(2.3) — Fenchel–Young inequality f(x) + g(y) ≥ (x | y) for f ∈ Γ₀(H) and its dual g
ProvedMoreauProx.Decomposition.fenchel_youngLet be a real Hilbert space, let (proper, convex, lower semicontinuous, with values in ), and let be its dual function, . Then for all ,
This is the inequality underlying the notion of conjugate points: and are called conjugate with respect to and exactly when equality holds.
Formalization Note The sum is taken in EReal. Because never takes the value and is not identically , neither nor is , so the convention never enters.
import Mathlib import Definitions.Def_MoreauProx_Decomposition_ConvexDuality
namespace MoreauProx.Decomposition
open scoped InnerProductSpace
/-- Moreau 1965, (2.3), p. 277: for `f ∈ Γ₀(H)` and its dual `g`,
`f(x) + g(y) ≥ (x | y)` for all `x, y`. -/
theorem fenchel_young {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H]
[CompleteSpace H] (f : H → EReal) (hf : GammaZero f) (x y : H) :
((⟪x, y⟫_ℝ : ℝ) : EReal) ≤ f x + conj f y := by sorry
end MoreauProx.Decomposition
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What the Lean code literally says, in plain math · claude-opus-5-5
Let be a real Hilbert space, meaning a complete real inner product space. Let belong to . That is:
- never takes the value ;
- is finite at some point;
- the epigraph is convex;
- is lower semicontinuous.
Let be its conjugate, computed in the extended reals, where a point with contributes .
The theorem asserts that for all ,
where the sum is taken in the extended reals, with the convention .
Degenerate cases. If , the inequality says . This is automatically true unless , and that cannot happen here because is finite somewhere. When , the statement reads with real.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.