Alphabeta Math
DefinitionDefinition: Literature-sourcedProof: Not applicablePipeline-generatedjudge pass (gpt-6.1-sol)
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Convex and strictly convex functionals on a convex subset of a real vector space

Definition

Let X be a real vector space and K⊆X. The set K is convex if λu+(1−λ)v∈K for all u,v∈K and λ∈[0,1]. Fix a nonempty convex K and an extended-real functional I:K→(−∞,+∞] (Proper, coercive and weakly lower semicontinuous extended-real functionals), with the sums and positive-weight products of The extended real line R‾=R∪{−∞,+∞}, its order, and the arithmetic that is left undefined. For convex combinations only, additionally define 0⋅(+∞)=0; this is a local convention, since that product is left undefined in the general extended-real arithmetic. Then I is convex if I(λu+(1−λ)v)≤λI(u)+(1−λ)I(v),u,v∈K, λ∈[0,1], and strictly convex if the inequality is strict whenever u≠v, I(u),I(v)<+∞ and λ∈(0,1). A convex functional has convex sublevel sets: for every t∈R the set {u∈K:I(u)≤t} is convex. Only real coefficients are used: on a complex vector space these notions are read on the underlying real structure.

Remarks

  • Sublevel sets. Let I be convex and let t∈R. If u,v∈K satisfy I(u)≤t and I(v)≤t, then I(u),I(v)<+∞, and for λ∈[0,1] convexity and the extended-real conventions give I(λu+(1−λ)v)≤λI(u)+(1−λ)I(v)≤max⁡{I(u),I(v)}≤t; hence {u∈K:I(u)≤t} is convex. This is the property used when a sublevel set is intersected with a weakly closed admissible set.

  • Endpoint coefficients. At λ=0 and λ=1 the defining inequality reads I(v)≤I(v) and I(u)≤I(u), using 0⋅(+∞)=0 for the extended value +∞; the strict form is therefore imposed only for 0<λ<1, as stated.

  • Finite competitors. For 0<λ<1, if either I(u) or I(v) is +∞, the right-hand side of the convexity inequality is +∞, so it carries no information at such a pair; the strict form is correspondingly restricted to pairs in the effective domain dom⁡I (Proper, coercive and weakly lower semicontinuous extended-real functionals).

Depends on

Used by

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Sources