We constructed a theoretical magnetic phase diagram in an external magnetic field , making it possible to determine the conditions for the existence of ferromagnets, antiferromagnets, and spin glass phases. The high-performance CUDA software package was used to the complete enumeration of all configurations of finite number spins in the Ising model. We performed the rigorous numerical calculation of the partition function of systems of interacting spins with open boundary conditions. We used Monte Carlo methods like the Metropolis algorithm to calculate the critical temperatures for spins. The results of the Monte Carlo experiments are consistent with rigorous calculation data. The transition from the spin glass to the induced ferromagnetic state in an external field occurs without any critical change in the heat capacity. We used the Ising model to calculate the instability line (—line) for the heat capacity of spin glass in the diagram in an external magnetic field and the behavior of magnetic susceptibility in an external magnetic field. A rigorous calculation of the partition function allowed us to calculate all possible states and their thermodynamic probability. The calculation of the partition function meant that the model’s physics was obtained in an equilibrium state. The instability line was calculated for spin glass in the equilibrium state.
{"title":"Thermodynamic equilibrium of ±J Ising model on square lattice","authors":"V.O. Trukhin , V.S. Strongin , M.A. Chesnokov , A.G. Makarov , E.A. Lobanova , Y.A. Shevchenko , K.V. Nefedev","doi":"10.1016/j.physa.2024.130172","DOIUrl":"10.1016/j.physa.2024.130172","url":null,"abstract":"<div><div>We constructed a theoretical magnetic phase diagram in an external magnetic field <span><math><mrow><mi>T</mi><mrow><mo>(</mo><msub><mrow><mi>P</mi></mrow><mrow><mo>+</mo></mrow></msub><mo>)</mo></mrow></mrow></math></span>, making it possible to determine the conditions for the existence of ferromagnets, antiferromagnets, and spin glass phases. The high-performance CUDA software package was used to the complete enumeration of all configurations of finite number spins in the <span><math><mrow><mo>±</mo><mi>J</mi></mrow></math></span> Ising model. We performed the rigorous numerical calculation of the partition function of <span><math><mrow><mi>N</mi><mo>=</mo><mn>8</mn><mo>×</mo><mn>8</mn></mrow></math></span> systems of interacting spins with open boundary conditions. We used Monte Carlo methods like the Metropolis algorithm to calculate the critical temperatures for <span><math><mrow><mi>N</mi><mo>=</mo><mn>40</mn><mo>×</mo><mn>40</mn></mrow></math></span> spins. The results of the Monte Carlo experiments are consistent with rigorous calculation data. The transition from the spin glass to the induced ferromagnetic state in an external field occurs without any critical change in the heat capacity. We used the <span><math><mrow><mo>±</mo><mi>J</mi></mrow></math></span> Ising model to calculate the instability line (<span><math><mrow><mi>A</mi><mi>T</mi></mrow></math></span>—line) for the heat capacity of spin glass in the <span><math><mrow><mi>H</mi><mo>−</mo><mi>T</mi></mrow></math></span> diagram in an external magnetic field and the behavior of magnetic susceptibility in an external magnetic field. A rigorous calculation of the partition function allowed us to calculate all possible states and their thermodynamic probability. The calculation of the partition function meant that the model’s physics was obtained in an equilibrium state. The instability line was calculated for spin glass in the equilibrium state.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"655 ","pages":"Article 130172"},"PeriodicalIF":2.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539117","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}
Probabilistic Cellular Automata are a generalization of Cellular Automata. Despite their simple definition, they exhibit fascinating and complex behaviours. The stationary behaviour of these models changes when model parameters are varied, making the study of their phase diagrams particularly interesting. The block approximation method, also known in this context as the local structure approach, is a powerful tool for studying the main features of these diagrams, improving upon Mean Field results. This work considers systems with multiple stationary states, aiming to understand how their interactions give rise to the structure of the phase diagram. Additionally, it shows how a simple algorithmic implementation of the block approximation allows for the effective study of the phase diagram even in the presence of several absorbing states.
