Prékopa–Leindler inequality
ProvedConvexOptimization.prekopa_leindlerThe Prékopa–Leindler inequality — the functional form of the Brunn–Minkowski inequality.
Let and let be measurable functions satisfying the pointwise hypothesis
Then the same multiplicative inequality holds for the integrals:
Applied to indicator functions of convex bodies and , with the indicator of , the hypothesis holds by convexity and the conclusion becomes — the multiplicative Brunn–Minkowski inequality. Remarkably, the hypothesis only constrains along the single interpolation point of each pair , yet controls its whole integral, and there is no convexity or regularity assumption on any of the three functions.
This is the one genuinely analytic input of the mission: Prékopa's theorem on marginals follows from it by applying the inequality to the sections of a log-concave function.
Formalization Note The functions are ℝ≥0∞-valued and the integrals are lower Lebesgue integrals ∫⁻, which removes every integrability side condition and makes the statement unconditional; the integrable real-valued form follows by truncation and monotone convergence. Source: Gardner, The Brunn–Minkowski inequality, BAMS 39 (2002), Theorem 4.2, verified verbatim; cited from B&V §3.5.2.
import Mathlib open scoped RealInnerProductSpace ENNReal open MeasureTheory
theorem ConvexOptimization.prekopa_leindler {n : ℕ} (l : ℝ) (hl0 : 0 < l) (hl1 : l < 1)
(f g h : EuclideanSpace ℝ (Fin n) → ℝ≥0∞)
(hf : Measurable f) (hg : Measurable g) (hh : Measurable h)
(hple : ∀ x y : EuclideanSpace ℝ (Fin n),
f x ^ (1 - l) * g y ^ l ≤ h ((1 - l) • x + l • y)) :
(∫⁻ x, f x) ^ (1 - l) * (∫⁻ x, g x) ^ l ≤ ∫⁻ x, h x := by
sorry
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What the Lean code literally says, in plain math · claude-fable-5
Theorem statement. Fix , a real with (two strict hypotheses), and three measurable functions taking values in the extended nonnegative reals . Hypothesis: for all pairs (pointwise everywhere, not almost-everywhere), . Conclusion: , where is the lower (Lebesgue) integral with respect to the volume (Lebesgue) measure on Euclidean -space — always defined, with values in . Powers are the extended-nonnegative-real power with real exponent; since both exponents and lie strictly in , the conventions in play are and for , and multiplication in uses — e.g. if the left side is even when , and the conclusion then holds automatically. No integrability or finiteness is assumed anywhere (the measurability hypotheses are stated even though the lower integral is defined for any function). Degenerate case : the space is a single point whose volume measure has total mass , and the statement reduces to the hypothesis at that point.
Confirmed by the mission captain (proposal self-audit).