial autonomous driving that functions in longitudinal control, has attracted significant research interest because of its potential to reduce accident rates. By introducing a non-fixed headway concept, Kerner recently proposed the Three-traffic-Phase ACC (TPACC) model, which integrates a speed adaptation module derived from
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Microbiome abundance patterns as attractors and the implications for the inference of microbial interaction networks Physica A (IF 3.3) Pub Date : 2024-03-02 Isabella-Hilda Mendler, Barbara Drossel, Marc-Thorsten Hütt
Inferring microbial interaction networks from abundance patterns is an important approach to advance our understanding of microbial communities in general and the human microbiome in particular. Here we suggest discriminating two levels of information contained in microbial abundance data: (1) the quantitative abundance values and (2) the pattern of presences and absences of microbial organisms. The
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On the ideal gas law for crowds with high pressure Physica A (IF 3.3) Pub Date : 2024-03-02 Zexu Li, Lei Fang
Active particle systems, such as human crowds, are out of equilibrium posing a significant challenge in identifying a suitable equation of state. However, several previous observations suggest that a crowd’s speed distribution may conform to a two-dimensional Maxwell–Boltzmann distribution under certain yet-to-be-determined conditions. Our research uncovers that the divergence between the fluctuation
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Exploring synchronizability of complex dynamical networks from edges perspective Physica A (IF 3.3) Pub Date : 2024-03-02 Ying Zheng, Yayong Wu, Guo-Ping Jiang
With the rapid development of network information technology, synchronization problem of complex dynamical networks has garnered extensive attention. Current research predominantly concentrates on analyzing synchronizability and synchronization control in the complex dynamical networks with static edge weights or single weight attribute connections. However, there is limited research on networks characterized
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“All-or-none” dynamics and local-range dominated interaction leading to criticality in neural systems Physica A (IF 3.3) Pub Date : 2024-03-01 JinHao Yang, Yiming Ding, Zengru Di, DaHui Wang
Since the first observation of criticality in neural systems, many researchers have thought that the nervous system can operate in a critical state, and an increasing number of models equipped with different mechanisms have been proposed. We believe that there are simple mechanisms underlying the criticality in neural systems. We constructed a neural network model to investigate the mechanism underlying
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Modeling dedicated lanes for connected autonomous vehicles with poly-information uncertainties and electronic throttle dynamics Physica A (IF 3.3) Pub Date : 2024-03-01 Zihao Wang, Chen Xing, WENXING ZHU, Xiaolong Ma
Numerous studies have demonstrated that connected autonomous vehicles and human-driven vehicles are now coexisting throughout a transitional phase. Traffic flow can be improved, the system can be stabilized, and less energy will be used with dedicated lanes for connected autonomous vehicles. Additionally, with few communication resources, no communication delivery is ever perfect, leading to issues
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Transparent windows in a layered medium with mosaic layers.Windows distribution by area Physica A (IF 3.3) Pub Date : 2024-03-01 R, o, m, a, n, , Y, e, ., , B, r, o, d, s, k, i, i
The work considers a layered system, the layers of which consist of transparent and opaque elements. At the places where parts of the transparent elements are opposite each other in all layers, a transparent through window is formed. The work is devoted to the case when transparent and opaque elements are the cells of a Voronoi mosaic. The distributions of windows by area were obtained for different
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Uncertainty modeling of connected and automated vehicle penetration rate under mixed traffic environment Physica A (IF 3.3) Pub Date : 2024-03-01 Jiali Peng, Wei Shangguan, Cong Peng, Linguo Chai
Accurate knowledge of the penetration rate of connected and automated vehicles (CAVs) is crucial for effective control applications during the transition from mixed traffic to full CAV deployment. Previous studies have focused on characterizing or controlling mixed traffic with a fixed CAV penetration rate. However, in reality, the on-road penetration rate of CAVs varies, even if their market share
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A strength and sparsity preserving algorithm for generating weighted, directed networks with predetermined assortativity Physica A (IF 3.3) Pub Date : 2024-02-28 Yelie Yuan, Jun Yan, Panpan Zhang
Degree-preserving rewiring is a widely used technique for generating unweighted networks with given assortativity, but for weighted networks, it is unclear how an analog would preserve the strengths and other critical network features such as sparsity level. This study introduces a novel approach for rewiring weighted networks to achieve desired directed assortativity. The method utilizes a mixed integer
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Surrounding vehicle trajectory prediction under mixed traffic flow based on graph attention network Physica A (IF 3.3) Pub Date : 2024-02-28 Yuan Gao, Jinlong Fu, Wenwen Feng, Tiandong Xu, Kaifeng Yang
