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Register a new userSequential disruption of the shortest path in critical percolation
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Oliver Gschwend ETH Zurich
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We investigate the effect of sequentiallydisrupting the shortest path of percolation clusters at criticality by comparing it with the shortest alternative path. We measure the difference in length and the enclosed area between the two paths. The sequential approach allows to study spatial correlations. We find the lengths of the segments of successively constant differences in length to be uncorrelated. Simultaneously, we study the distance between red bonds. We find the probability distributions for the enclosed areas A, the differences in length $Delta l$, and the lengths between the redbonds $l_r$ to follow power law distributions. Using maximum likelihood estimation and extrapolation we find the exponents $beta$ = 1.38 $pm$ 0.03 for $Delta l$, $alpha$ = 1.186 $pm$ 0.008 for A and $delta$ = 1.64 $pm$ 0.025 for thedistribution of $l_r$.
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We investigate the behaviour of the shortest path on a directed two-dimensional square lattice for bond percolation at the critical probability $p_c$ . We observe that flipping an edge lying on the shortest path has a non-local effect in the form of power-law distributions for both the differences in shortest path lengths and for the minimal enclosed areas. Using maximum likelihood estimation and extrapolation we find the exponents $alpha = 1.36 pm 0.01$ for the path length differences and $beta = 1.186 pm 0.001$ for the enclosed areas.
Restricted-valence random sequential adsorption~(RSA) is studied in its pure and disorder
We analyze the geometry of scaling limits of near-critical 2D percolation, i.e., for $p=p_c+lambdadelta^{1/ u}$, with $ u=4/3$, as the lattice spacing $delta to 0$. Our proposed framework extends previous analyses for $p=p_c$, based on $SLE_6$. It combines the continuum nonsimple loop process describing the full scaling limit at criticality with a Poissonian process for marking double (touching) points of that (critical) loop process. The double points are exactly the continuum limits of macroscopically pivotal lattice sites and the marked ones are those that actually change state as $lambda$ varies. This structure is rich enough to yield a one-parameter family of near-critical loop processes and their associated connectivity probabilities as well as related processes describing, e.g., the scaling limit of 2D minimal spanning trees.
The random sequential adsorption (RSA) model is a classical model in Statistical Physics for adsorption on two-dimensional surfaces. Objects are deposited sequentially at random and adsorb irreversibly on the landing site, provided that they do not overlap any previously adsorbed object. The kinetics of adsorption ceases when no more objects can be adsorbed (jamming state). Here, we investigate the role of post-relaxation on the jamming state and percolation properties of RSA of dimers on a two-dimensional lattice. We consider that, if the deposited dimer partially overlaps with a previously adsorbed one, a sequence of dimer displacements may occur to accommodate the new dimer. The introduction of this simple relaxation dynamics leads to a more dense jamming state than the one obtained with RSA without relaxation. We also consider the anisotropic case, where one dimer orientation is favored over the other, finding a non-monotonic dependence of the jamming coverage on the strength of anisotropy. We find that the density of adsorbed dimers at which percolation occurs is reduced with relaxation, but the value depends on the strength of anisotropy.
Long linear polymers in strongly disordered media are well described by self-avoiding walks (SAWs) on percolation clusters. The length-distribution of these SAWs encompasses to distinct averages, viz. the averages over cluster- and SAW-conformations. For the latter average, there are two basic options, one being static and one being kinetic. It is well known for static averaging that if the disorder of the underlying medium is weak, differences to the ordered case appear merely in non-universal quantities. Using dynamical field theory, we show that the same holds true for kinetic averaging. For strong disorder, i.e., the medium being close to the percolation point, we employ a field theory for the nonlinear random resistor network in conjunction with a real-world interpretation of Feynman diagrams, and we calculate the scaling exponents for the shortest, the longest and the mean or average SAW to 2-loop order. In addition, we calculate to 2-loop order the entire family of multifractal exponents that governs the moments of the the statistical weights of the elementary constituents (bonds or sites of the underlying fractal cluster) contributing to the SAWs. Our RG analysis reveals that kinetic averaging leads to renormalizability whereas static averaging does not, and hence, we argue that the latter does not lead to a well-defined scaling limit. We discuss the possible implications of this finding for experiments and numerical simulations which have produced wide-spread results for the exponent of the average SAW. To corroborate our results, we also study the well-known Meir-Harris model for SAWs on percolation clusters. We demonstrate that this model leads back to 2-loop order to the renormalizable real world formulation with kinetic averaging if the replica limit is consistently performed at the first possible instant of the calculation.
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