{"title":"Block approximations for probabilistic mixtures of elementary cellular automata","authors":"Emilio N.M. Cirillo , Giacomo Lancia , Cristian Spitoni","doi":"10.1016/j.physa.2024.130150","DOIUrl":"10.1016/j.physa.2024.130150","url":null,"abstract":"<div><div>Probabilistic Cellular Automata are a generalization of Cellular Automata. Despite their simple definition, they exhibit fascinating and complex behaviours. The stationary behaviour of these models changes when model parameters are varied, making the study of their phase diagrams particularly interesting. The block approximation method, also known in this context as the local structure approach, is a powerful tool for studying the main features of these diagrams, improving upon Mean Field results. This work considers systems with multiple stationary states, aiming to understand how their interactions give rise to the structure of the phase diagram. Additionally, it shows how a simple algorithmic implementation of the block approximation allows for the effective study of the phase diagram even in the presence of several absorbing states.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"654 ","pages":"Article 130150"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528807","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 : 2024-10-16DOI: 10.1016/j.physa.2024.130164
Hoseung Jang, Unjong Yu
We investigate four types of percolation models — node, edge, bootstrap, and diffusion percolation — in three fractal graphs constructed on the Sierpiński carpet, employing the Monte Carlo method based on the Newman–Ziff algorithm. For each case, we calculate the percolation threshold and critical exponents (, , and ) through the crossing of percolation probabilities and the finite-size scaling analysis, incorporating correction-to-scaling effects. Our results reveal that critical exponents of the percolation phase transition in the three fractal graphs exhibit universality across all four percolation models. Furthermore, we demonstrate that the hyperscaling relation is also valid in the percolation phase transition on the Sierpiński carpet if the spatial dimension is replaced by the Hausdorff dimension.
{"title":"Phase transitions in the node, edge, bootstrap, and diffusion percolation models on the Sierpiński carpet","authors":"Hoseung Jang, Unjong Yu","doi":"10.1016/j.physa.2024.130164","DOIUrl":"10.1016/j.physa.2024.130164","url":null,"abstract":"<div><div>We investigate four types of percolation models — node, edge, bootstrap, and diffusion percolation — in three fractal graphs constructed on the Sierpiński carpet, employing the Monte Carlo method based on the Newman–Ziff algorithm. For each case, we calculate the percolation threshold and critical exponents (<span><math><mi>ν</mi></math></span>, <span><math><mi>γ</mi></math></span>, and <span><math><mi>β</mi></math></span>) through the crossing of percolation probabilities and the finite-size scaling analysis, incorporating correction-to-scaling effects. Our results reveal that critical exponents of the percolation phase transition in the three fractal graphs exhibit universality across all four percolation models. Furthermore, we demonstrate that the hyperscaling relation <span><math><mrow><mi>d</mi><mi>ν</mi><mo>=</mo><mi>γ</mi><mo>+</mo><mn>2</mn><mi>β</mi></mrow></math></span> is also valid in the percolation phase transition on the Sierpiński carpet if the spatial dimension <span><math><mi>d</mi></math></span> is replaced by the Hausdorff dimension.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"655 ","pages":"Article 130164"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527535","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 : 2024-10-16DOI: 10.1016/j.physa.2024.130171
T. Sahdane, R. Masrour, I. Elhnaki
This paper employs Monte Carlo simulations to comprehensively explore the magnetic properties of a spherical nanostructure composed of mixed σ=5/2 and S=2 spins. By systematically varying the proportion (p %) of σ or S spins within the sphere, we investigate the system magnetic behavior, including magnetization, hysteresis loops, remanence, and coercive field. Our findings offer valuable insights into the mechanisms governing the magnetic behavior of this spherical structure, potentially contributing to advancements in fields ranging from data storage to biomedical devices.