This paper proposes a trajectory prediction method based on graph attention network to accurately predict the trajectories of HDV (Human Drive Vehicles) around the ICV (Intelligent Connected Vehicles) under mixed traffic flow scenario on highways. Firstly, the vehicle trajectory data is filtered and smoothed to construct a trajectory prediction dataset containing map information. Secondly, the vehicle
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Resilience analysis of highway network under rainfall using a data-driven percolation theory-based method Physica A (IF 3.3) Pub Date : 2024-02-28 Yang Li, Jialu Wu, Yunjiang Xiao, Hangqi Hu, Wei Wang, Jun Chen
This paper proposes a data-driven approach using percolation theory to analyze the resilience of highway networks under rainfall conditions. The proposed approach's main contribution is integrating real-world traffic data with percolation theory to evaluate the impact of rainfall on traffic flow and identify the critical links of highway networks. The resilience indicators, accounting for network topology
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Modular nudging models: Formulation and identification from real-world traffic data sets Physica A (IF 3.3) Pub Date : 2024-02-28 Jing Li, Di Liu, Simone Baldi
The vehicle nudging behaviour suggests that a vehicle in the traffic flow may induce a ‘pushing effect’ to its preceding vehicle. In other words, while the traditional vehicle-following behaviour results in look-ahead interaction, the nudging behaviour may result in look-behind interaction: the combination of the two effects would result in bidirectional inter-vehicle interactions. Unfortunately, all
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Effects of three-faced strategy on the evolution of cooperation in social dilemma Physica A (IF 3.3) Pub Date : 2024-02-27 Sinan Feng, Xuesong Liu
Cooperative behavior can contribute to the development of society. Evolutionary game theory is a fundamental framework for studying cooperative behavior. This article explores the evolutionary dynamics of the three-faced strategy, which can demonstrate its different attribute behaviors according to different types of objects encountered by paying a certain role-switching cost. When three-faced individuals
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A multi-task spatio-temporal generative adversarial network for prediction of travel time reliability in peak hour periods Physica A (IF 3.3) Pub Date : 2024-02-27 Feng Shao, Hu Shao, Dongle Wang, William H.K. Lam
Travel time reliability (TTR) serves as a crucial indicator for evaluating the efficiency and service quality of a road traffic network. This paper proposes a multi-task spatio-temporal generative adversarial network (MTST-GAN) model that simultaneously predicts the TTR in morning and evening peak hour periods. The model incorporates multi-graph convolutional networks to extract spatial correlations
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Analysis of local density during football stadium access: Integrating pedestrian flow simulations and empirical data Physica A (IF 3.3) Pub Date : 2024-02-27 Ander García, Dariel Hernández-Delfin, Borja González, Germán Garitaonaindia, Dae-Jin Lee, Marco Ellero
This study analyzes numerically the access of football fans to a typical football stadium through pedestrian flow simulations. With this aim, we introduce a novel framework to address the difficulty of simulating pedestrian dynamics in highly complex geometries with multiple accesses. The framework consists of a combination of the Social Force Model (SFM) and Computational Fluid Dynamics tools to calculate
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Accurate solution of the Index Tracking problem with a hybrid simulated annealing algorithm Physica A (IF 3.3) Pub Date : 2024-02-27 Álvaro Rubio-García, Samuel Fernández-Lorenzo, Juan José García-Ripoll, Diego Porras
An actively managed portfolio almost never beats the market in the long term. Thus, many investors often resort to passively managed portfolios whose aim is to follow a certain financial index. The task of building such passive portfolios aiming also to minimize the transaction costs is called Index Tracking (IT), where the goal is to track the index by holding only a small subset of assets in the
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Multistep traffic speed prediction: A sequence-to-sequence spatio-temporal attention model Physica A (IF 3.3) Pub Date : 2024-02-27 Di Yang, Hong Li, Peng Wang, Lihong Yuan
Multistep traffic speed prediction plays a crucial role in alleviating road congestion and improving transport efficiency. In actual traffic networks, the spatio-temporal dependence among roads dynamically changes over time due to factors such as road conditions and unforeseen incidents, which brings great challenges to multistep traffic speed prediction. Additionally, multistep traffic speed prediction
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Impact of detour on traffic flow in branching Koch curve network with bottleneck Physica A (IF 3.3) Pub Date : 2024-02-24 Takashi Nagatani
There are various routes with and without detours in city traffic network with a complex connectivity. Branching Koch curve fractal has such complex connectivity with singly, doubly, and multiply connecting links. We consider branching Koch curve as a city traffic network. We study the effect of detour routes (bypasses) on macroscopic traffic flow in branching Koch curve network with a bottleneck.
