scholarly journals Monte Carlo study of magnetic structures in rare-earth amorphous alloys

2018 ◽  
Vol 185 ◽  
pp. 04017
Author(s):  
Alexey Bondarev ◽  
Igor Bataronov
Keyword(s):  
Monte Carlo ◽  
Correlation Functions ◽  
Amorphous Alloys ◽  
Magnetic Phase ◽  
Monte Carlo Study ◽  
Spin Correlation ◽  
Magnetic Structures ◽  
Random Anisotropy ◽  
The Monte Carlo Method ◽  
The Difference

Using the Monte Carlo method, we studied magnetic properties of the models of Re-Tb and Re-Gd amorphous alloys as well as pure amorphous Tb and Gd. The magnetic phase diagrams for the models of amorphous Tb and Gd were constructed. We determined the values of D/J0 (for Tb) and J1/|J2| (for Gd) at which the transition into spin-glass-like state takes place. The local magnetic structure was studied by the spin correlation functions and the angular spin correlation functions. The difference in magnetic structures in amorphous alloys with the random anisotropy and with fluctuations of exchange interaction was revealed.

Monte Carlo study of magnetic phase transitions in a model forFeCl2

1993 ◽  
Vol 47 (5) ◽  
pp. 2602-2606 ◽  
Author(s):  
Laura Hernández ◽  
H. T. Diep ◽  
D. Bertrand
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Magnetic Phase ◽  
Monte Carlo Study ◽  
Magnetic Phase Transitions

Reduction of Computing Time and Improvement of Convergence Stability of the Monte Carlo Method Applied to Radiative Heat Transfer With Variable Properties

1989 ◽  
Vol 111 (1) ◽  
pp. 135-140 ◽  
Author(s):  
M. Kobiyama
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Computing Time ◽  
Energy Difference ◽  
Radiative Properties ◽  
Radiative Energy ◽  
Control Element ◽  
The Monte Carlo Method ◽  
The Difference ◽  
Convergence Stability

A modified Monte Carlo method is suggested to reduce the computing time and improve the convergence stability of iterative calculations without losing other excellent features of the conventional Monte Carlo method. In this method, two kinds of radiative bundle are used: energy correcting bundles and property correcting bundles. The energy correcting bundles are used for correcting the radiative energy difference between two successive iterative cycles, and the property correcting bundles are used for correcting the radiative properties. The number of radiative energy bundles emitted from each control element is proportional to the difference in emissive energy between two successive iterative cycles.

A MONTE CARLO STUDY OF SPONTANEOUS CHIRAL SYMMETRY BREAKING IN LATTICE GAUGE THEORIES

1986 ◽  
Vol 01 (04) ◽  
pp. 953-969
Author(s):  
N.S. CRAIGIE ◽  
E. KATZNELSON ◽  
S. MAHMOOD
Keyword(s):  
Monte Carlo ◽  
Symmetry Breaking ◽  
Chiral Symmetry ◽  
Correlation Functions ◽  
Short Distance ◽  
Chiral Symmetry Breaking ◽  
Monte Carlo Study ◽  
Small Mass ◽  
Theoretical Problem ◽  
Spontaneous Chiral Symmetry Breaking

Spontaneous chiral symmetry breaking in lattice QCD is studied by calculating special four fermion correlation functions using the Monte Carlo method. In the continuum theory in the limit of short distance and small mass these functions are related to the order parameter [Formula: see text]. We found a range of quark mass for which the predicted relations approximately hold, using the Susskind formulation of fermions. However, we encountered a theoretical problem in the latter formulation concerning the short distance behavior of the correlation functions of different spin and flavor. This may cast some doubt on the interpretation of spin and flavor in this formulation.

The Influence of Defects on Proton Diffusion in Perovskites АIIВIV11-xRIIIxO3-δ: Monte Carlo Study

2006 ◽  
Vol 258-260 ◽  
pp. 124-129 ◽  
Author(s):  
V.I. Tsidilkovski ◽  
M.Z. Uritsky ◽  
A.N. Varaksin ◽  
Anatoly Yakovlevich Fishman
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Tracer Diffusion ◽  
Proton Proton ◽  
Dopant Content ◽  
Proton Conducting ◽  
Conducting Oxides ◽  
Proton Diffusion ◽  
The Monte Carlo Method ◽  
Small X

The tracer diffusion coefficient D* and the mobility of protons in proton-conducting oxides of the АIIВIV 1-xRIII xO3-δ family have been calculated using the Monte Carlo method as functions of temperature and concentration x of the acceptor impurity RIII. The effect of protondopant interactions (proton trapping) and the effect of protonic sites blocking caused by protonproton and proton - oxygen vacancy interactions, are analyzed. It is shown that the proton diffusivity depends significantly on the dopant content and is considerably reduced already at small x. The D* value weakly depends on the concentration of oxygen vacancies at fixed, not too large values of x. The conductivity dependence on the doping concentration σ(x) can have a maximum due to the proton-defect and proton-proton interactions. The Haven ratio deviates slightly from unity at the expected intensity of interparticle correlations. The calculated values of both the diffusivity activation energy increase (with x), and the location of the σ(x) maxima agree with the experimental data for a number of proton-conducting oxides.

scholarly journals Analysis of the Accuracy of the Calculation of the Diaphragm Area by the Monte Carlo Method

2020 ◽  
pp. 22-26
Author(s):  
O. D. Kupko
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Circular Aperture ◽  
The Monte Carlo Method ◽  
Relative Standard ◽  
Uniform Probability Distribution ◽  
Standard Deviations ◽  
The Difference

The process of measuring the area of a circular diaphragm using a device that determines the coordinates of the boundary of the diaphragm is theoretically considered. The Monte Carlo method with a small number of implementations was used. The procedure for calculating the area is described in detail. We considered a circular aperture with a precisely known radius. On the circumference of the diaphragm, the coordinate measuring points vibrated through 0.1, 0.3, 0.6, and π/2 radians vibrated. To simulate random deviations (uncertainties) when measuring coordinates, random additives were used with a uniform probability distribution and a given standard deviation. For each case, the areas were calculated in accordance with the proposed procedure. The difference in the results of calculating the area from the true area depending on the number of measurement points and the standard deviation of random additives is analyzed. It is shown that the ratio of the relative standard deviations of the area to the relative standard deviations of the coordinates is approximately the same for each number of measurements. The dependence of this relationship on the number of measurements is determined. The results obtained are analyzed.

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