June 2022 Large deviation for uniform graphs with given degrees
Souvik Dhara, Subhabrata Sen
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Ann. Appl. Probab. 32(3): 2327-2353 (June 2022). DOI: 10.1214/21-AAP1745

Abstract

Consider the random graph sampled uniformly from the set of all simple graphs with a given degree sequence. Under mild conditions on the degrees, we establish a large deviation principle (LDP) for these random graphs, viewed as elements of the graphon space. As a corollary of our result, we obtain LDPs for functionals continuous with respect to the cut metric, and obtain an asymptotic enumeration formula for graphs with given degrees, subject to an additional constraint on the value of a continuous functional. Our assumptions on the degrees are identical to those of Chatterjee, Diaconis and Sly (Ann. Appl. Probab. 21 (2011) 1400–1435), who derived the almost sure graphon limit for these random graphs.

Citation

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Souvik Dhara. Subhabrata Sen. "Large deviation for uniform graphs with given degrees." Ann. Appl. Probab. 32 (3) 2327 - 2353, June 2022. https://doi.org/10.1214/21-AAP1745

Information

Received: 1 January 2020; Revised: 1 April 2021; Published: June 2022
First available in Project Euclid: 29 May 2022

MathSciNet: MR4430015
zbMATH: 07581754
Digital Object Identifier: 10.1214/21-AAP1745

Subjects:
Primary: 05C80 , 60C05

Keywords: degree contraints , graphons , large deviation , uniform random graphs

Rights: Copyright © 2022 Institute of Mathematical Statistics

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Vol.32 • No. 3 • June 2022
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