scholarly journals Confined Quantum Hard Spheres

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 775
Author(s):  
Sergio Contreras ◽  
Alejandro Gil-Villegas
Keyword(s):  
Computer Simulation ◽  
Monte Carlo ◽  
Computer Simulations ◽  
Hard Spheres ◽  
Quantum Systems ◽  
Confined Space ◽  
Free Energies ◽  
Classical Systems ◽  
Accessible Volume ◽  
Theoretical Results

We present computer simulation and theoretical results for a system of N Quantum Hard Spheres (QHS) particles of diameter σ and mass m at temperature T, confined between parallel hard walls separated by a distance Hσ, within the range 1≤H≤∞. Semiclassical Monte Carlo computer simulations were performed adapted to a confined space, considering effects in terms of the density of particles ρ*=N/V, where V is the accessible volume, the inverse length H−1 and the de Broglie’s thermal wavelength λB=h/2πmkT, where k and h are the Boltzmann’s and Planck’s constants, respectively. For the case of extreme and maximum confinement, 0.5<H−1<1 and H−1=1, respectively, analytical results can be given based on an extension for quantum systems of the Helmholtz free energies for the corresponding classical systems.

Structure of chemically reacting particles near a hard wall from integral equations and computer simulations

1996 ◽  
Vol 74 (1-2) ◽  
pp. 65-76 ◽  
Author(s):  
A. Trokhymchuk ◽  
D. Henderson ◽  
S. Sokołowski
Keyword(s):  
Monte Carlo ◽  
Computer Simulations ◽  
Hard Spheres ◽  
Total Density ◽  
Hard Wall ◽  
Monte Carlo Data ◽  
Density Profiles ◽  
Interparticle Potential ◽  
Theoretical Predictions ◽  
Chemically Reacting

We performed Monte-Carlo computer simulations of a fluid of chemically reacting, or overlapping, hard spheres near a hard wall. The model of the interparticle potential is that introduced by Cummings and Stell. This investigation is directed to the determination of the structure of the fluid at the wall, and the orientation of the dimers in particular. In addition, we applied the singlet Percus–Yevick, hypernetted chain and Born–Green–Yvon equations to calculate the total density profiles of the particles. A comparison with the Monte-Carlo data indicates that the singlet Percus–Yevick theory is superior and leads to results that are in reasonable agreement with simulations for all the parameters investigated. We also calculated the average numbers of dimers formed in the bulk part of the system and the results are compared with different theoretical predictions.

Evaluation of Free Energy Differences Between Crystalline Phases Using the Lattice-Switch Monte Carlo Method

1997 ◽  
Vol 499 ◽  
Author(s):  
G. J. Ackland ◽  
N. B. Wilding ◽  
A. D. Bruce
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Monte Carlo Method ◽  
Hard Spheres ◽  
Energy Difference ◽  
New Method ◽  
Free Energies ◽  
Free Energy Difference ◽  
Crystal Phases ◽  
The Difference

ABSTRACTA new method [1] of calculating the free energy difference between two crystalline structures is presented. The method involves a single simulation which repeatedly transforms the system between the two crystal phases. Since the configurations of both structures are sampled within a single Monte Carlo process, the difference between their free energies can be evaluated directly from the ratio of the measured probabilities of each. Compared with traditional techniques, the method is most advantageous when applied to highly anharmonic systems. To illustrate the method, an application to the free energy difference between the fee and hep structures of hard spheres is described.

Sampling Distribution of the Coefficient of Variation when the Population Takes Normal Distribution N(0,σ2)

2011 ◽  
Vol 291-294 ◽  
pp. 3300-3304 ◽  
Author(s):  
Jian Mei Xu ◽  
Lun Bai
Keyword(s):  
Computer Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Coefficient Of Variation ◽  
Theoretical Basis ◽  
Quality Index ◽  
Normal Population ◽  
Sampling Distribution ◽  
Important Quality ◽  
Theoretical Results

The coefficient of variation of the raw silk size objectively expresses the fluctuating characteristics of the raw silk size, and is an important quality index in the development of the new standard used in the electronic testing for raw silk. This paper theoretically deduces the sampling distribution of the coefficient of variation of the normal population, justifies the theoretical results by computer simulation using Monte Carlo method, and thus afford important theoretical basis for the development of the new standards for the electronic testing of the raw silk size.

