Numerical study shows convergence of iterative transformations to SLE curves in fractal systems, indicating strong statistical properties.
Stochastic Loewner evolution (SLE) is a differential equation driven by a onedimensional Brownian motion (BM), whose solution gives a stochastic process of conformal transformation on the upper half complex-plane H. As an evolutionary boundary of image of the transformation, a random curve (the SLE curve) is generated, which is starting from the origin and running in H toward the infinity as time is going. The SLE curves provides a variety of statistical ensembles of important fractal curves, if we change the diffusion constant of the driving BM. In the present paper, we consider the Schwarz-Christoffel transformation (SCT), which is a conformal map from H to the region H with a slit starting from the origin. We prepare a binomial system of SCTs, one of which generates a slit in H with an angle απ from the positive direction of the real axis, and the other of which with an angle (1 −α)π. One parameter κ > 0 is introduced to control the value of α and the length of slit. Driven by a one-dimensional random walk, which is a binomial stochastic process, a random iteration of SCTs is performed. By interpolating tips of slits by straight lines, we have a random path in H, which we call an Iterative SCT (ISCT) path. It is well-known that, as the number of steps N of random walk goes infinity, each path of random walk divided by √N converges to a Brownian curve. Then we expect that the ISCT paths divided by √N (the rescaled ISCT paths) converge to the SLE curves in N → ∞. Our numerical study implies that, for sufficiently large N , the rescaled ISCT paths will have the same statistical properties as the SLE curves have, supporting our expectation.
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Sato et al. (2011) studied this question.
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