本文利用蒙特卡洛模拟全面探索了由σ=5/2 和 S=2 混合自旋组成的球形纳米结构的磁特性。通过系统地改变球内 σ 或 S 自旋的比例（p %），我们研究了系统的磁行为，包括磁化、磁滞回线、剩磁和矫顽力场。我们的研究结果为了解这种球形结构的磁行为机制提供了宝贵的见解，可能有助于推动从数据存储到生物医学设备等领域的发展。
{"title":"Emergence of novel magnetic states in a spherical structure with mixed spins σ=5/2 and S=2: A Monte Carlo simulation study","authors":"T. Sahdane, R. Masrour, I. Elhnaki","doi":"10.1016/j.physa.2024.130171","DOIUrl":"10.1016/j.physa.2024.130171","url":null,"abstract":"<div><div>This paper employs Monte Carlo simulations to comprehensively explore the magnetic properties of a spherical nanostructure composed of mixed σ=5/2 and S=2 spins. By systematically varying the proportion (p %) of σ or S spins within the sphere, we investigate the system magnetic behavior, including magnetization, hysteresis loops, remanence, and coercive field. Our findings offer valuable insights into the mechanisms governing the magnetic behavior of this spherical structure, potentially contributing to advancements in fields ranging from data storage to biomedical devices.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"655 ","pages":"Article 130171"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555567","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 : 2024-10-16DOI: 10.1016/j.physa.2024.130177
Tao Chen, Zhengwu Wang, Jian Xiang, Hao Li
In the future, mixed traffic flow comprising Human-Driven Vehicles (HDVs), Connected and Autonomous Vehicles (CAVs), and CAV platoons will coexist for an extended period. Exploring the operational characteristics of mixed traffic flow under different lane management measures is essential for effective management and control. Initially, we analyze the motion characteristics of HDVs, CAVs, and CAV platoons and identify the car-following types within mixed traffic. Based on vehicle motion characteristics and the variance in maximum desired speeds among HDV drivers, we establish longitudinal motion rules for HDVs using a safety distance model. For CAVs and their platoons, we develop longitudinal motion rules by considering platoon merging and splitting behaviors, as well as speed and spacing error requirements for platoon driving. Subsequently, we formulate lateral lane-change rules based on the Symmetric Two-lane Cellular Automata (STCA) model, considering differences in reaction times and following distances between HDVs and CAVs. Finally, we conducted simulation experiments on a unidirectional three-lane highway using the multi-lane mixed traffic flow cellular automata model, analyzing the characteristics of mixed traffic under various lane management measures, such as mixed lane, CAV-dedicated lane, and CAV-priority lane. The results show that as the proportion of CAV (denoted as p) increases, the traffic flow capacity, optimal density, and jam density also increase. When p≤0.6, the k−q diagram exhibits a triangular shape, whereas for p>0.6, it assumes a trapezoidal shape. Implementing CAV-dedicated lane can reduce Cooperative Adaptive Cruise Control (CACC) degradation rates but only enhances traffic flow capacity when the CAV proportion reaches a certain threshold. Compared to the mixed lane scheme, when p≤0.3 and k≤0.3, the CAV-priority lane schemes not only meet traffic demands but also reduce CACC degradation rates. The vehicle speed in CAV-priority lane surpasses that in HDV lanes, facilitating improved traffic efficiency for CAVs. The distribution of maximum speeds among HDV drivers affects the fundamental diagram of mixed traffic flow and the performance of CAV-priority lane, with greater impacts observed as the standard deviation of the HDVs' maximum speed increases.