Generation of Correlated Logistic-Normal Random Variates for Medical Decision Trees

1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark
Keyword(s):  
Monte Carlo ◽  
Decision Trees ◽  
Computer Algebra ◽  
Taylor Series ◽  
Computer Algebra System ◽  
Random Variable ◽  
Monte Carlo Analysis ◽  
Normal Random Variable ◽  
Medical Decision ◽  
Theoretical Results

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.

A Computer Simulation Approach for Engineering Air-Jet Spun Yarns

1997 ◽  
Vol 67 (3) ◽  
pp. 223-230 ◽  
Author(s):  
Rangaswamy Rajamanickam ◽  
Steven M. Hansen ◽  
Sundaresan Jayaraman
Keyword(s):  
Computer Simulation ◽  
Computer Simulations ◽  
Fiber Length ◽  
Experimental Investigations ◽  
Simulation Approach ◽  
Air Jet ◽  
Fiber Fineness ◽  
Spun Yarns ◽  
Yarn Count ◽  
Wrap Angle

A computer simulation approach for engineering air-jet spun yarns is proposed, and the advantages of computer simulations over experimental investigations and stand-alone mathematical models are discussed. Interactions of the following factors in air-jet spun yarns are analyzed using computer simulations: yarn count and fiber fineness, fiber tenacity and fiber friction, fiber length and fiber friction, and number of wrapper fibers and wrap angle. Based on the results of these simulations, yarn engineering approaches to optimize strength are suggested.

Computer simulation and theory for free energies in dilute near-critical solutions

AIChE Journal ◽  
1993 ◽  
Vol 39 (12) ◽  
pp. 1985-1994 ◽  
Author(s):  
T. W. Li ◽  
F. Munoz ◽  
E. H. Chimowitz
Keyword(s):  
Computer Simulation ◽  
Free Energies ◽  
Critical Solutions

Computer Simulation of an Synthetic Ultraviolet Absorbent in the Interface of DMB and DMF

2010 ◽  
Vol 146-147 ◽  
pp. 966-971
Author(s):  
Qi Hua Jiang ◽  
Hai Dong Zhang ◽  
Bin Xiang ◽  
Hai Yun He ◽  
Ping Deng
Keyword(s):  
Computer Simulation ◽  
Computer Simulations ◽  
Density Functional ◽  
Density Functional Method ◽  
Mean Field ◽  
Functional Method ◽  
Dynamic Density ◽  
Interface Phase ◽  
Simulation Results

This work studies the aggregation of an synthetic ultraviolet absorbent, named 2-hydroxy-4-perfluoroheptanoate-benzophenone (HPFHBP), in the interface between two solvents which can not completely dissolve each other. The aggregation is studied by computer simulations based on a dynamic density functional method and mean-field interactions, which are implemented in the MesoDyn module and Blend module of Material Studios. The simulation results show that the synthetic ultraviolet absorbent diffuse to the interface phase and the concentration in the interface phase is greater than it in the solvents phase.

Monte Carlo computer simulation of small clusters of methane, ethane, and their mixture

1997 ◽  
Vol 106 (4) ◽  
pp. 1593-1599 ◽  
Author(s):  
Aleksey Vishnyakov ◽  
Elena M. Piotrovskaya ◽  
Elena N. Brodskaya
Keyword(s):  
Computer Simulation ◽  
Monte Carlo ◽  
Monte Carlo Computer Simulation ◽  
Small Clusters
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