2012
DOI: 10.1007/s10955-012-0450-9
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Lattice Permutations and Poisson-Dirichlet Distribution of Cycle Lengths

Abstract: We study random spatial permutations on Z 3 where each jump x → π(x) is penalized by a factor e −T x−π(x) 2 . The system is known to exhibit a phase transition for low enough T where macroscopic cycles appear. We observe that the lengths of such cycles are distributed according to Poisson-Dirichlet. This can be explained heuristically using a stochastic coagulation-fragmentation process for long cycles, which is supported by numerical data.

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Cited by 27 publications
(49 citation statements)
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“…Models on the complete graph are easier to analyse than the corresponding models on a lattice Z d , d ≥ 3; but the heuristics for the latter models is remarkably similar to the one for the former models; see [11,32]. The ideas sketched here are confirmed by the results of numerical simulations of various loop soups, including lattice permutations [12], loop O(N)-models [21], and the random interchange model [4].…”
Section: Random Loop Representationssupporting
confidence: 55%
“…Models on the complete graph are easier to analyse than the corresponding models on a lattice Z d , d ≥ 3; but the heuristics for the latter models is remarkably similar to the one for the former models; see [11,32]. The ideas sketched here are confirmed by the results of numerical simulations of various loop soups, including lattice permutations [12], loop O(N)-models [21], and the random interchange model [4].…”
Section: Random Loop Representationssupporting
confidence: 55%
“…The outcome is shown in Fig. 12: we (15) and A = 1.58 (20). Again we obtain good overlap of data from different system sizes.…”
mentioning
confidence: 59%
“…This behavior is actually fairly general and concerns many systems where one-dimensional objects have macroscopic size. The distribution PD(1) has been confirmed numerically in a model of lattice permutations [24] and analytically in the related annealed model [25]. More general PD(θ) have been confirmed numerically in O(n) loop models [14].…”
Section: A Macroscopic Loops and Random Partitionsmentioning
confidence: 57%