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Analytical results in calculating the entropy of recurrence microstates Physica A (IF 3.3) Pub Date : 2024-02-24 Felipe Eduardo Lopes da Cruz, João Vitor Vieira Flauzino, Sergio Roberto Lopes, Thiago de Lima Prado
Since the development of recurrence plots (RP) and recurrence quantification analysis (RQA), there has been a growing interest in many areas in studying physical systems using recursion techniques. In particular, as part of the RQAs, we observed the development of the concept of recurrence microstates, defined as small blocks obtained from a recurrence graph. It can be shown that some other RQAs can
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Collective dynamics of fluctuating-damping coupled oscillators in network structures: Stability, synchronism, and resonant behaviors Physica A (IF 3.3) Pub Date : 2024-02-24 Ruoqi Zhang, Lin Meng, Lei Yu, Sihong Shi, Huiqi Wang
The investigation of collective behaviors and synergies in coupled systems holds great significance in many fields. In this paper, we propose the coupled system of overdamped fluctuating-damping oscillators in a general network framework. Our initial theoretical analysis focuses on the system’s synchronization and stability, revealing that both the first and second moments of the mean field are asymptotic
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Cooperative control of dynamic CAV dedicated lanes and vehicle active lane changing in expressway bottleneck areas Physica A (IF 3.3) Pub Date : 2024-02-22 Yunran Di, Weihua Zhang, Heng Ding, Xiaoyan Zheng, Bin Ran
Bottleneck areas on expressways plague the operational efficiency of entire road systems. In mixed traffic flow environments consisting of connected and autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs), it is believed that road capacity can be improved to relieve traffic congestion in bottleneck areas by setting CAV dedicated lanes (CDLs) on expressways. Existing static CDL setup
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Urban rail transit passenger flow prediction with ResCNN-GRU based on self-attention mechanism Physica A (IF 3.3) Pub Date : 2024-02-22 Changxi Ma, Bowen Zhang, Shukai Li, Youpeng Lu
With the development of modern cities, urban rail transit has become an indispensable part of residents' travelling mode, and accurate prediction of urban rail transit passenger flow is particularly important. However, due to the non-linearity and non-stability of passenger flow, the low quality of big data and the lack of data make it more and more difficult to predict the passenger flow of urban
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Interplay of network topologies in aviation delay propagation: A complex network and machine learning analysis Physica A (IF 3.3) Pub Date : 2024-02-22 Qiang Li, Lu Wu, Xinjia Guan, Ze-jin Tian
In this study, the fundamental characteristics of flight delay propagation and the key factors influencing such propagation are investigated. Three distinct types of networks were constructed: an aviation network, a traffic flow network, and a delay propagation network. Employing complex network theory, an analysis of the fundamental topological attributes of each network was conducted, exploring the
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Simulating the bi-directional pedestrian flow under high densities by a Floor Field Cellular Automaton model Physica A (IF 3.3) Pub Date : 2024-02-22 Shuyi Fang, Cheng-Jie Jin, Rui Jiang, Dawei Li
In this paper we propose one floor field cellular automaton model, which can simulate the bi-directional pedestrian flow at high densities. Based on the model rules proposed by Nowak and Schadschneider, we make some modifications, including changes of cell size, realistic velocity configurations and extended lateral movement. The best parameters are determined by the results of sensitivity analysis
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Multifractal information on reading eye tracking data Physica A (IF 3.3) Pub Date : 2024-02-21 Marcos M. Meo, Francisco R. Iaconis, Jessica A. Del Punta, Claudio A. Delrieux, Gustavo Gasaneo
The study of the multifractal characteristics of physiological processes attracted wide interest in recent decades, since evidence has been found that the presence of certain alterations in these processes is reflected in the variability of their dynamics. However, neurocognitive processes have not been so widely studied from this perspective. We aim to provide new insights regarding the alterations
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Recovering network topology and dynamics from sequences: A machine learning approach Physica A (IF 3.3) Pub Date : 2024-02-20 Lucas Guerreiro, Filipi N. Silva, Diego R. Amancio
Sequences are prevalent in myriad real-world scenarios, making it imperative to discern the mechanisms behind symbol generation and, subsequently, to decode complex system behaviors. Diverging from conventional graph analysis methods that primarily relies on Markov chains and time series analysis, this paper offers a fresh perspective based on network science to understand sequences produced by agents
