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Again this curve appears to become linear for large n

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Unformatted text preview: ks that did not achieve first passage in 105 steps were prematurely terminated. Figure 1 shows the computed values of f (n) for low values of n, while figure 2 shows a logarithmic plot highlighting the asymptotic behavior. For large n, the curve becomes almost linear, and by applying regression over the range 103 ≤ n ≤ 105 we find that f (n) ∝ n−1.50061 , which appears to match the theoretical result of f (n) ∝ n−3/2 for the Bernoulli walk. Figure 3 shows a plot of the survival probability S (n). Again, this curve appears to become linear for large n, and by applying regression we find S (n) ∝ n−0.500147 . Since we have a negative exponent, we see that S (n) → 0 as n → ∞, and thus our expected probability of return is 1. 2.2 Biased Cauchy walk The GSL code was also run for d = 1.0 and d = −1.0. The same number of trials were used for d = −1.0 as for the unbiased case, but 2 × 108 trials were used for d = 1.0, since many of these walks took a great number of steps to complete, thus creating a larger computational overhead. The computed f (n) for low values of n is shown in figure 1, while a log plot showing the asymptotic behavior is shown in figure 2. We see that for large n, the curves in this figure become almost linear. Applying linear regression over the range 103 ≤ n ≤ 105 shows that f (n) ∝ n−1.75027 for d = −1.0, and f (n) ∝ n−1.25015 for d = 1.0. The survival probability function S (n) for these cases is shown in figure 3. Again, these curves appear linear as n increases, and by applying linear regression we find that S (n) ∝ n−0.750051 for d = −1.0 and S (n) ∝ n−0.250044 for d = 1.0. Thus we expect that the probability of return is always 1, even for the case of positive drift, although some of these walks may take a very long time to return. Nevertheless, this fits with our intuition, since Cauchy walkers are capable of taking extrem...
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This note was uploaded on 01/23/2014 for the course MATH 18.366 taught by Professor Martinbazant during the Fall '06 term at MIT.

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