Abstract

The winding angle probability distribution of a planar self-avoiding walk has been known exactly since a long time: it has a gaussian shape with a variance growing as <θ2>∼ln⁡L<θ^2>\sim \ln L. For the three-dimensional case of a walk winding around a bar, the same scaling is suggested, based on a first-order epsilon-expansion. We tested this three-dimensional case by means of Monte Carlo simulations up to length L≈25 000L\approx25\,000 and using exact enumeration data for sizes L≤20L\le20. We find that the variance of the winding angle scales as <θ2>∼(ln⁡L)2α<θ^2>\sim (\ln L)^{2α}, with α=0.75(1)α=0.75(1). The ratio γ=<θ4>/<θ2>2=3.74(5)γ= <θ^4>/<θ^2>^2=3.74(5) is incompatible with the gaussian value γ=3γ=3, but consistent with the observation that the tail of the probability distribution function p(θ)p(θ) is found to decrease slower than a gaussian function. These findings are at odds with the existing first-order εε-expansion results.

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