A Sharp Small-Coefficient Variant of Khintchine's Inequality and the Sharp Theorem
Lei Yu
Source abstract
We prove a refined quadratic normal approximation for the first absolute moment of normalized weighted Rademacher sums with bounded maximal coefficients. For any weight vector satisfying and with sufficiently small , we establish the uniform error bound over all admissible weight configurations. Our proof combines zero-bias Stein's method and refined small-ball probability estimates to exploit symmetry cancellation and control the non-smooth residual of the absolute-value test function. An explicit extremal construction further verifies the optimality of this quadratic convergence rate. As an application, we establish an asymptotically sharp refinement of the Friedgut--Kalai--Naor (FKN) theorem for Boolean functions, also known as the sharp theorem, characterizing the level-1 Fourier energy for functions deviating far from dictatorships.
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