Local and Global Expansion in Random Geometric Graphs

PROCEEDINGS OF THE 55TH ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING, STOC 2023(2023)

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摘要
Consider a random geometric 2-dimensional simplicial complex X sampled as follows: first, sample n vectors u(1), ..., u(n) uniformly at random on Sd-1; then, for each triple i, j, k is an element of [n], add {i, j, k} and all of its subsets to X if and only if < u(i), u(j)> >= tau, < u(i), u(k)> >= tau and < u(j), u(k)> >= tau. We prove that for every epsilon > 0, there exists a choice of d = Theta(log n) and tau = tau (epsilon, d) so that with high probability, X is a high-dimensional expander of average degree n(epsilon) in which each 1-link has spectral gap bounded away from 1/2. To our knowledge, this is the first demonstration of a natural distribution over 2-dimensional expanders of arbitrarily small polynomial average degree and spectral link expansion better than 1/2. All previously known constructions are algebraic. This distribution also furnishes an example of simplicial complexes for which the trickle-down theorem is nearly tight. En route, we prove general bounds on the spectral expansion of random induced subgraphs of arbitrary vertex transitive graphs, which may be of independent interest. For example, one consequence is an almost-sharp bound on the second eigenvalue of random n-vertex geometric graphs on Sd-1, which was previously unknown for most n, d pairs. The full version of this paper can be found here.
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关键词
random graphs,random geometric graphs,high-dimensional expansion,trace method
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