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Complexity.Foundations.BooleanAnalysis.Hypercontractivity.Derivative

L^p norms of derivatives of Boolean functions #

The derivative of a Boolean function read as signs takes the values 0 and ±1, so its L^p norm is the p-th root of the influence (BitString.lpNorm_derivative_signVal) O'Donnell, Section 9.6. This is how the Kahn–Kalai–Linial theorem feeds influences into hypercontractivity.

Main results #

References #

theorem Cslib.BitString.lpNorm_derivative_signVal {ι : Type u_1} [Fintype ι] [DecidableEq ι] (f : (ι → Bool) → Bool) (i : ι) {p : ℝ} (hp : p ≠ 0) :
lpNorm p (derivative i fun (x : ι → Bool) => signVal (f x)) = (influence i fun (x : ι → Bool) => signVal (f x)) ^ p⁻¹

The L^p norm of the derivative of a Boolean function, read as signs, is the p-th root of the influence.