scholarly journals Meissner effect in a system of coupled one-dimensional superconducting wires: Monte Carlo simulations

2007 ◽  
Vol 75 (2) ◽  
Author(s):  
Chunyin Qiu ◽  
Tiezheng Qian ◽  
Ping Sheng
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Meissner Effect ◽  
One Dimensional ◽  
Superconducting Wires

scholarly journals A fractional generalization of the dirichlet distribution and related distributions

2021 ◽  
Vol 24 (1) ◽  
pp. 112-136
Author(s):  
Elvira Di Nardo ◽  
Federico Polito ◽  
Enrico Scalas
Keyword(s):  
Monte Carlo ◽  
Probability Density Function ◽  
Monte Carlo Simulations ◽  
Probability Density ◽  
Dirichlet Distribution ◽  
One Dimensional ◽  
Reasonable Approximation ◽  
Generalized Dirichlet Distribution ◽  
The One ◽  
Generalized Dirichlet

Abstract This paper is devoted to a fractional generalization of the Dirichlet distribution. The form of the multivariate distribution is derived assuming that the n partitions of the interval [0, Wn ] are independent and identically distributed random variables following the generalized Mittag-Leffler distribution. The expected value and variance of the one-dimensional marginal are derived as well as the form of its probability density function. A related generalized Dirichlet distribution is studied that provides a reasonable approximation for some values of the parameters. The relation between this distribution and other generalizations of the Dirichlet distribution is discussed. Monte Carlo simulations of the one-dimensional marginals for both distributions are presented.

One-dimensional nanofiller induced crystallization in random copolymers studied by dynamic Monte Carlo simulations

2018 ◽  
Vol 46 (9) ◽  
pp. 669-677 ◽  
Author(s):  
Rongjuan Liu ◽  
Luyao Yang ◽  
Xiaoyan Qiu ◽  
Haitao Wu ◽  
Yongqiang Zhang ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Random Copolymers ◽  
One Dimensional ◽  
Dynamic Monte Carlo ◽  
Induced Crystallization

Interdiffusion in Short-Wavelength Modulated Materials Studied by Monte-Carlo Simulations

1987 ◽  
Vol 103 ◽  
Author(s):  
M. Atzmon
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Interdiffusion Coefficient ◽  
Short Range ◽  
Short Range Order ◽  
Range Order ◽  
One Dimensional ◽  
Interdiffusion Process ◽  
Limiting Value ◽  
Modulation Wavelength

ABSTRACTInterdiffusion in a two-dimensional compositionally modulated lattice has been studied by Monte-Carlo simulations. In the initial stages, the interdiffusion coefficient has been observed to change with time due to the development of short-range order simultaneously with the interdiffusion process. When the short-range order parameter approached its limiting value, the diffusion coefficient approached a constant value. The dependence of the interdiffusion coefficient on the modulation wavelength does not agree with the prediction of one-dimensional theories. For ordering alloy systems, the effective interdiffusion coefficient is positive, i.e., an initially present modulation decays in time, for all wavelengths.

scholarly journals RELAXATION UNDER OUTFLOW DYNAMICS WITH RANDOM SEQUENTIAL UPDATING

2005 ◽  
Vol 16 (11) ◽  
pp. 1771-1783 ◽  
Author(s):  
SYLWIA KRUPA ◽  
KATARZYNA SZNAJD-WERON
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Mean Field ◽  
Square Lattice ◽  
One Dimensional ◽  
Sequential Updating ◽  
The Mean

In this paper we compare the relaxation in several versions of the Sznajd model (SM) with random sequential updating on the chain and square lattice. We start by reviewing briefly all proposed one-dimensional versions of SM. Next, we compare the results obtained from Monte Carlo simulations with the mean field results obtained by Slanina and Lavicka. Finally, we investigate the relaxation on the square lattice and compare two generalizations of SM, one suggested by Stauffer et al. and another by Galam. We show that there are no qualitative differences between these two approaches, although the relaxation within the Galam rule is faster than within the well known Stauffer et al. rule.

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