Around the Brunn-Minkowski inequality

Similar documents
Murat Akman. The Brunn-Minkowski Inequality and a Minkowski Problem for Nonlinear Capacities. March 10

From the Brunn-Minkowski inequality to a class of Poincaré type inequalities

Shape optimization problems for variational functionals under geometric constraints

A glimpse into convex geometry. A glimpse into convex geometry

Infinitesimal form of Brunn-Minkowski type inequalities

Brunn-Minkowski inequality for the 1-Riesz capacity and level set convexity for the 1/2-Laplacian

PROD. TYPE: COM ARTICLE IN PRESS. Andrea Colesanti. Received 4 August 2003; accepted 8 June 2004 Communicated by Michael Hopkins

Brunn-Minkowski inequalities for two functionals involving the p-laplace operator

Convex Geometry. Otto-von-Guericke Universität Magdeburg. Applications of the Brascamp-Lieb and Barthe inequalities. Exercise 12.

Brunn-Minkowski inequality for the 1-Riesz capacity and level set convexity for the 1/2-Laplacian

ON A LINEAR REFINEMENT OF THE PRÉKOPA-LEINDLER INEQUALITY

NAKAJIMA S PROBLEM: CONVEX BODIES OF CONSTANT WIDTH AND CONSTANT BRIGHTNESS

1 Lesson 1: Brunn Minkowski Inequality

Steiner s formula and large deviations theory

Asymptotic Geometric Analysis, Fall 2006

Citation for the original published paper (version of record):

Log-concave distributions: definitions, properties, and consequences

Probabilistic Methods in Asymptotic Geometric Analysis.

A Brunn Minkowski inequality for the Hessian eigenvalue in three-dimensional convex domain

Brunn Minkowski Theory in Minkowski space-times. François Fillastre Université de Cergy Pontoise France

Moment Measures. Bo az Klartag. Tel Aviv University. Talk at the asymptotic geometric analysis seminar. Tel Aviv, May 2013

Affine surface area and convex bodies of elliptic type

BORELL S GENERALIZED PRÉKOPA-LEINDLER INEQUALITY: A SIMPLE PROOF. Arnaud Marsiglietti. IMA Preprint Series #2461. (December 2015)

Theory of Probability Fall 2008

Mixed volumes and mixed integrals

Entropy Power Inequalities: Results and Speculation

BRUNN-MINKOWSKI INEQUALITIES IN PRODUCT METRIC MEASURE SPACES

STABILITY RESULTS FOR THE BRUNN-MINKOWSKI INEQUALITY

Integro-differential equations: Regularity theory and Pohozaev identities

Asymptotic Convex Geometry Lecture Notes

%HZ1EXLRS. CONVEXITY OF L p -INTERSECTION BODIES

Bulletin of the. Iranian Mathematical Society

On the Brunn-Minkowski and Aleksandrov-Fenchel Inequalities. Master s Thesis in Engineering Mathematics SIMON LARSON

Relative Isoperimetric Inequality Outside Convex Bodies

Complemented Brunn Minkowski Inequalities and Isoperimetry for Homogeneous and Non-Homogeneous Measures

Quermassintegrals of quasi-concave functions and generalized Prékopa Leindler inequalities

ALEKSANDROV-TYPE ESTIMATES FOR A PARABOLIC MONGE-AMPÈRE EQUATION

1 An Elementary Introduction to Monotone Transportation

A Brunn Minkowski theory for coconvex sets of finite volume

Assignment 1: From the Definition of Convexity to Helley Theorem

ON THE REGULARITY OF SAMPLE PATHS OF SUB-ELLIPTIC DIFFUSIONS ON MANIFOLDS

THE RELATIVE ISOPERIMETRIC INEQUALITY OUTSIDE A CONVEX DOMAIN IN R n. 1. Introduction

Unbounded Convex Semialgebraic Sets as Spectrahedral Shadows

CONVEX SOLUTIONS OF ELLIPTIC DIFFERENTIAL EQUATIONS IN CLASSICAL DIFFERENTIAL GEOMETRY. 1. Introduction

Isoperimetric Inequalities and the Alexandrov Theorem

Lebesgue Integration on R n

DAR S CONJECTURE AND THE LOG-BRUNN-MINKOSKI INEQUALITY

Banach Journal of Mathematical Analysis ISSN: (electronic)

Convexity of level sets for solutions to nonlinear elliptic problems in convex rings. Paola Cuoghi and Paolo Salani

Minkowski Valuations on Convex Functions

Algorithmic Convex Geometry

Convex Optimization Notes

Lecture 7: Positive Semidefinite Matrices

High-dimensional distributions with convexity properties

Chapter 1. Optimality Conditions: Unconstrained Optimization. 1.1 Differentiable Problems

LECTURE 5: SURFACES IN PROJECTIVE SPACE. 1. Projective space

HESSIAN VALUATIONS ANDREA COLESANTI, MONIKA LUDWIG & FABIAN MUSSNIG

Some problems involving fractional order operators

Boot camp - Problem set

Convex Functions and Optimization

Math 341: Convex Geometry. Xi Chen

Chapter 1 Preliminaries

Static Problem Set 2 Solutions

Spectral Gap and Concentration for Some Spherically Symmetric Probability Measures

