Real Convexity On The Effective Domain
ProvedFunctionalInequalities.Probability.real_convexOn_effective_domain_readablefunctional-inequalitieskls-conjecturekls-modularkls-readablelog-concave
This statement extracts ordinary real convexity from an extended-real convex epigraph.
Let be a real inner-product normed additive group and let . Assume:
- for every .
- The real epigraph
is convex.
Then the function is ConvexOn on the effective domain
This is a technical bridge between extended-real convex potentials and ordinary real convex-analysis results.
Original Lean declaration header
Within namespace FunctionalInequalities.Probability. Shown in its original module context. Proof omitted.
lemma real_convexOn_effective_domain {φ : E → EReal} (h0 : ∀ x, 0 ≤ φ x)
(hφ : Convex ℝ {p : E × ℝ | φ p.1 ≤ (p.2 : EReal)}) :
ConvexOn ℝ {x | φ x ≠ ⊤} (fun x => (φ x).toReal)
Module navigation
Module: Probability/ConvexSupport.
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Source excerpt, lines 541–543 · Frozen source 408915f.
Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Probability_ConvexSupport
variable {E : Type*}
variable [NormedAddCommGroup E] [InnerProductSpace ℝ E]
Formal statement
lemma FunctionalInequalities.Probability.real_convexOn_effective_domain_readable {φ : E → EReal} (h0 : ∀ x, 0 ≤ φ x)
(hφ : Convex ℝ {p : E × ℝ | φ p.1 ≤ (p.2 : EReal)}) :
ConvexOn ℝ {x | φ x ≠ ⊤} (fun x => (φ x).toReal) := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Probability/ConvexSupport.lean#L539-L559 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Probability.ConvexSupport`, declaration `FunctionalInequalities.Probability.real_convexOn_effective_domain`; the repository is private at upload time).