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Computational studies of classical disordered spin systems

In this thesis classical disordered spin systems, in particular, the random field Ising model (RFIM), are studied using numerical methods. The previous experimental and theoretical research on the RFIM is reviewed. Critical exponents of the RFIM are extracted at zero temperature. The heat capacity exponent α is found to be near zero. The ground states within a certain region with varying external field and disorder are portrayed, and it is speculated that if related quantities are scaled properly, ground state portraits at different system sizes are statistically similar. The performance of the Wang-Landau (WL) algorithm, which is used in our positive temperature study of the RFIM, is measured by the mean first-passage time. It is proved that the mean first, passage time of the mean field Ising model scales as N 2 log N, where N is the number of spins. The logarithmic correction term to the unbiased Markovian random walk is due to the boundaries. When applied to the Ising model with nearest neighbor interactions, the WL algorithm suffers from power law slowing down. Carefully designed cluster updating, however, can accelerate the WL algorithm and eliminate the slowing down. The WL algorithm is used in our finite temperature study of the RFIM. Physical quantities, such as the specific heat and the susceptibility, are obtained by the WL algorithm over a broad range of temperature. It is discovered that for some realizations with system size larger than 8 3, sharp peaks are present in these physical quantities. These sharp peaks result from flipping a large domain, and furthermore, the critical domains are strongly correlated to the domains found at the zero temperature transition. This observation suggests a strong version of the zero temperature fixed point picture. The MKRG approximation is employed to test the correlation between the critical states and the ground states in much larger systems. It is found that the fraction of correlated realizations drops as system size grows, while there are still significant number of correlated realizations even for systems as large as 10243. Whether substantial correlations will remain in the thermodynamic limit is unclear from our present data.
Date01 January 2006
CreatorsWu, Yong
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
Detected LanguageEnglish
SourceDoctoral Dissertations Available from Proquest

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