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arXiv · 1703.10557

Monte Carlo study of four-dimensional self-avoiding walks of up to one billion steps

Nathan Clisby
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Abstract

We study self-avoiding walks on the four-dimensional hypercubic lattice via Monte Carlo simulations of walks with up to one billion steps. We study the expected logarithmic corrections to scaling, and find convincing evidence in support the scaling form predicted by the renormalization group, with an estimate for the power of the logarithmic factor of 0.2516(14), which is consistent with the predicted value of 1/4. We also characterize the behaviour of the pivot algorithm for sampling four-dimensional self-avoiding walks, and conjecture that the probability of a pivot move being successful for an $N$-step walk is $O([ \log N ]^{-1/4})$.

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Nathan Clisby. 2017-03-30. Monte Carlo study of four-dimensional self-avoiding walks of up to one billion steps. https://doi.org/10.1007/s10955-018-2049-2

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