{"title":"Analysis of mixed traffic flow characteristics based on cellular automata model under lane management measures","authors":"Tao Chen, Zhengwu Wang, Jian Xiang, Hao Li","doi":"10.1016/j.physa.2024.130177","DOIUrl":"10.1016/j.physa.2024.130177","url":null,"abstract":"<div><div>In the future, mixed traffic flow comprising Human-Driven Vehicles (HDVs), Connected and Autonomous Vehicles (CAVs), and CAV platoons will coexist for an extended period. Exploring the operational characteristics of mixed traffic flow under different lane management measures is essential for effective management and control. Initially, we analyze the motion characteristics of HDVs, CAVs, and CAV platoons and identify the car-following types within mixed traffic. Based on vehicle motion characteristics and the variance in maximum desired speeds among HDV drivers, we establish longitudinal motion rules for HDVs using a safety distance model. For CAVs and their platoons, we develop longitudinal motion rules by considering platoon merging and splitting behaviors, as well as speed and spacing error requirements for platoon driving. Subsequently, we formulate lateral lane-change rules based on the Symmetric Two-lane Cellular Automata (STCA) model, considering differences in reaction times and following distances between HDVs and CAVs. Finally, we conducted simulation experiments on a unidirectional three-lane highway using the multi-lane mixed traffic flow cellular automata model, analyzing the characteristics of mixed traffic under various lane management measures, such as mixed lane, CAV-dedicated lane, and CAV-priority lane. The results show that as the proportion of CAV (denoted as <em>p</em>) increases, the traffic flow capacity, optimal density, and jam density also increase. When <em>p</em>≤0.6, the <em>k</em>−<em>q</em> diagram exhibits a triangular shape, whereas for <em>p</em>>0.6, it assumes a trapezoidal shape. Implementing CAV-dedicated lane can reduce Cooperative Adaptive Cruise Control (CACC) degradation rates but only enhances traffic flow capacity when the CAV proportion reaches a certain threshold. Compared to the mixed lane scheme, when <em>p</em>≤0.3 and <em>k</em>≤0.3, the CAV-priority lane schemes not only meet traffic demands but also reduce CACC degradation rates. The vehicle speed in CAV-priority lane surpasses that in HDV lanes, facilitating improved traffic efficiency for CAVs. The distribution of maximum speeds among HDV drivers affects the fundamental diagram of mixed traffic flow and the performance of CAV-priority lane, with greater impacts observed as the standard deviation of the HDVs' maximum speed increases.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"654 ","pages":"Article 130177"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529185","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 : 2024-10-16DOI: 10.1016/j.physa.2024.130163
M. Senay
Examination of Chandrasekhar’s equilibrium and stability condition for stars in the context of -deformed Maxwell–Boltzmann statistics leads to the derivation of a new analytical formula that extends its classical case. This derivation assumes that the kinetic description of stellar matter conforms to a generalized Maxwell–Boltzmann distribution. It has been found that the maximum allowable radiation pressure at the center of a star for a given mass depends on the deformation parameter . The classical Chandrasekhar condition is recovered in this framework when equals 1.
{"title":"Implications of q-deformed statistics on stellar stability","authors":"M. Senay","doi":"10.1016/j.physa.2024.130163","DOIUrl":"10.1016/j.physa.2024.130163","url":null,"abstract":"<div><div>Examination of Chandrasekhar’s equilibrium and stability condition for stars in the context of <span><math><mi>q</mi></math></span>-deformed Maxwell–Boltzmann statistics leads to the derivation of a new analytical formula that extends its classical case. This derivation assumes that the kinetic description of stellar matter conforms to a generalized Maxwell–Boltzmann distribution. It has been found that the maximum allowable radiation pressure at the center of a star for a given mass depends on the deformation parameter <span><math><mi>q</mi></math></span>. The classical Chandrasekhar condition is recovered in this framework when <span><math><mi>q</mi></math></span> equals 1.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"656 ","pages":"Article 130163"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664327","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 : 2024-10-16DOI: 10.1016/j.physa.2024.130174
Weiwei Qi , Wenyi Wang , Chuanyun Fu
In the current traffic environment dominated by manual driving, existing models of drivers' rear-view perceptions are inadequate. Existing car-following models that incorporate rear-view information are primarily focused on the Internet of Vehicles (IoV) and automated driving environments. However, they fail to realistically reflect the visual processing mechanisms of human drivers, limiting their effectiveness in realistic traffic scenarios. Therefore, we propose a new following model, the multi-vehicle influence from front and rear perspectives (MVFR), that considers the influence of multiple vehicles. The MVFR model combines information from both front and rear vehicles, integrating views from the front, side front and rear. It provides an in-depth analysis of the effects of relative state differences between a vehicle and its surrounding vehicles on speed, including the effects of perspectives in both the lateral and longitudinal directions. Linear stability analysis and numerical simulation demonstrate that considering the perspectives of rear-following vehicles and lateral offset angles can improve traffic flow stability to a certain extent. Furthermore, properly considering the lateral offset distance and the number of vehicles ahead also positively affects traffic flow stability. This study reveals that observing following vehicles and considering information from multiple front vehicles enhances system stability, especially when there is no or minimal lateral offset. In contrast, focusing on fewer front vehicles is more effective for traffic flow stability when there is a large lateral offset. Experimental results using the CKQ4up dataset show that the MVFR model achieves higher accuracy than the conventional FVD model, the front-view-only improved FVD model (MFVD-RV), and the MFRHVAD-RV and MFRHVAD-AV models. Compared with models relying solely on front-view or non-visual perception, the MVFR model demonstrates a better fit, validating the advantages of this full-view perception model in manual driving environments. This innovation addresses the shortcomings of existing research, thereby enhancing the reliability of models under manual driving conditions on highways.
