arXiv subjects

Jian-Sheng Wang

Publications and source records attributed to Jian-Sheng Wang.

At least 163 records · Page 9Linked to original sources

arXiv2003

Intriguing Heat Conduction of a Polymer Chain

We study heat conduction in a one-dimensional chain of particles with longitudinal as well as transverse motions. The particles are connected by two-dimensional harmonic springs together with bending angle interactions. Using equilibrium and nonequilibrium molecular dynamics, three types of thermal conducting behaviors are found: a logarithmic divergence with system sizes for large transverse coupling, 1/3 power-law at intermediate coupling, and 2/5 power-law at low temperatures and weak coupling. The results are consistent with a simple mode-coupling analysis of the same model. The 1/3 power-law divergence should be a generic feature for models with transverse motions.

cond-mat.stat-mech↗

arXiv2003

Transition matrix Monte Carlo and flat-histogram algorithm

In any valid Monte Carlo sampling that realizes microcanonical property we can collect statistics for a transition matrix in energy. This matrix is used to determine the density of states, from which most of the thermodynamical averages can be calculated, including free energy and entropy. We discuss single-spin-flip algorithms, such as flat-histogram and equal-hit algorithms, that can be used for simulations. The flat-histogram algorithm realizes multicanonical ensemble. We demonstrate the use of the method with applications to Ising model and show its efficiency of search for spin-glass ground states.

cond-mat.stat-mech↗

arXiv2002

A comparison of extremal optimization with flat-histogram dynamics for finding spin-glass ground states

We compare the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin-glass ground states. The first-passage-times to a ground state are computed. At optimal parameter of tau=1.15, EO outperforms other methods for small system sizes, but equal-hit algorithm is competitive to EO, particularly for large systems. Flat-histogram and equal-hit algorithms offer additional advantage that they can be used for equilibrium thermodynamic calculations. We also propose a method to turn EO into a useful algorithm for equilibrium calculations. Keywords: extremal optimization. flat-histogram algorithm, equal-hit algorithm, spin-glass model, ground state.

cond-mat.stat-mech↗

arXiv2002

Comments on Sweeny and Gliozzi dynamics for simulations of Potts models in the Fortuin-Kasteleyn representation

We compare the correlation times of the Sweeny and Gliozzi dynamics for two-dimensional Ising and three-state Potts models, and the three-dimensional Ising model for the simulations in the percolation prepresentation. The results are also compared with Swendsen-Wang and Wolff cluster dynamics. It is found that Sweeny and Gliozzi dynamics have essentially the same dynamical critical behavior. Contrary to Gliozzi's claim (cond-mat/0201285), the Gliozzi dynamics has critical slowing down comparable to that of other cluster methods. For the two-dimensional Ising model, both Sweeny and Gliozzi dynamics give good fits to logarithmic size dependences; for two-dimensional three-state Potts model, their dynamical critical exponent z is 0.49(1); the three-dimensional Ising model has z = 0.37(2).

cond-mat.stat-mech↗

arXiv2002

Binary tree summation Monte Carlo simulation for Potts models

In this talk, we briefly comment on Sweeny and Gliozzi methods, cluster Monte Carlo method, and recent transition matrix Monte Carlo for Potts models. We mostly concentrate on a new algorithm known as "binary tree summation". Some of the most interesting features of this method will be highlighted - such as simulating fractional number of Potts states, as well as offering the partition function and thermodynamic quantities as functions of temperature in a single run.

cond-mat.stat-mech↗

arXiv2002

Binary tree summation Monte Carlo method for Potts models

We give a new sampling algorithm for the Potts model based on the Fortuin-Kasteleyn transformation. The method produces independent samples and sums up a large number of configurations for each sweep. The partition function and thermodynamic averages for all values of the temperature can be computed from a single run. We compare the results with exact 2D Ising model.

cond-mat.stat-mech↗

arXiv2001

Flow properties of driven-diffusive lattice gases: theory and computer simulation

We develop n-cluster mean-field theories (0 < n < 5) for calculating the flow properties of the non-equilibrium steady-states of the Katz-Lebowitz-Spohn model of the driven diffusive lattice gas, with attractive and repulsive inter-particle interactions, in both one and two dimensions for arbitrary particle densities, temperature as well as the driving field. We compare our theoretical results with the corresponding numerical data we have obtained from the computer simulations to demonstrate the level of accuracy of our theoretical predictions. We also compare our results with those for some other prototype models, notably particle-hopping models of vehicular traffic, to demonstrate the novel qualitative features we have observed in the Katz-Lebowitz-Spohn model, emphasizing, in particular, the consequences of repulsive inter-particle interactions.

cond-mat.stat-mech↗

arXiv2001

Flat histogram simulation of lattice polymer systems

We demonstrate the use of a new algorithm called the Flat Histogram sampling algorithm for the simulation of lattice polymer systems. Thermodynamics properties, such as average energy or entropy and other physical quantities such as end-to-end distance or radius of gyration can be easily calculated using this method. Ground-state energy can also be determined. We also explore the accuracy and limitations of this method. Key words: Monte Carlo algorithms, flat histogram sampling, HP model, lattice polymer systems

cond-mat.stat-mech↗

arXiv2001

Transition Matrix Monte Carlo Method

We present a formalism of the transition matrix Monte Carlo method. A stochastic matrix in the space of energy can be estimated from Monte Carlo simulation. This matrix is used to compute the density of states, as well as to construct multi-canonical and equal-hit algorithms. We discuss the performance of the methods. The results are compared with single histogram method, multi-canonical method, and other methods. In many aspects, the present method is an improvement over the previous methods. PACS numbers: 02.70.Tt, 05.10.Ln, 05.50.+q. Keywords: Monte Carlo method, flat histogram, multi-canonical ensemble.