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Diffusion coefficient expression for asymmetric discrete random walk with unequal jump times, lengths, and probabilities Physica A (IF 3.3) Pub Date : 2024-02-20 Guoxing Lin, Shaokuan Zheng
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Financial risk contagion based on dynamic multi-layer network between banks and firms Physica A (IF 3.3) Pub Date : 2024-02-20 Qichao Jin, Lei Sun, Yanyu Chen, Zhao-Long Hu
Banks and firms play pivotal roles within the financial system and serve as primary channels for systemic risk contagion. While progress has been made in understanding risk contagion within financial network systems, many studies tend to overlook the intricate interplay of multi-channel risk transmission and the dynamic evolution of network structures. Leveraging complex network theory, we have developed
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A permutation entropy analysis of Bitcoin volatility Physica A (IF 3.3) Pub Date : 2024-02-20 Praise Otito Obanya, Modisane Seitshiro, Carel Petrus Olivier, Tanja Verster
Cryptocurrencies are widely regarded as volatile and less predictable assets by financial participants. The behaviour and dynamics of Bitcoin’s daily volatility, obtained by fitting GARCH models, are investigated for a period of 8 years using permutation entropy which is represented by the variable for calculations. The best fitting GARCH models selected are the FIGARCH(1,0.7,1) and SGARCH(1,1) models
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The role of occupancy on traffic flow in a multiple-loop network Physica A (IF 3.3) Pub Date : 2024-02-19 Muskan Verma, Tanvi Singla, Arvind Kumar Gupta, Sapna Sharma
A dynamic model for traffic flow is proposed to analyze the impact of occupancy in a multiple-loop network with a single intersection. The graph representation of multiple-loop lines is obtained utilizing the cell-transmission model, and consequently, the density equations are derived. The macroscopic fundamental diagrams are investigated for different cases of occupancy and the fraction of vehicles
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Fast Trajectory Extraction and Pedestrian Dynamics Analysis Using Deep Neural Network Physica A (IF 3.3) Pub Date : 2024-02-19 Ruolong Yi, Mingyu Du, Weiguo Song, Jun Zhang
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Macroscopic fluctuation theory of local time in lattice gases Physica A (IF 3.3) Pub Date : 2024-02-19 Naftali R. Smith, Baruch Meerson
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Public and private beliefs under disinformation in social networks Physica A (IF 3.3) Pub Date : 2024-02-19 Diana Riazi, Giacomo Livan
We develop a model of opinion dynamics where agents in a social network seek to learn a ground truth among a set of competing hypotheses. Agents in the network form private beliefs about such hypotheses by aggregating their neighbours’ publicly stated beliefs, in an iterative fashion. This process allows us to keep track of scenarios where private and public beliefs align, leading to population-wide
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Practical quantum protocols for blind millionaires’ problem based on rotation encryption and swap test Physica A (IF 3.3) Pub Date : 2024-02-17 Xi Huang, Wenfang Zhang, Shibin Zhang
Millionaires’ problem, as the most fundamental problem in secure multiparty computation (SMC), has attracted much attention in recent years. Blind millionaires’ problem, an extension of millionaires’ problem, enables to determine the size relationship of the secrets sum. In this paper, two practical quantum protocols based on rotation encryption and swap test are proposed, which can essentially solve
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Repeated quantum game as a stochastic game: Effects of the shadow of the future and entanglement Physica A (IF 3.3) Pub Date : 2024-02-17 Archan Mukhopadhyay, Saikat Sur, Tanay Saha, Shubhadeep Sadhukhan, Sagar Chakraborty
We present a systematic investigation of the quantum games, constructed using a novel repeated game protocol, when played repeatedly ad infinitum. We focus on establishing that such repeated games—by virtue of inherent quantum-mechanical randomness—can be mapped to the paradigm of stochastic games. Subsequently, using the setup of two-player–two-action games, we explore the pure reactive strategies
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Efficient dynamic quantum secret sharing in pre-measurement and post-measurement phases Physica A (IF 3.3) Pub Date : 2024-02-17 Jason Lin, Chang-Chi Chen, Chung-Yung Huang
This study introduces a novel dynamic quantum secret sharing (DQSS) protocol that utilizes entanglement swapping, Bell measurements, and single-particle measurements to enable agent addition and revocation in both the pre-measurement and post-measurement phases. Since the dealer is only required to prepare Bell states for execution, the proposed DQSS offers greater flexibility and practicality compared
