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Quantitative Bishop–Phelps support functional construction

Statement

Assume the Axiom of Dependent Choice (DC) and the relative Hahn–Banach principle HB. Let C be a nonempty closed bounded convex subset of a real Banach space X. For every f∈X∗ and every ε>0 there are v∈C and g∈X∗ such that

∥g−f∥≤εandg(c)≤g(v)(c∈C).

In fact, the construction below gives the strict bound ∥g−f∥<ε.

Facts & Assumptions

Given: DC, HB, X,C,f and ε as in the statement.

[F1]

A closed subset of a complete metric space is complete, without a choice axiom (Closed subspaces of complete metric spaces are complete; the converse under countable choice, claim 2, Banach space).

[F2]

DC produces a sequence along an entire relation from a specified initial state (The axiom of dependent choice: a relation in which every element is related to something admits an N-indexed chain).

[F4]

Under HB, a real linear functional dominated by a sublinear functional on a subspace has a dominated real-linear extension (Dominated extension conditional on the relative principle, The real dominated-extension principle as an additional hypothesis over ZF).

[F5]

The dual norm is the supremum of the absolute values on the closed unit ball (The dual space X^* of a normed space and its dual norm).

Proof

technique · maximizing variational construction followed by a support-cone Hahn–Banach argument
1.1givenF1construct

Choose a real number η with 0<η<ε. The restriction F=f∣C is continuous and bounded above because C is bounded. By [F1], C with its norm metric is complete. Fix one x0∈C, possible because C is nonempty, and for x∈C define S(x)={y∈C:F(y)≥F(x)+η∥y−x∥}. Each S(x) is nonempty because it contains x, and it is closed because F(y)−F(x)−η∥y−x∥ is continuous in y.

2.1step 1.1algebra

If y∈S(x) and z∈S(y), then F(z)≥F(y)+η∥z−y∥≥F(x)+η(∥y−x∥+∥z−y∥)≥F(x)+η∥z−x∥. Thus z∈S(x) and S(y)⊆S(x). Since F is bounded above and S(x) is nonempty, its supremum is a real number. For every n and every x∈C, the defining approximation property of the supremum supplies y∈S(x) with F(y)>sup⁡z∈S(x)F(z)−2−n.

3.1step 2.1F2choose

Let a state be a nonempty finite sequence (x0,…,xn) in C which starts at the fixed x0 and, at each earlier index k<n, has xk+1∈S(xk) and F(xk+1)>sup⁡z∈S(xk)F(z)−2−k. Relate each state to every valid one-term extension. Step 2.1 proves that this relation is entire, so one application of DC gives a compatible infinite sequence (xn) with both displayed properties for every n.

4.1step 1.1step 3.1F3algebra

The ascent condition gives η∥xn+1−xn∥≤F(xn+1)−F(xn). Consequently the partial sums of ∑n∥xn+1−xn∥ are nondecreasing and bounded above by (sup⁡CF−F(x0))/η. By [F3] the series converges, hence its tails tend to zero and (xn) is Cauchy. Completeness gives a limit v∈C.

5.1step 1.1step 2.1step 3.1step 4.1algebra

Transitivity in step 2.1 makes every tail point xk, k≥n, belong to S(xn); closedness gives v∈S(xn) for every n. If z∈S(v), then transitivity also puts z in every S(xn), and the approximate-supremum condition gives F(z)<F(xn+1)+2−n. Letting n→∞ and using continuity yields F(z)≤F(v). But z∈S(v) also gives F(z)≥F(v)+η∥z−v∥, so z=v. Therefore F(c)<F(v)+η∥c−v∥(c∈C, c≠v), and the corresponding non-strict inequality holds for every c∈C.

6.1step 5.1givenalgebra

Put D={t(c−v):t≥0, c∈C}. Because C−v is convex and contains zero, D is a convex cone: for t,s≥0 the sum t(c−v)+s(c′−v) is zero if t+s=0, and otherwise equals (t+s)(tt+sc+st+sc′−v). Step 5.1 and real linearity give f(d)≤η∥d∥(d∈D). This includes d=0.

7.1step 6.1F3algebra

For x∈X define p(x)=inf⁡d∈D(η∥x+d∥−f(d)). The set being infimized is nonempty because 0∈D. Step 6.1 and the reverse triangle inequality give every one of its terms at least −η∥x∥, while d=0 gives a term equal to η∥x∥. Thus [F3] makes p(x) a finite real and −η∥x∥≤p(x)≤η∥x∥.(1) Both bounds are uniform in the choice of d.

8.1step 6.1step 7.1algebra

The cone identities imply p(tx)=tp(x) for t>0, and (1) gives p(0)=0. If d1,d2∈D, then d1+d2∈D and η∥x+y+d1+d2∥−f(d1+d2)≤η∥x+d1∥−f(d1)+η∥y+d2∥−f(d2). Taking infima first over d1,d2 and then over D proves p(x+y)≤p(x)+p(y). Hence p is sublinear.

9.1step 7.1step 8.1F4F5

Apply [F4] to the zero functional on {0}, dominated by p, to obtain a real-linear h:X→R with h(x)≤p(x). Applying this at x and −x and using (1) gives ∣h(x)∣≤η∥x∥, so h∈X∗ and ∥h∥≤η by [F5]. For d∈D, the candidate d in the infimum gives p(−d)≤−f(d), whence −h(d)=h(−d)≤p(−d)≤−f(d) and h(d)≥f(d). Thus the extension dominates f on the support cone.

10.1step 6.1step 9.1given∎

Set g=f−h. Then g∈X∗ and ∥g−f∥=∥h∥≤η<ε. For every c∈C, the vector c−v lies in D, so step 9.1 gives g(c)−g(v)=f(c−v)−h(c−v)≤0. Thus g attains its supremum on C at v. The proof permits a singleton C, f=0, X={0} and the closed-boundary cases; DC is used only in step 3.1 and HB only in step 9.1.

Source notes

Loewen–Wang Theorem 2.2 proves a generalized variational principle and derives the Ekeland inequality in (2.14). Proposition 5.1(i) applies that principle to a coercive function, and Theorem 5.2 states Bishop–Phelps for nonempty closed bounded convex sets. The proof above derives exactly the maximizing inequality needed here and then spells out the support-cone/sublinear-gauge argument.

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