Abstract
Let be an by symmetric stochastic matrix. For and a metric space , let be the infimum over those for which every satisfy Thus measures the magnitude of the {\em nonlinear spectral gap} of the matrix with respect to the kernel . We study pairs of metric spaces and for which there exists such that for every symmetric stochastic with . When is linear a complete geometric characterization is obtained. Our estimates on nonlinear spectral gaps yield new embeddability results as well as new nonembeddability results. For example, it is shown that if and then for every there exist such that {equation}\label{eq:p factor} \forall\, i,j\in \{1,...,n\},\quad \|x_i-x_j\|_2\lesssim p\|f_i-f_j\|_p, {equation} and This statement is impossible for , and the asymptotic dependence on in \eqref{eq:p factor} is sharp. We also obtain the best known lower bound on the distortion of Ramanujan graphs, improving over the work of Matoušek. Links to Bourgain--Milman--Wolfson type and a conjectural nonlinear Maurey--Pisier theorem are studied.
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