{"title":"A following model considering multiple vehicles from the driver's front and rear perspectives","authors":"Weiwei Qi , Wenyi Wang , Chuanyun Fu","doi":"10.1016/j.physa.2024.130174","DOIUrl":"10.1016/j.physa.2024.130174","url":null,"abstract":"<div><div>In the current traffic environment dominated by manual driving, existing models of drivers' rear-view perceptions are inadequate. Existing car-following models that incorporate rear-view information are primarily focused on the Internet of Vehicles (IoV) and automated driving environments. However, they fail to realistically reflect the visual processing mechanisms of human drivers, limiting their effectiveness in realistic traffic scenarios. Therefore, we propose a new following model, the multi-vehicle influence from front and rear perspectives (MVFR), that considers the influence of multiple vehicles. The MVFR model combines information from both front and rear vehicles, integrating views from the front, side front and rear. It provides an in-depth analysis of the effects of relative state differences between a vehicle and its surrounding vehicles on speed, including the effects of perspectives in both the lateral and longitudinal directions. Linear stability analysis and numerical simulation demonstrate that considering the perspectives of rear-following vehicles and lateral offset angles can improve traffic flow stability to a certain extent. Furthermore, properly considering the lateral offset distance and the number of vehicles ahead also positively affects traffic flow stability. This study reveals that observing following vehicles and considering information from multiple front vehicles enhances system stability, especially when there is no or minimal lateral offset. In contrast, focusing on fewer front vehicles is more effective for traffic flow stability when there is a large lateral offset. Experimental results using the CKQ4up dataset show that the MVFR model achieves higher accuracy than the conventional FVD model, the front-view-only improved FVD model (MFVD-RV), and the MFRHVAD-RV and MFRHVAD-AV models. Compared with models relying solely on front-view or non-visual perception, the MVFR model demonstrates a better fit, validating the advantages of this full-view perception model in manual driving environments. This innovation addresses the shortcomings of existing research, thereby enhancing the reliability of models under manual driving conditions on highways.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"655 ","pages":"Article 130174"},"PeriodicalIF":2.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527633","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 : 2024-10-15DOI: 10.1016/j.physa.2024.130160
Thingujam Yaiphalemba Meitei , Saikumar Krithivasan , Arijit Sen , Md Manirul Ali
Although coherent manipulation of electronic states can be achieved in quantum dot (QD) devices by harnessing nanofabrication tools, it is often hard to fathom the extent to which these nanoelectronic devices can behave quantum mechanically. Witnessing their nonclassical nature would thus remain of paramount importance in the emerging world of quantum technologies, since the coherent dynamics of electronic states plays there a crucial role. Against this backdrop, we resort to the general framework of Leggett–Garg inequalities (LGI) as it allows for distinguishing the classical and quantum transport through nanostructures by way of various two-time correlation functions. Using the local charge detection at two different time, we investigate here theoretically whether any quantum violation of the original LGI exists with varying device configurations and parameters under both Markovian and non-Markovian dynamics. Two-time correlators within LGI are derived in terms of the non-equilibrium Green’s functions (NEGFs) by exactly solving the quantum Langevin equations. The present study of non-Markovian dynamics of quantum systems interacting with reservoirs is significant for understanding the relaxation phenomenon in the ultrafast transient regime to especially mimic what happens to high-speed quantum devices. We can potentially capture the effect of finite reservoir correlation time by accounting for level-broadening at the electrodes along with non-Markovian memory effects. Furthermore, the large bias restriction is no longer imposed in our calculations so that we can safely consider a finite bias between the electronic reservoirs. Our approach is likely to open up new possibilities of witnessing the quantumness for other quantum many-body systems as well that are driven out of the equilibrium.
