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Superconcentration in surface growth
Author(s) -
Chatterjee Sourav
Publication year - 2023
Publication title -
random structures and algorithms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.314
H-Index - 69
eISSN - 1098-2418
pISSN - 1042-9832
DOI - 10.1002/rsa.21108
Subject(s) - percolation (cognitive psychology) , mathematical proof , mathematics , class (philosophy) , meaning (existential) , statistical physics , surface (topology) , combinatorics , physics , geometry , computer science , psychology , psychotherapist , biology , artificial intelligence , neuroscience
Height functions of growing random surfaces are often conjectured to be superconcentrated, meaning that their variances grow sublinearly in time. This article introduces a new concept—called subroughness —meaning that there exist two distinct points such that the expected squared difference between the heights at these points grows sublinearly in time. The main result of the paper is that superconcentration is equivalent to subroughness in a class of growing random surfaces. The result is applied to establish superconcentration in a variant of the restricted solid‐on‐solid (RSOS) model and in a variant of the ballistic deposition model, and give new proofs of superconcentration in directed last‐passage percolation and directed polymers.