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A hybrid forecasting framework based on MCS and machine learning for higher dimensional and unbalanced systems Physica A (IF 3.3) Pub Date : 2024-02-16 Guo-Hui Yang, Guang-Yan Zhong, Li-Ya Wang, Zu-Guang Xie, Jiang-Cheng Li
Forecasting methods and theories have been widely researched and applied in complex systems and fields such as statistical physics, econophysics, material crystals, etc. However, challenges persist in applying these methods to complex systems characterized by high dimensionality, data imbalance, and single prediction evaluation. To address these issues, we propose a novel hybrid forecasting approach
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A time-varying driving style oriented model predictive control for smoothing mixed traffic flow Physica A (IF 3.3) Pub Date : 2024-02-16 Haoli Lou, Hao Lyu, Rongjun Cheng
Connected and automated vehicles (CAVs) have great potential to smooth mixed traffic flow. To focus on the fact that the driving styles of HDVs are time-varying, a new control framework based on time-varying model predictive control (MPC) is proposed for mixed traffic flow in longitudinal control. Firstly, a genetic algorithm can be employed to calibrate the parameters of the car-following model based
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Anticipation promotes the velocity alignment in collective motion Physica A (IF 3.3) Pub Date : 2024-02-15 Yongjian Zhou, Tao Wang, Tonghao Wang, Xiaokang Lei, Xingguang Peng
Anticipation is a fundamental capacity found in many living organisms, particularly in humans. In this study, we investigate the influence of anticipation on collective behavior based on a self-propelled model that relies on solely attractive interaction forces. Focal particles employ anticipation to predict the future positions of neighboring particles, foreseeing their locations time steps ahead
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Regulating spatiotemporal dynamics for a delay Gierer–Meinhardt model Physica A (IF 3.3) Pub Date : 2024-02-15 Haoming He, Min Xiao, Jiajin He, Weixing Zheng
As a classical activator-inhibitor system with diffusion effects, the Gierer–Meinhardt (GM) model has received a considerable attention in recent years. Discussions on dynamic behaviors of the GM model are well underway. However, we still lack the means to further detect the bifurcation direction and the stability of bifurcated periodic solutions as a Hopf bifurcation appears in the space–time evolution
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Optimizing the connectedness of recommendation networks for retrieval accuracy and visiting diversity of random walks Physica A (IF 3.3) Pub Date : 2024-02-15 Lei Hou, Yichen Huang
Recommendation networks have been widely implemented on online systems, where each object connects to several similar others with hyperlinks. A typical example is Amazon’s “customers who bought this item also bought” list. Though the recommendation list length is potentially pivotal in determining the connectedness of recommendation networks, how such list length influences the systems’ navigation
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An elementary mean-field approach to the spectral densities of random matrix ensembles Physica A (IF 3.3) Pub Date : 2024-02-15 Wenping Cui, Jason W. Rocks, Pankaj Mehta
We present a simple mean-field approach for calculating spectral densities for random matrix ensembles in the thermodynamic limit. Our approach is based on constructing a linear system of equations and calculating how the solutions to these equation change in response to a small perturbation using the zero-temperature cavity method. We illustrate the power of the method by providing simple analytic
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Jackpot statistics, a physicist’s approach Physica A (IF 3.3) Pub Date : 2024-02-15 István Gere, Szabolcs Kelemen, Zoltán Néda, Tamás S. Biró
At first glance lottery is a form of gambling, a game in which the chances of winning are extremely small. But upon a deeper look, considering that the Jackpot prize of lotteries is a result of the active participation of millions of players, we come to the conclusion that the interaction of the simple rules with the high number of players creates an emergent complex system. Such a system is characterized
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Ground states of a distinct spin–orbit-coupled spin-1 Bose–Einstein Condensate in a toroidal trap Physica A (IF 3.3) Pub Date : 2024-02-15 Ning Yue, Yong-Kai Liu
This study delves into the influence of a new type of spin–orbit coupling (SOC) on spin-1 Bose–Einstein condensates (BECs) in quasi-two-dimensional annular regions. The unconventional characteristics of the annular potential trap coupled with innovative artificial gauge field bring about a diverse array of phase diagrams for the ground state behavior of the BECs. In the antiferromagnetic state, we