{"title":"Quantumness of electron transport in quantum dot devices through Leggett–Garg inequalities: A non-equilibrium Green’s function approach","authors":"Thingujam Yaiphalemba Meitei , Saikumar Krithivasan , Arijit Sen , Md Manirul Ali","doi":"10.1016/j.physa.2024.130160","DOIUrl":"10.1016/j.physa.2024.130160","url":null,"abstract":"<div><div>Although coherent manipulation of electronic states can be achieved in quantum dot (QD) devices by harnessing nanofabrication tools, it is often hard to fathom the extent to which these nanoelectronic devices can behave quantum mechanically. Witnessing their nonclassical nature would thus remain of paramount importance in the emerging world of quantum technologies, since the coherent dynamics of electronic states plays there a crucial role. Against this backdrop, we resort to the general framework of Leggett–Garg inequalities (LGI) as it allows for distinguishing the classical and quantum transport through nanostructures by way of various two-time correlation functions. Using the local charge detection at two different time, we investigate here theoretically whether any quantum violation of the original LGI exists with varying device configurations and parameters under both Markovian and non-Markovian dynamics. Two-time correlators within LGI are derived in terms of the non-equilibrium Green’s functions (NEGFs) by exactly solving the quantum Langevin equations. The present study of non-Markovian dynamics of quantum systems interacting with reservoirs is significant for understanding the relaxation phenomenon in the ultrafast transient regime to especially mimic what happens to high-speed quantum devices. We can potentially capture the effect of finite reservoir correlation time by accounting for level-broadening at the electrodes along with non-Markovian memory effects. Furthermore, the large bias restriction is no longer imposed in our calculations so that we can safely consider a finite bias between the electronic reservoirs. Our approach is likely to open up new possibilities of witnessing the quantumness for other quantum many-body systems as well that are driven out of the equilibrium.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"655 ","pages":"Article 130160"},"PeriodicalIF":2.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527537","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 : 2024-10-12DOI: 10.1016/j.physa.2024.130162
Ardvin Kester S. Ong , Mary Christy O. Mendoza , Jean Rondel R. Ponce , Kent Timothy A. Bernardo , Seth Angelo M. Tolentino , John Francis T. Diaz , Michael N. Young
Despite the emergence of more accessible and modern forms of investment, the ever competitive and volatile market remains subject to anomalous irrationalities caused by investors. To this day, predicting their behavior remains difficult with lacking information, and poses a problem for investment platforms to effectively adjust to their predispositions. Therefore, this study aimed to comprehensively analyze the factors that have influenced investors’ behaviors using the integrated construct of the Social Exchange Theory and the Theory of Planned Behavior. With consideration of convenience sampling, a total number of 10,725 data points were collected and analyzed through machine learning algorithms of decision tree and neural network. Specifically, the comparison between long short-term memory (LSTM) and neural network, and random forest classifier and LightGBM were considered. It was found that the investor’s attitude, accessibility to financial services, and perceived economic benefits were the most influential predictors to their behavior, while six other factors also showed varying levels of significance. This study aimed to provide a unique framework which could be utilized by investment platforms to cater to the different behavioral factors expressed by investors. In line with these findings, it is recommended that platforms create flexible solutions that are based on their intentions and preferences, and more user-friendly through the implementation of new technologies. In addition, they are suggested to appeal to novice investors by reducing the burden of costs, promising future benefits, and promoting financial education. The results of this study proved the reliability of the integrated model as a social and behavioral framework, and consequently, LSTM overpowering other tools on accurate forecast made, followed by neural network, and random forest.
