Threshold for detecting high dimensional geometry in anisotropic random geometric graphs

Author:

Brennan Matthew1,Bresler Guy1,Huang Brice1

Affiliation:

1. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts USA

Abstract

AbstractIn the anisotropic random geometric graph model, vertices correspond to points drawn from a high‐dimensional Gaussian distribution and two vertices are connected if their distance is smaller than a specified threshold. We study when it is possible to hypothesis test between such a graph and an Erdős‐Rényi graph with the same edge probability. If is the number of vertices and is the vector of eigenvalues, Eldan and Mikulincer, Geo. Aspects Func. Analysis: Israel seminar, 2017 shows that detection is possible when and impossible when . We show detection is impossible when , closing this gap and affirmatively resolving the conjecture of Eldan and Mikulincer, Geo. Aspects Func. Analysis: Israel seminar, 2017.

Publisher

Wiley

Subject

Applied Mathematics,Computer Graphics and Computer-Aided Design,General Mathematics,Software

Reference17 articles.

1. M.Brennan G.Bresler andB.Huang.De Finetti‐style results for Wishart matrices: Combinatorial structure and phase transitions. arXiv preprint arXiv:2103.14011.2021.

2. Phase transitions for detecting latent geometry in random graphs

3. Testing for high-dimensional geometry in random graphs

4. Entropic CLT and phase transition in high‐dimensional Wishart matrices;Bubeck S.;Int. Math. Res. Not.,2018

5. Multivariate normal approximation using exchange‐able pairs;Chatterjee S.;Alea,2008

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1. On the Fourier Coefficients of High-Dimensional Random Geometric Graphs;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

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