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On the repeated epidemic waves Physica A (IF 3.3) Pub Date : 2024-02-15 A.I. Shnip, S.A. Trigger
Based on the discrete model of infection spread in a closed population, appearance of epidemic waves associated with strengthening and weakening quarantine measures in the present paper is shown. The effect of quarantine measures is considered in the model under consideration via time dependence in the infection transmission rate. It was shown that the epidemic development is controlled by four key
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Detecting non-uniform structures in oil-in-water bubbly flow experiments Physica A (IF 3.3) Pub Date : 2024-02-15 Meng Du, Fei-fan Ren, Rui Min, Zhen-qian Zhang, Zhong-ke Gao, Celso Grebogi
In this work, we first design a series of oil bubbly flow experiments in a vertical testing pipe, and collected the fluid fluctuations as experimental observations. Then we establish a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) from 4272 fluid time-frequency features, which is used to detect anomalous fluctuations in the experimental oil bubbly flow signals. These anomalous fluctuations
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Exploring cascading failure processes of interdependent multi-modal public transit networks Physica A (IF 3.3) Pub Date : 2024-02-13 Xiaohan Xu, Ailing Huang, Amer Shalaby, Qian Feng, Mingyang Chen, Geqi Qi
Maintaining the reliable operation of multi-modal public transit networks (MPTNs) is of great significance in improving urban public transit systems. However, most of the studies on the dynamic robustness of PTNs focus on individual modes and cannot reveal the complexity caused by the coupling of different modes in MPTNs. In addition, there is still a gap in the research on the modeling of MPTNs and
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Hierarchical-attention-based neural network for gait emotion recognition Physica A (IF 3.3) Pub Date : 2024-02-13 Sainan Zhang, Jun Zhang, Weiguo Song, Longnan Yang, Xuedan Zhao
Human gait is an emerging biometric feature and contains important information for long-distance emotion recognition. However, sadness and neutral emotions are easily misjudged during the recognition process, because the body posture of the two emotions is quite similar. Existing methods have difficulty in distinguishing these two emotions satisfactorily since they treat all action features equally
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Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations Physica A (IF 3.3) Pub Date : 2024-02-12 Werner Kristjanpoller, Ramzi Nekhili, Elie Bouri
Blockchain exchange-traded funds (ETFs) are nascent products in the financial industry. A limited literature focuses on the multifractal analysis of some conventional ETFs, but the multifractal behaviour of the blockchain ETF market has not been studied. In this paper, we investigate the multifractal and asymmetric cross-correlation features between blockchain ETFs and the cryptocurrency and Nasdaq
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Itô-distribution from Gibbs measure and a comparison with experiment Physica A (IF 3.3) Pub Date : 2024-02-12 Abhinav Dhawan, A. Bhattacharyay
Langevin dynamics of a confined Brownian particle with coordinate–dependent diffusion involves multiplicative noise. Mathematically, equilibrium of such a stochastic system with multiplicative noise is an Itô–process. However, in physics literature, the process and resulting Itô–distribution are not considered to represent equilibrium because the distribution is a modified Boltzmann distribution. Itô–distribution
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The dynamics of traffic congestion: Data from a freeway Electronic Toll Collection system Physica A (IF 3.3) Pub Date : 2024-02-12 T.S. Choi, Kiwing To, K.Y. Michael Wong
Electronic Toll Collection systems installed at regular intervals along freeways provide a tremendous amount of individualized vehicle data useful for traffic analyses and predictions. We demonstrate how real data from the Taiwan freeway system enables us to monitor the evolution of traffic congestions on the fundamental diagram, and find that congestion is characterized by a loopy trajectory such
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Regional traffic flow combination prediction model considering virtual space of the road network Physica A (IF 3.3) Pub Date : 2024-02-11 Yue Hou, Di Zhang, Da Li, Zhiyuan Deng
Accurate traffic flow forecasting is an important technical measure to alleviate traffic congestion. Since traffic flow has spatial and temporal characteristics, thus the adequate extraction of its spatio-temporal features is an important prerequisite to promote the forecast accuracy of the model. However, a majority of existing traffic flow prediction models cannot sufficiently consider the neighborhood