Complex-valued Monte Carlo method and modified path integrals in the studies of wave localization in random media

1993 ◽  
Author(s):  
Vladimir S. Filinov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Media ◽  
Path Integrals ◽  
Title Complex ◽  
Wave Localization ◽  
Complex Valued

scholarly journals THE FOURTH VIRIAL COEFFICIENT OF ANYONS

1998 ◽  
Vol 13 (21) ◽  
pp. 3723-3747 ◽  
Author(s):  
ANDERS KRISTOFFERSEN ◽  
STEFAN MASHKEVICH ◽  
JAN MYRHEM ◽  
KÅRE OLAUSSEN
Keyword(s):  
Monte Carlo ◽  
Fourier Series ◽  
Monte Carlo Method ◽  
Path Integral ◽  
Virial Coefficient ◽  
Path Integrals ◽  
Second Virial Coefficient ◽  
Virial Coefficients ◽  
Partition Functions ◽  
Two Dimensional

We have computed by a Monte Carlo method the fourth virial coefficient of free anyons, as a function of the statistics angle θ. It can be fitted by a four term Fourier series, in which two coefficients are fixed by the known perturbative results at the boson and fermion points. We compute partition functions by means of path integrals, which we represent diagramatically in such a way that the connected diagrams give the cluster coefficients. This provides a general proof that all cluster and virial coefficients are finite. We give explicit polynomial approximations for all path integral contributions to all cluster coefficients, implying that only the second virial coefficient is statistics dependent, as is the case for two-dimensional exclusion statistics. The assumption leading to these approximations is that the tree diagrams dominate and factorize.

An improved Gaussian laser beam probability distribution simulation based on Monte Carlo method

2020 ◽  
Vol 34 (36) ◽  
pp. 2050414
Author(s):  
Di Gao ◽  
Yanhui Li
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Media ◽  
Sampling Method ◽  
Target Recognition ◽  
Monte Carlo Model ◽  
Gaussian Laser Beam ◽  
Cross Sectional ◽  
Simulation Based ◽  
The Common

Research on target recognition in random media by Monte Carlo method has made rapid progress. However, the commonly used probability sampling function of the emitted photons’ directions is not suitable for simulating the radial cross-sectional distribution of a beam. This sampling has little effect on the simulated laser transmission in clouds, but if the laser range profile (LRP) of a target is simulated, it will cause serious distortion because the common sampling method cannot well represent the radial two-dimensional intensity distribution of the beam. In this paper, the traditional sampling method is improved through rigorous derivation, and the superiority of the method is illustrated by simulation data. The simulation results show that the Monte Carlo model of LRP based on the improved sampling method plays well in profile shape of ideal targets identification. This research can bring more reference and significance to target recognition application.

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