Joint large deviation principle for some empirical measures of the d-regular random graphs
U Ibrahim, A Lotsi… - Journal of Discrete …, 2021 - Taylor & Francis
U Ibrahim, A Lotsi, K Doku-Amponsah
Journal of Discrete Mathematical Sciences and Cryptography, 2021•Taylor & FrancisIn this paper, we define ad–regular random model by perfect matching of vertices or paring
of vertices. For each vertex, we assign aq–state spin. From this d–regular graph model, we
define the empirical co-operate measure, which enumerates the number of co-operation
between a given couple of spins, and empirical spin measure, which enumerates the
number of sites having a given spin on the d–regular random graph model. For these
empirical measures, we obtain large deviation principle (LDP) in the weak topology.
of vertices. For each vertex, we assign aq–state spin. From this d–regular graph model, we
define the empirical co-operate measure, which enumerates the number of co-operation
between a given couple of spins, and empirical spin measure, which enumerates the
number of sites having a given spin on the d–regular random graph model. For these
empirical measures, we obtain large deviation principle (LDP) in the weak topology.
Abstract
In this paper, we define a d–regular random model by perfect matching of vertices or paring of vertices. For each vertex, we assign a q–state spin. From this d–regular graph model, we define the empirical co-operate measure, which enumerates the number of co-operation between a given couple of spins, and empirical spin measure, which enumerates the number of sites having a given spin on the d–regular random graph model. For these empirical measures, we obtain large deviation principle(LDP) in the weak topology.
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