THE BRUNN-MINKOWSKI INEQUALITY AND A MINKOWSKI PROBLEM FOR NONLINEAR CAPACITY

Locally convex spaces, the hyperplane separation theorem, and the Krein-Milman theorem

Homework 11. Solutions

Division of the Humanities and Social Sciences. Supergradients. KC Border Fall 2001 v ::15.45

THE LOGARITHMIC MINKOWSKI PROBLEM

SWFR ENG 4TE3 (6TE3) COMP SCI 4TE3 (6TE3) Continuous Optimization Algorithm. Convex Optimization. Computing and Software McMaster University

SHARP BOUNDARY TRACE INEQUALITIES. 1. Introduction

Inequality Constraints

Nonparametric estimation under Shape Restrictions

Approximately Gaussian marginals and the hyperplane conjecture

Appendix B Convex analysis

Overview of normed linear spaces

CONCENTRATION INEQUALITIES AND GEOMETRY OF CONVEX BODIES

Lebesgue s Differentiation Theorem via Maximal Functions

A NEW ELLIPSOID ASSOCIATED WITH CONVEX BODIES

Remarks on Extremization Problems Related To Young s Inequality

The general programming problem is the nonlinear programming problem where a given function is maximized subject to a set of inequality constraints.

Elliptic PDEs of 2nd Order, Gilbarg and Trudinger

Nonparametric estimation of log-concave densities

Chapter 2 Convex Analysis

REFINEMENTS OF THE BRUNN-MINKOWSKI INEQUALITY

Probability and Measure

Best approximations in normed vector spaces

The Volume of the Intersection of a Convex Body with its Translates

Introduction to Hausdorff Measure and Dimension

EQUIVALENCE OF TOPOLOGIES AND BOREL FIELDS FOR COUNTABLY-HILBERT SPACES

On a weighted total variation minimization problem

AN INTRODUCTION TO EXTREME POINTS AND APPLICATIONS IN ISOMETRIC BANACH SPACE THEORY

Quantitative stability for the Brunn-Minkowski inequality

1 Introduction. A SHARP STABILITY RESULT FOR THE RELATIVE ISOPERIMETRIC INEQUALITY INSIDE CONVEX CONES A. Figalli and E. Indrei. 1.

On the Brunn-Minkowski inequality for general measures with applications to new isoperimetric-type inequalities

Mathematics II, course

SYMMETRY RESULTS FOR PERTURBED PROBLEMS AND RELATED QUESTIONS. Massimo Grosi Filomena Pacella S. L. Yadava. 1. Introduction

Appendix A: Separation theorems in IR n

The L p -Minkowski Problem and the Minkowski Problem in Centroaffine Geometry

Summary of Real Analysis by Royden

Transcription:

Around the Brunn-Minkowski inequality Andrea Colesanti Technische Universität Berlin - Institut für Mathematik January 28, 2015

Summary

Summary The Brunn-Minkowski inequality

Summary The Brunn-Minkowski inequality The isoperimetric inequality

Summary The Brunn-Minkowski inequality The isoperimetric inequality Infinitesimal form of Brunn-Minkowski inequality

Summary The Brunn-Minkowski inequality The isoperimetric inequality Infinitesimal form of Brunn-Minkowski inequality Inequalities of Brunn-Minkowski type

The Brunn-Minkowski inequality

The Brunn-Minkowski inequality Thm. A, B R n, compact; λ [0, 1]; then V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n. (BM) V n = volume (Lebesgue measure); (1 λ)a + λb = {(1 λ)a + λb : a A, b B}.

The Brunn-Minkowski inequality Thm. A, B R n, compact; λ [0, 1]; then V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n. (BM) V n = volume (Lebesgue measure); (1 λ)a + λb = {(1 λ)a + λb : a A, b B}. Equivalently: The functional Vn 1/n is concave in the class of compact sets of R n, equipped with the vector addition. An excellent survey (much better than this talk): R. Gardner, The Brunn-Minkowski inequality, Bull. A.M.S., 2002.

(BM) privileges convex sets

(BM) privileges convex sets In the inequality V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n, equality holds iff A is convex and B is a homothetic copy of A (up to subsets of volume zero).

(BM) privileges convex sets In the inequality V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n, equality holds iff A is convex and B is a homothetic copy of A (up to subsets of volume zero). Why? If you plug A = B in (BM) in general you don t get an equality, because

(BM) privileges convex sets In the inequality V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n, equality holds iff A is convex and B is a homothetic copy of A (up to subsets of volume zero). Why? If you plug A = B in (BM) in general you don t get an equality, because (1 λ)a + λa A

(BM) privileges convex sets In the inequality V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n, equality holds iff A is convex and B is a homothetic copy of A (up to subsets of volume zero). Why? If you plug A = B in (BM) in general you don t get an equality, because (1 λ)a + λa A ((1 λ)a + λa A).

