New Features of the Open Source Monte Carlo Software Brick-CFCMC: Thermodynamic Integration and Hybrid Trial Moves

TI/PIMC METHOD WITH THE TAKAHASHI–IMADA APPROXIMATION FOR THE EQUILIBRIUM CONSTANT OF THE O + HCl ⇌ OH + Cl REACTION

Journal of Theoretical and Computational Chemistry ◽

10.1142/s0219633613500260 ◽

2013 ◽

Vol 12 (04) ◽

pp. 1350026 ◽

Cited By ~ 1

Author(s):

MARCIN BUCHOWIECKI

Keyword(s):

Monte Carlo ◽

Temperature Dependence ◽

Equilibrium Constant ◽

Path Integral ◽

Thermodynamic Integration ◽

Partition Functions ◽

Integration Path ◽

Path Integral Monte Carlo

The thermodynamic integration/path integral Monte Carlo (TI/PIMC) method of calculating the temperature dependence of the equilibrium constant quantum mechanically is applied to O + HCl ⇌ OH + Cl reaction. The method is based upon PIMC simulations for energies of the reactants and the products and subsequently on thermodynamic integration for the ratios of partition functions. PIMC calculations are performed with the primitive approximation (PA) and the Takahashi–Imada approximation (TIA).

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Short communication: A semi-automated method for rapid fault slip analysis from topographic scarp profiles

10.5194/esurf-2019-53 ◽

2019 ◽

Author(s):

Franklin D. Wolfe ◽

Timothy A. Stahl ◽

Pilar Villamor ◽

Biljana Lukovic

Keyword(s):

Monte Carlo ◽

High Resolution ◽

Open Source ◽

Hanging Wall ◽

Temporal Analysis ◽

Fault Scarp ◽

Fault Slip ◽

Source Characterization ◽

Automated Method ◽

Wide Range

Abstract. Here, we introduce an open source, semi-automated, Python-based graphical user interface (GUI) called the Monte Carlo Slip Statistics Toolkit (MCSST) for estimating dip slip on individual or bulk fault datasets. Using this toolkit, profiles are defined across fault scarps in high-resolution digital elevation models (DEMs) and then relevant fault scarp components are interactively identified (e.g., footwall, hanging wall, and scarp). Displacement statistics are calculated automatically using Monte Carlo simulation and can be conveniently visualized in Geographic Information Systems (GIS) for spatial analysis. Fault slip rates can also be calculated when ages of footwall and hanging wall surfaces are known, allowing for temporal analysis. This method allows for rapid analysis of tens to hundreds of faults in rapid succession within GIS and a Python coding environment. Application of this method may contribute to a wide range of regional and local earthquake geology studies with adequate high-resolution DEM coverage, both regional fault source characterization for seismic hazard and/or estimating geologic slip and strain rates, including creating long-term deformation maps. ArcGIS versions of these functions are available, as well ones that utilize free, open source Quantum GIS (QGIS) and Jupyter Notebook Python software.

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Technical Note: Integrating an open source Monte Carlo code “MCsquare” for clinical use in intensity‐modulated proton therapy

Medical Physics ◽

10.1002/mp.14125 ◽

2020 ◽

Vol 47 (6) ◽

pp. 2558-2574 ◽

Cited By ~ 2

Author(s):

Wei Deng ◽

James E. Younkin ◽

Kevin Souris ◽

Sheng Huang ◽

Kurt Augustine ◽

...

Keyword(s):

Monte Carlo ◽

Open Source ◽

Proton Therapy ◽

Technical Note ◽

Monte Carlo Code ◽

Clinical Use ◽

Intensity Modulated Proton Therapy ◽

Intensity Modulated

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Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms

PLoS ONE ◽

10.1371/journal.pone.0147935 ◽

2016 ◽

Vol 11 (1) ◽

pp. e0147935 ◽

Cited By ~ 3

Author(s):

Steffen Rechner ◽

Annabell Berger

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Open Source ◽

Open Source Software ◽

Software Library ◽

Monte Carlo Algorithms

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Accurate determination of the Gibbs energy of Cu–Zr melts using the thermodynamic integration method in Monte Carlo simulations

The Journal of Chemical Physics ◽

10.1063/1.3624530 ◽

2011 ◽

Vol 135 (8) ◽

pp. 084502 ◽

Cited By ~ 14

Author(s):

J.-P. Harvey ◽

A. E. Gheribi ◽

P. Chartrand

Keyword(s):

Monte Carlo ◽

Gibbs Energy ◽

Monte Carlo Simulations ◽

Integration Method ◽

Accurate Determination ◽

Thermodynamic Integration

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Configurational Entropy in Multicomponent Alloys: Matrix Formulation from Ab Initio Based Hamiltonian and Application to the FCC Cr-Fe-Mn-Ni System

Entropy ◽

10.3390/e21010068 ◽

2019 ◽

Vol 21 (1) ◽

pp. 68 ◽

Cited By ~ 7

Author(s):

Antonio Fernández-Caballero ◽

Mark Fedorov ◽

Jan Wróbel ◽

Paul Mummery ◽

Duc Nguyen-Manh

Keyword(s):

Solid Solution ◽

Monte Carlo ◽

Monte Carlo Simulations ◽

Ab Initio ◽

Density Functional ◽

Elevated Temperatures ◽

Thermodynamic Integration ◽

Matrix Formulation ◽

Configuration Entropy ◽

Multi Body

Configuration entropy is believed to stabilize disordered solid solution phases in multicomponent systems at elevated temperatures over intermetallic compounds by lowering the Gibbs free energy. Traditionally, the increment of configuration entropy with temperature was computed by time-consuming thermodynamic integration methods. In this work, a new formalism based on a hybrid combination of the Cluster Expansion (CE) Hamiltonian and Monte Carlo simulations is developed to predict the configuration entropy as a function of temperature from multi-body cluster probability in a multi-component system with arbitrary average composition. The multi-body probabilities are worked out by explicit inversion and direct product of a matrix formulation within orthonomal sets of point functions in the clusters obtained from symmetry independent correlation functions. The matrix quantities are determined from semi canonical Monte Carlo simulations with Effective Cluster Interactions (ECIs) derived from Density Functional Theory (DFT) calculations. The formalism is applied to analyze the 4-body cluster probabilities for the quaternary system Cr-Fe-Mn-Ni as a function of temperature and alloy concentration. It is shown that, for two specific compositions (Cr 25Fe 25Mn 25Ni 25 and Cr 18Fe 27Mn 27Ni 28), the high value of probabilities for Cr-Fe-Fe-Fe and Mn-Mn-Ni-Ni are strongly correlated with the presence of the ordered phases L1 2 -CrFe 3 and L1 0-MnNi, respectively. These results are in an excellent agreement with predictions of these ground state structures by ab initio calculations. The general formalism is used to investigate the configuration entropy as a function of temperature and for 285 different alloy compositions. It is found that our matrix formulation of cluster probabilities provides an efficient tool to compute configuration entropy in multi-component alloys in a comparison with the result obtained by the thermodynamic integration method. At high temperatures, it is shown that many-body cluster correlations still play an important role in understanding the configuration entropy before reaching the solid solution limit of high-entroy alloys (HEAs).

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