New Monte Carlo Algorithm for Evaluation of Outgoing Polarized Radiation

2018 ◽  
pp. 115-125
Author(s):  
Gennady A. Mikhailov ◽  
Natalya V. Tracheva ◽  
Sergey A. Ukhinov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Algorithm ◽  
Polarized Radiation

Numerical statistical study of the angular distribution of the polarized radiation scattered by a medium

2017 ◽  
Vol 32 (2) ◽  
Author(s):  
Natalya V. Tracheva ◽  
Sergey A. Ukhinov
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Statistical Study ◽  
Expansion Method ◽  
Statistical Modelling ◽  
Monte Carlo Algorithm ◽  
Polarization Characteristics ◽  
Polarized Radiation

AbstractA Monte Carlo algorithm for studying the spatial-angular distribution of polarization characteristics of the radiation scattered by a medium is developed. The algorithm is based on the projection expansion method for the density of the corresponding angular distribution over polynomials orthonormalized with a ‘Lambert’ weight. The influence of parameters of the medium on angular characteristics of the polarized radiation transmitted through and reflected by dense layers of the medium is studied with the use of numerical statistical modelling.

Two-dimensional projection Monte Carlo estimators for the study of angular characteristics of polarized radiation

2018 ◽  
Vol 33 (3) ◽  
pp. 187-197 ◽  
Author(s):  
Natalya V. Tracheva ◽  
Sergey A. Ukhinov
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Algorithm ◽  
Polarization Degree ◽  
Angular Distributions ◽  
Two Dimensional ◽  
Numerical Estimation ◽  
Thick Layers ◽  
Hemispherical Harmonics ◽  
Polarized Radiation

Abstract The paper presents a Monte Carlo algorithm for the study of bidirectional angular characteristics of a scattered polarized radiation based on projection expansion of the density of the corresponding angular distribution over hemispherical harmonics. The results of numerical estimation of two-dimensional angular distributions of the intensity and the polarization degree of the radiation passed through and reflected from optically thick layers of scattering and absorbing substance are presented.

Examining sharp restart in a Monte Carlo method for the linearized Poisson–Boltzmann equation

2020 ◽  
Vol 26 (3) ◽  
pp. 223-244
Author(s):  
W. John Thrasher ◽  
Michael Mascagni
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Monte Carlo Algorithm ◽  
Significant Bias ◽  
Poisson Boltzmann ◽  
Electrostatic Free Energy ◽  
Poisson Boltzmann Equation ◽  
The Stability ◽  
Potential Methods ◽  
The Individual

AbstractIt has been shown that when using a Monte Carlo algorithm to estimate the electrostatic free energy of a biomolecule in a solution, individual random walks can become entrapped in the geometry. We examine a proposed solution, using a sharp restart during the Walk-on-Subdomains step, in more detail. We show that the point at which this solution introduces significant bias is related to properties intrinsic to the molecule being examined. We also examine two potential methods of generating a sharp restart point and show that they both cause no significant bias in the examined molecules and increase the stability of the run times of the individual walks.

Sign in / Sign up

Export Citation Format

Share Document