Proof of Jensen's Lemma: the Contact Set of a Semiconvex Function at a Strict Maximum has Positive Measure
lemmalem:jensen-maximum-2026aFor small perturbation bounds the contact set is compact and lies in the half ball, so the map sending a maximiser to its perturbing vector is single-valued and Lipschitz with constant twice the semiconvexity constant, and it maps the contact set onto the closed ball of perturbations; the Lipschitz image bound for Lebesgue measure then forces the contact set to have measure at least a fixed multiple of that of a ball.
Step 0: the contact-set lemma applies. The ball is contained in , and by the continuity estimate for semiconvex functions, applied with the subset of the open convex set , the restriction of to satisfies hypothesis (H1) of Maximisers of Linearly Perturbed Continuous Functions on a Closed Ball: Existence, Localisation, and Compactness of the Contact Set; hypothesis (H2) there is exactly the strict maximum assumption made here. Consequently Maximisers of Linearly Perturbed Continuous Functions on a Closed Ball: Existence, Localisation, and Compactness of the Contact Set applies to , and the restriction of to , and the sets and of that lemma are the ones written here.
Step 1: the choice of . Apply the localisation of maximisers with to obtain a positive real such that whenever . Let be the smaller of and ; since and , this is a positive real number. Fix from now on a real with where claims 1 to 3 are concerned.
Proof of claim 1. By the existence of maximisers the set is nonempty, and by the compactness of the contact set it is compact in ; hence by claim 3 of Balls Have Positive Lebesgue Measure and Bounded Sets Have Finite Lebesgue Measure. Since , step 1 gives , and by claim 1 of Elementary Properties of the Closed Ball in a Metric Space.
Proof of claim 2. For put
which is nonempty by the definition of .
(a) has exactly one element. Let . By the triangle inequality and claim 5 of Elementary Properties of the Euclidean Norm on ,
By claim 1 above, . Applying the Lipschitz estimate between maximisers with the convex set , the constant , the ball , the vectors and the points , we obtain . Write for the unique element of ; this defines a map .
(b) is Lipschitz with constant . Let and put , . As in (a), , and by claim 1 both and lie in ; each of maximises the corresponding perturbation over . The Lipschitz estimate between maximisers therefore gives
so is Lipschitz with constant for the Euclidean distances.
(c) . Every satisfies , that is, , so . Conversely let with . By the existence of maximisers there is ; then and , so . Hence .
(d) The measure estimate. The set is nonempty and compact by claim 1, and is Lipschitz with constant by (b). Applying The Lebesgue Measure of a Lipschitz Image of a Compact Subset of and using (c),
which is the displayed inequality of claim 2.
(e) Positivity. Since , claim 1 of Elementary Properties of the Closed Ball in a Metric Space gives , and by claim 1 of Balls Have Positive Lebesgue Measure and Bounded Sets Have Finite Lebesgue Measure the open ball is a Borel set of positive -measure. The closed ball is compact, hence Borel, by claim 2 of A Closed Euclidean Ball is Convex and Compact and claim 3 of Balls Have Positive Lebesgue Measure and Bounded Sets Have Finite Lebesgue Measure, so monotonicity (claim 2 of Basic Properties of a Measure) gives . Combining with (d), ; as and make positive, it follows that .
Proof of claim 3. Let with , and suppose that every lay in , that is, . Then monotonicity (claim 2 of Basic Properties of a Measure) would give , contradicting claim 2. Hence some satisfies .
Proof of claim 4. Let with . By the localisation of maximisers there is a positive real with for every real with . Let be the smaller of and ; it is positive and satisfies , and every real with satisfies , so .
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Prerequisites
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