Large deviations for subcomplex counts and Betti numbers in multiparameter simplicial complexes

Abstract

We consider the multiparameter random simplicial complex as a higher dimensional extension of the classical Erdős–Rényi graph. We investigate appearance of “unusual” topological structures in the complex from the point of view of large deviations. We first study upper tail large deviation probabilities for subcomplex counts, deriving the order of magnitude of such probabilities at the logarithmic scale precision. The obtained results are then applied to analyze large deviations for the number of simplices of the multiparameter simplicial complexes. Finally, these results are also used to deduce large deviation estimates for Betti numbers of the complex in the critical dimension.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 16, 2023
Source ID
10.1002/rsa.21146

Entities

People

  • Gennady Samorodnitsky
  • Takashi Owada

Organizations

  • Air Force Office of Scientific Research
  • Cornell University
  • National Science Foundation
  • Purdue University

Tags

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Operations Research
  • Regression Analysis.