Hysteresis, Avalanches, and Noise: Numerical Methods

Details Hysteresis, Avalanches, and Noise: Numerical Methods Hysteresis, Avalanches, and Noise: Numerical Methods

1998-09-07

arxiv.org/abs/cond-mat/9809122v2

Physics

Condensed Matter

Disordered Systems and Neural Networks

Scientific paper

In studying the avalanches and noise in a model of hysteresis loops we have developed two relatively straightforward algorithms which have allowed us to study large systems efficiently. Our model is the random-field Ising model at zero temperature, with deterministic albeit random dynamics. The first algorithm, implemented using sorted lists, scales in computer time as O(N log N), and asymptotically uses N (sizeof(double)+ sizeof(int)) bits of memory. The second algorithm, which never generates the random fields, scales in time as O(N \log N) and asymptotically needs storage of only one bit per spin, about 96 times less memory than the first algorithm. We present results for system sizes of up to a billion spins, which can be run on a workstation with 128MB of RAM in a few hours. We also show that important physical questions were resolved only with the largest of these simulations.

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