Parallel-Tempering Monte Carlo Study of (H2O)n=6-9

2003 ◽  
Vol 107 (38) ◽  
pp. 7380-7389 ◽  
Author(s):  
Arnold N. Tharrington ◽  
Kenneth D. Jordan
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Parallel Tempering

Exploring repulsive interactions in a model helical peptide: A parallel tempering Monte Carlo study

2003 ◽  
Vol 119 (17) ◽  
pp. 9274-9279 ◽  
Author(s):  
Mayra Ocasio ◽  
Johnny R. Maury-Evertsz ◽  
Belinda Pastrana-Rı́os ◽  
Gustavo E. López
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Parallel Tempering ◽  
Helical Peptide ◽  
Repulsive Interactions

HEAT CAPACITY OF 13- AND 19-ATOM PD–CO BINARY CLUSTERS: PARALLEL TEMPERING MONTE CARLO STUDY

2009 ◽  
Vol 20 (11) ◽  
pp. 1737-1747 ◽  
Author(s):  
HAYDAR ARSLAN ◽  
ALI EKBER IRMAK
Keyword(s):  
Heat Capacity ◽  
Monte Carlo ◽  
Monte Carlo Study ◽  
Parallel Tempering ◽  
Many Body ◽  
Atom Cluster ◽  
Binary Clusters ◽  
Body Potential ◽  
Two Stages ◽  
Bulk Alloys

Alloy nanoclusters are of interest because of their novel properties compared to bulk alloys. In this study, the thermal behavior of 13- and 19-atom Pd–Co binary clusters has been investigated by parallel tempering Monte Carlo technique using the Sutton–Chen many body potential. Clear changes in heat capacity curve are observed as a function of Pd–Co composition. We also found that, the 13-atom cluster melts in two stages and 19-atom cluster melts as a whole.

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study

Monte Carlo study of 50 nm-long single and dual-gate MODFETs: suppression of short-channel effects

1993 ◽  
Vol 3 (9) ◽  
pp. 1719-1728
Author(s):  
P. Dollfus ◽  
P. Hesto ◽  
S. Galdin ◽  
C. Brisset
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Short Channel Effects ◽  
Short Channel ◽  
Channel Effects ◽  
Dual Gate

MONTE CARLO STUDY OF EPITAXIAL OVERLAYER WITH SUBSTANTIAL LATTICE MISMATCH

1987 ◽  
Vol 48 (C5) ◽  
pp. C5-199-C5-202
Author(s):  
T. MIYASAKI ◽  
K. AIZAWA ◽  
H. AOKI ◽  
C. ITOH ◽  
M. OKAZAKI
Keyword(s):  
Monte Carlo ◽  
Lattice Mismatch ◽  
Monte Carlo Study
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