cond-mat.stat-mech↗

arXiv2001

Efficient Monte Carlo Simulation Methods in Statistical Physics

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in statistical physics. We discuss their advantages, applications, and some challenge problems which are still awaiting for better solutions. We discuss some of the recent development in simulation where reweighting is used, such as histogram methods and multicanonical method. We then discuss the transition matrix Monte Carlo method and associated algorithms. The transition matrix method offers an efficient way to compute the density of states. Thus entropy and free energy, as well as the usual thermodynamic averages, are obtained as functions of model parameter (e.g. temperature) in a single run. New sampling algorithms, such as the flat histogram algorithm and equal-hit algorithm, offer sampling techniques which generate uniform probability distribution for some chosen macroscopic variable.

cond-mat.stat-mech↗

arXiv2000

A new approach to the study of the ground-state properties of 2D Ising spin glass

A new approach known as flat histogram method is used to study the +/-J Ising spin glass in two dimensions. Temperature dependence of the energy, the entropy, and other physical quantities can be easily calculated and we give the results for the zero-temperature limit. For the ground-state energy and entropy of an infinite system size, we estimate e0 = -1.4007 +/- 0.0085 and s0 = 0.0709 +/- 0.006, respectively. Both of them agree well with previous calculations. The time to find the ground-states as well as the tunneling times of the algorithm are also reported and compared with other methods.

cond-mat.stat-mech↗

arXiv1999

Unequal Intra-layer Coupling in a Bilayer Driven Lattice Gas

The system under study is a twin-layered square lattice gas at half-filling, being driven to non-equilibrium steady states by a large, finite `electric' field. By making intra-layer couplings unequal we were able to extend the phase diagram obtained by Hill, Zia and Schmittmann (1996) and found that the tri-critical point, which separates the phase regions of the stripped (S) phase (stable at positive interlayer interactions J_3), the filled-empty (FE) phase (stable at negative J_3) and disorder (D), is shifted even further into the negative J_3 region as the coupling traverse to the driving field increases. Many transient phases to the S phase at the S-FE boundary were found to be long-lived. We also attempted to test whether the universality class of D-FE transitions under a drive is still Ising. Simulation results suggest a value of 1.75 for the exponent gamma but a value close to 2.0 for the ratio gamma/nu. We speculate that the D-FE second order transition is different from Ising near criticality, where observed first-order-like transitions between FE and its "local minimum" cousin occur during each simulation run.

cond-mat.stat-mech↗

arXiv1999

Flat histogram Monte Carlo method

We discuss a sampling algorithm which generates flat histogram in energy. In combination with transition matrix Monte Carlo, the density of states and derived quantities such as entropy and free energy as a function of temperature can be computed in a single simulation.

cond-mat.stat-mech↗

arXiv1999

Transition Matrix Monte Carlo

Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from independent simulations. In this paper, we describe an complementary approach to extracting information from Monte Carlo simulations that uses the matrix of transition probabilities. Combining the Transition Matrix with an N-fold way simulation technique produces an extremely flexible and efficient approach to rather general Monte Carlo simulations.

cond-mat.stat-mech↗

arXiv1999

Monte Carlo algorithms based on the number of potential moves

We discuss Monte Carlo dynamics based on _E, the (microcanonical) average number of potential moves which increase the energy by Delta E in a single spin flip. The microcanonical average can be sampled using Monte Carlo dynamics of a single spin flip with a transition rate min(1, _E' / _E) from energy E to E'. A cumulative average (over Monte Carlo steps) can be used as a first approximation to the exact microcanonical average in the flip rate. The associated histogram is a constant independent of the energy. The canonical distribution of energy can be obtained from the transition matrix Monte Carlo dynamics. This second dynamics has fast relaxation time - at the critical temperature the relaxation time is proportional to specific heat. The dynamics are useful in connection with reweighting methods for computing thermodynamic quantities.

cond-mat.stat-mech↗

arXiv1999

Series expansion and computer simulation studies of random sequential adsorption

We discuss two important techniques, series expansion and Monte Carlo simulation, for random sequential adsorption study. Random sequential adsorption is an idealization for surface deposition where the time scale of particle relaxation is much longer than the time scale of deposition. Particles are represented as extended objects which are adsorbed to a continuum surface or lattice sites. Once landed on the surface, the particles stick to the surface. We review in some details various methods of computing the coverage theta(t) and present some of the recent and new results in random sequential adsorption.

cond-mat.stat-mech↗

arXiv1999

Anisotropic finite-size scaling analysis of a three-dimensional driven-diffusive system

We study the standard three-dimensional driven diffusive system on a simple cubic lattice where particle jumps along a given lattice direction are biased by an infinitely strong field, while those along other directions follow the usual Kawasaki dynamics. Our goal is to determine which of the several existing theories for critical behavior is valid. We analyze finite-size scaling properties using a range of system shapes and sizes far exceeding previous studies. Four different analytic predictions are tested against the numerical data. Binder and Wang's prediction does not fit the data well. Among the two slightly different versions of Leung, the one including the effects of a dangerous irrelevant variable appears to be better. Recently proposed isotropic finite-size scaling is inconsistent with our data from cubic systems, where systematic deviations are found, especially in scaling at the critical temperature.

cond-mat.stat-mech↗

arXiv1998

Transition Matrix Monte Carlo Method

We analyze a new Monte Carlo method which uses transition matrix in the space of energy. This method gives an efficient reweighting technique. The associated artificial dynamics is a constrained random walk in energy, producing the result that correlation time is proportional to the specific heat.

cond-mat.stat-mech↗