Comparison of metric spectral gaps
Abstract
Let A=(aij)∈ Mn() be an n by n symmetric stochastic matrix. For p∈ [1,∞) and a metric space (X,dX), let γ(A,dXp) be the infimum over those γ∈ (0,∞] for which every x1,...,xn∈ X satisfy 1n2 Σi=1nΣj=1n dX(xi,xj)p γnΣi=1nΣj=1n aij dX(xi,xj)p. Thus γ(A,dXp) measures the magnitude of the nonlinear spectral gap of the matrix A with respect to the kernel dXp:X× X [0,∞). We study pairs of metric spaces (X,dX) and (Y,dY) for which there exists :(0,∞) (0,∞) such that γ(A,dXp) (γ(A,dYp)) for every symmetric stochastic A∈ Mn() with γ(A,dYp)<∞. 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 n∈ and p∈ (2,∞) then for every f1,...,fn∈ Lp there exist x1,...,xn∈ L2 such that equationeq:p factor ∀\, i,j∈ \1,...,n\, \|xi-xj\|2 p\|fi-fj\|p, equation and Σi=1nΣj=1n \|xi-xj\|22=Σi=1nΣj=1n \|fi-fj\|p2. This statement is impossible for p∈ [1,2), and the asymptotic dependence on p in eq:p factor is sharp. We also obtain the best known lower bound on the Lp distortion of Ramanujan graphs, improving over the work of Matousek. Links to Bourgain--Milman--Wolfson type and a conjectural nonlinear Maurey--Pisier theorem are studied.
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