TY - JOUR

T1 - Non-Backtracking Loop Soups and Statistical Mechanics on Spin Networks

AU - Camia, Federico

AU - Lis, Marcin

PY - 2017/2/1

Y1 - 2017/2/1

N2 - We introduce and study a Markov field on the edges of a graph G in dimension d≥ 2 whose configurations are spin networks. The field arises naturally as the edge-occupation field of a Poissonian model (a soup) of non-backtracking loops and walks characterized by a spatial Markov property such that, conditionally on the value of the edge-occupation field on a boundary set that splits the graph into two parts, the distributions of the loops and arcs contained in the two parts are independent of each other. The field has a Gibbs distribution with a Hamiltonian given by a sum of terms which involve only edges incident on the same vertex. Its free energy density and other quantities can be computed exactly, and their critical behavior analyzed, in any dimension.

AB - We introduce and study a Markov field on the edges of a graph G in dimension d≥ 2 whose configurations are spin networks. The field arises naturally as the edge-occupation field of a Poissonian model (a soup) of non-backtracking loops and walks characterized by a spatial Markov property such that, conditionally on the value of the edge-occupation field on a boundary set that splits the graph into two parts, the distributions of the loops and arcs contained in the two parts are independent of each other. The field has a Gibbs distribution with a Hamiltonian given by a sum of terms which involve only edges incident on the same vertex. Its free energy density and other quantities can be computed exactly, and their critical behavior analyzed, in any dimension.

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U2 - 10.1007/s00023-016-0524-3

DO - 10.1007/s00023-016-0524-3

M3 - Article

AN - SCOPUS:84991786896

SN - 1424-0637

VL - 18

SP - 403

EP - 433

JO - Annales Henri Poincare

JF - Annales Henri Poincare

IS - 2

ER -