{"title":"Analysis of investment behavior among Filipinos: Integration of Social exchange theory (SET) and the Theory of planned behavior (TPB)","authors":"Ardvin Kester S. Ong , Mary Christy O. Mendoza , Jean Rondel R. Ponce , Kent Timothy A. Bernardo , Seth Angelo M. Tolentino , John Francis T. Diaz , Michael N. Young","doi":"10.1016/j.physa.2024.130162","DOIUrl":"10.1016/j.physa.2024.130162","url":null,"abstract":"<div><div>Despite the emergence of more accessible and modern forms of investment, the ever competitive and volatile market remains subject to anomalous irrationalities caused by investors. To this day, predicting their behavior remains difficult with lacking information, and poses a problem for investment platforms to effectively adjust to their predispositions. Therefore, this study aimed to comprehensively analyze the factors that have influenced investors’ behaviors using the integrated construct of the Social Exchange Theory and the Theory of Planned Behavior. With consideration of convenience sampling, a total number of 10,725 data points were collected and analyzed through machine learning algorithms of decision tree and neural network. Specifically, the comparison between long short-term memory (LSTM) and neural network, and random forest classifier and LightGBM were considered. It was found that the investor’s attitude, accessibility to financial services, and perceived economic benefits were the most influential predictors to their behavior, while six other factors also showed varying levels of significance. This study aimed to provide a unique framework which could be utilized by investment platforms to cater to the different behavioral factors expressed by investors. In line with these findings, it is recommended that platforms create flexible solutions that are based on their intentions and preferences, and more user-friendly through the implementation of new technologies. In addition, they are suggested to appeal to novice investors by reducing the burden of costs, promising future benefits, and promoting financial education. The results of this study proved the reliability of the integrated model as a social and behavioral framework, and consequently, LSTM overpowering other tools on accurate forecast made, followed by neural network, and random forest.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"654 ","pages":"Article 130162"},"PeriodicalIF":2.8,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441622","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 : 2024-10-11DOI: 10.1016/j.physa.2024.130152
Mikhail I. Bogachev, Nikita S. Pyko, Nikita Tymchenko, Svetlana A. Pyko, Oleg A. Markelov
Modern information and telecommunication, transportation and logistic, economic and financial systems are represented by complex networks exhibiting traffic flows with spatio-temporal long-term persistence. Conventional queuing theory relies largely upon stationary models where traffic flows are assumed independent and are typically characterized by the first two moments of inter-arrival and service time distributions, leading to drastic underestimations of traffic flow delays. Here we extend a recent superstatistical approach focusing on traffic models with variable arrival rates by accounting for interdependent activity patterns on multiple network nodes. We suggest an analytical correction to the conventional stationary queue model given by the Kingman’s formula based on the calculation of aggregated inter-arrival times variability from the variabilities of arrival rates at individual nodes and cross-correlations between them. We confirm our analytical approximations by comparing with computer simulation results and large-batch empirical traffic analysis from the backbone of a major academic network. We believe that our results, in combination with recent data on the effects of long-term temporal persistence in network traffic flow, are applicable to various complex networks not limited to information and telecommunication, transportation, and logistics but also to economics and finance, rainfall and river flow dynamics, water accumulation in reservoirs, and many other research domains exhibiting spatio-temporal interdependence patterns.
{"title":"Approximate waiting times for queuing systems with variable cross-correlated arrival rates","authors":"Mikhail I. Bogachev, Nikita S. Pyko, Nikita Tymchenko, Svetlana A. Pyko, Oleg A. Markelov","doi":"10.1016/j.physa.2024.130152","DOIUrl":"10.1016/j.physa.2024.130152","url":null,"abstract":"<div><div>Modern information and telecommunication, transportation and logistic, economic and financial systems are represented by complex networks exhibiting traffic flows with spatio-temporal long-term persistence. Conventional queuing theory relies largely upon stationary models where traffic flows are assumed independent and are typically characterized by the first two moments of inter-arrival and service time distributions, leading to drastic underestimations of traffic flow delays. Here we extend a recent superstatistical approach focusing on traffic models with variable arrival rates by accounting for interdependent activity patterns on multiple network nodes. We suggest an analytical correction to the conventional stationary queue model given by the Kingman’s formula based on the calculation of aggregated inter-arrival times variability from the variabilities of arrival rates at individual nodes and cross-correlations between them. We confirm our analytical approximations by comparing with computer simulation results and large-batch empirical traffic analysis from the backbone of a major academic network. We believe that our results, in combination with recent data on the effects of long-term temporal persistence in network traffic flow, are applicable to various complex networks not limited to information and telecommunication, transportation, and logistics but also to economics and finance, rainfall and river flow dynamics, water accumulation in reservoirs, and many other research domains exhibiting spatio-temporal interdependence patterns.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"654 ","pages":"Article 130152"},"PeriodicalIF":2.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529184","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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