Article
Physics, Condensed Matter
Dan Lv, De-zhi Zhang, Min Yang, Feng Wang, Jie Yu
Summary: In this study, Monte Carlo simulation was used to investigate the magnetic and thermodynamic properties of ladder-like boronene nanoribbon with ferrimagnetic mixed-spin (3/2, 2) Ising spin configuration. The results show the magnetic behaviors of the system under different parameters, as well as the occurrence of multi-cycle hysteresis loops under certain parameters.
SUPERLATTICES AND MICROSTRUCTURES
(2021)
Article
Polymer Science
Zhong-yue Gao, Dan Lv, Wei Wang, Jie Yu
Summary: In this study, the dynamic magnetic behaviors of a ferrimagnetic mixed spin-1 and spin-3/2 Ising ladder-type graphene nanoribbon under a time-dependent magnetic field were analyzed using Monte Carlo simulation. The impact of various factors on the magnetic properties and hysteresis behaviors of the system was investigated, revealing the possibility of double-loop hysteresis behavior under certain parameters.
Article
Biochemical Research Methods
Dan Lv, Jin-cheng Liu, Fan Zhang, De-zhi Zhang
Summary: The study investigated the magnetic behaviors of an antiferromagnetic/ferromagnetic mixed spin-5/2 and spin-3/2 Ising bilayer system in a time-dependent magnetic field using the Monte Carlo method. The analysis focused on magnetization, magnetic susceptibility, internal energy, and hysteresis loops, revealing how different physical parameters affect the critical temperature and observing a triple-loop hysteresis behavior.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
(2021)
Article
Materials Science, Multidisciplinary
Linhe Chen, Jing Cai, Wei Zhang
Summary: A study on the magnetic and thermodynamic behaviors of a ferromagnetic mixed-spin L1(0) nanoisland with a layered face center cubic structure using Monte Carlo simulation is conducted. The research focuses on the effects of anisotropies, exchange couplings, external magnetic field, and temperature on magnetization, susceptibility, internal energy, and hysteresis loop. It is found that the system exhibits triple saturation values, single hysteresis loops, and a double peak in the chi curve. The critical temperature and coercivity of the nanoisland depend on the exchange coupling and anisotropy.
JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
(2022)
Article
Materials Science, Multidisciplinary
Brahim Boughazi, Mohamed Kerouad, Abdelhadi Kotri
Summary: Monte Carlo simulation was used to study the magnetic properties of a zigzag graphene-like nanoribbon based on a ferrimagnetic (5/2, 3/2) Ising system. The effects of varying exchange coupling interactions and ion anisotropies on magnetic and thermodynamic properties were investigated, and phase diagrams were provided for different physical parameters. The study also explored the impact of different Hamiltonian parameters on the behavior of multiple-loop hysteresis.
ECS JOURNAL OF SOLID STATE SCIENCE AND TECHNOLOGY
(2022)
Article
Physics, Multidisciplinary
Bo-chen Li, Dan Lv, Wei Wang, Lei Sun, Zi-Ming Hao, Jia Bao
Summary: Using the Monte Carlo method, this study investigates the compensation temperature and hysteresis loops of a ferrimagnetic mixed spin-3/2 and spin-5/2 Ising-type graphene-like bilayer induced by various physical parameters. The variations of magnetization, magnetic susceptibility, specific heat, and internal energy with temperature are discussed. Phase diagrams, including transition temperature and compensation temperature, are also plotted. Multiple hysteresis loops under certain parameters are presented.
COMMUNICATIONS IN THEORETICAL PHYSICS
(2023)
Article
Physics, Multidisciplinary
Chun-lu Chang, Wei Wang, He Ma, Han Huang, Jin-cheng Liu, Rui-ze Geng
Summary: The study investigates the magnetic properties and magnetocaloric effect of a BiFeO3/Co bilayer with mixed-spin through Monte Carlo simulation, revealing that decreasing exchange coupling and increasing external magnetic fields can enhance the magnetic entropy change, adiabatic temperature change, and relative cooling power. The results also include hysteresis loops for different exchange couplings and temperatures.
COMMUNICATIONS IN THEORETICAL PHYSICS
(2021)
Article
Materials Science, Multidisciplinary
Xu Wang, Dan Lv, Lei Sun, Wei Wang, Xu-hang Tu, Zheng-hao Ma
Summary: The Monte Carlo study explores the magnetic behaviors of a ferrimagnetic decorated kagome-like lattice by establishing a mixed spin-2 and spin-5/2 Ising system. Various magnetic properties, including magnetization, susceptibility, internal energy, specific heat, and entropy, have been discussed as functions of temperature under the influence of diverse Hamiltonian parameters. The study also reveals the change of critical temperature and compensation temperature with different parameters, showing potential for multiple-loop hysteresis behaviors due to competition among these parameters.
JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
(2021)
Article
Chemistry, Physical
Michele Invernizzi, Andreas Kraemer, Cecilia Clementi, Frank Noe
Summary: In this paper, a method named Learned Replica Exchange (LREX) is proposed, which combines replica exchange with normalizing flows to efficiently sample rare events. By training a normalizing flow to map the configurations of the fastest-mixing replica into configurations of the target distribution, LREX enables direct exchanges between the two without simulating intermediate replicas, thus significantly reducing computational cost. The proposed method also offers advantages compared to using normalizing flows directly for sampling the target distribution.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Chemistry, Physical
Michele Invernizzi, Andreas Kraemer, Cecilia Clementi, Frank Noe
Summary: We propose a efficient sampling method called learned replica exchange (LREX) by combining replica exchange with normalizing flows, which is a class of deep generative models. LREX allows direct exchanges between the fastest-mixing replica and the target distribution, reducing the computational cost compared to standard replica exchange. It also offers several advantages over Boltzmann generators that directly use normalizing flows to sample the target distribution.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Materials Science, Multidisciplinary
Wei Wang, Lei Sun, Qi Li, Dan Lv, Zhong-yue Gao, Te Huang
Summary: Through Monte Carlo simulation, the magnetic and thermodynamic behaviors of the diluted ferromagnetic spin-3/2 Ising nano-graphene monolayer under the longitudinal magnetic field were explored. The effects of various parameters on magnetic phase transition and hysteresis behaviors were discussed, and phase diagrams for different physical parameters were presented, showing a strong dependence of hysteresis loop characteristics on selected parameters.
JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
(2021)
Article
Physics, Condensed Matter
N. El Mekkaoui, I El Housni, S. Mtougui, H. Labrim, R. Khalladi, S. Idrissi, S. Ziti, L. Bahmad
Summary: In this paper, we investigate the magnetic properties of a core/shell Kekulene-like structure with mixed spins by Monte Carlo simulations, analyzing ground state phase diagrams, magnetizations, susceptibilities, and hysteresis loops.
SOLID STATE COMMUNICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Sanae Zriouel
Summary: Our recent research focuses on the Zigzag FeO2 nanoribbons defected by the removal of oxygen atoms, exploring the impact of oxygen vacancies on dielectric and hysteretic behaviors. The study reveals the presence of second order phase transition and Q-type behavior, with the role of ribbon's edge, positions, and number of removed atoms carefully examined. Additionally, both single and square hysteresis loops are observed regardless of the number of oxygen vacancies in the system.
MATERIALS SCIENCE AND ENGINEERING B-ADVANCED FUNCTIONAL SOLID-STATE MATERIALS
(2021)
Article
Physics, Multidisciplinary
Lei Sun, Dan Lv, Wei Wang, Zhong-yue Gao, Bo-chen Li
Summary: Thermodynamic and magnetocaloric properties of a triple-layer graphene-like structure with mixed spin-3/2 and spin-5/2 have been studied using Monte Carlo simulation. The results show that various exchange couplings and external magnetic field significantly influence the magnetic behaviors and magnetocaloric effect, leading to enhanced magnetization and system stability with increasing exchange couplings or external magnetic field. Additionally, the presence of peaks in magnetic entropy change curves near the critical temperature, which increase with decreasing exchange couplings or increasing external magnetic field, and the enhancement of relative cooling power as exchange couplings decrease or external magnetic field increases, have been observed.
Article
Physics, Condensed Matter
Jia-qi Lv, Wei Wang, Bo-chen Li, Min Yang
Summary: In this study, the compensation behaviors and magnetic properties of an Ising-type bilayer graphyne nanoribbon are examined using the Monte Carlo method. The influence of the length of the nanoribbon and the number of Monte Carlo steps on the magnetic characteristics is investigated. Different parameters, including exchange coupling, crystal field, temperature, and external magnetic field, are also studied. The results show that the system can exhibit interesting behaviors, such as double compensation points and multi-loop hysteresis behaviors, under certain parameters, which may have theoretical implications for multi-state magnetic recording.
PHYSICA B-CONDENSED MATTER
(2023)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)