(BM) privileges convex sets In the inequality V n ((1 λ)a + λb) 1/n (1 λ)v n (A) 1/n + λv n (B) 1/n, equality holds iff A is convex and B is a homothetic copy of A (up to subsets of volume zero). Why? If you plug A = B in (BM) in general you don t get an equality, because But if A is convex (1 λ)a + λa A ((1 λ)a + λa A). (1 λ)a + λa = A λ [0, 1].

Many equivalent forms

Many equivalent forms Classic V n ((1 λ)a+λb) 1/n (1 λ)v n (A) 1/n +λv n (B) 1/n. (BM)

Many equivalent forms Classic V n ((1 λ)a+λb) 1/n (1 λ)v n (A) 1/n +λv n (B) 1/n. (BM) Elegant V n (A + B) 1/n V n (A) 1/n + V n (B) 1/n. (BM )

Many equivalent forms Classic V n ((1 λ)a+λb) 1/n (1 λ)v n (A) 1/n +λv n (B) 1/n. (BM) Elegant V n (A + B) 1/n V n (A) 1/n + V n (B) 1/n. (BM ) Multiplicative V n ((1 λ)a + λb) V n (A) 1 λ V n (B) λ. (BM 0 )

Many equivalent forms Classic V n ((1 λ)a+λb) 1/n (1 λ)v n (A) 1/n +λv n (B) 1/n. (BM) Elegant V n (A + B) 1/n V n (A) 1/n + V n (B) 1/n. (BM ) Multiplicative V n ((1 λ)a + λb) V n (A) 1 λ V n (B) λ. (BM 0 ) Minimal V n ((1 λ)a + λb) min{v n (A), V n (B)}. (BM )

A general fact about homogeneous functional Let F be a real-valued functional defined on a convex cone C; α-homogeneous: F(λx) = λ α F(x), x C, λ > 0 (α > 0); non-negative.

A general fact about homogeneous functional Let F be a real-valued functional defined on a convex cone C; α-homogeneous: F(λx) = λ α F(x), x C, λ > 0 (α > 0); non-negative. F 1/α concave {F t} is convex t. The last condition (quasi-concavity) is equivalent to F((1 λ)a + λb) min{f(a), F(B)} A, B C, λ [0, 1].

A general fact about homogeneous functional Let F be a real-valued functional defined on a convex cone C; α-homogeneous: F(λx) = λ α F(x), x C, λ > 0 (α > 0); non-negative. F 1/α concave {F t} is convex t. The last condition (quasi-concavity) is equivalent to F((1 λ)a + λb) min{f(a), F(B)} A, B C, λ [0, 1]. In our case: C = {compact sets}, F = V n, α = n.

An elementary proof of (BM) - I

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality).

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions,

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions, and let λ [0, 1].

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions, and let λ [0, 1]. Assume that f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n.

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions, and let λ [0, 1]. Assume that f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. Then ( ) 1 λ ( ) λ fdz gdx hdy. R n R n R n

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions, and let λ [0, 1]. Assume that Then Proof. f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. ( ) 1 λ ( ) λ fdz gdx hdy. R n R n R n Prove the 1-dimensional case (using just the so-called layer cake, or Cavalieri s, principle);

An elementary proof of (BM) - I Lemma (Prékopa-Leindler inequality). Let f, g, h : R n R + be measurable functions, and let λ [0, 1]. Assume that Then Proof. f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. ( ) 1 λ ( ) λ fdz gdx hdy. R n R n R n Prove the 1-dimensional case (using just the so-called layer cake, or Cavalieri s, principle); the n-dimensional case follows by induction and Fubini s theorem.

A proof of (BM) - II

A proof of (BM) - II Given A, B R n and λ [0, 1], let

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb,

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B.

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B. Then: f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n.

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B. Then: f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. By Prékopa-Leindler inequality V n ((1 λ)a + λb) = R n fdz

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B. Then: f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. By Prékopa-Leindler inequality V n ((1 λ)a + λb) = fdz R ( n ) 1 λ ( gdx hdy R n R n ) λ

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B. Then: f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. By Prékopa-Leindler inequality V n ((1 λ)a + λb) = fdz R ( n ) 1 λ ( ) λ gdx R n hdy R n = V n (A) 1 λ V n (B) λ,

A proof of (BM) - II Given A, B R n and λ [0, 1], let f = characteristic function of (1 λ)a + λb, g = charact. function of A, h = charact. function of B. Then: f ((1 λ)x + λy)) g(x) (1 λ) h(y) λ x, y R n. By Prékopa-Leindler inequality V n ((1 λ)a + λb) = fdz R ( n ) 1 λ ( ) λ gdx R n hdy R n = V n (A) 1 λ V n (B) λ, i.e. the multiplicative form of (BM).

The isoperimetric inequality

The isoperimetric inequality Thm. Among all subsets of R n with given perimeter, the ball having such perimeter maximizes the volume.

The isoperimetric inequality Thm. Among all subsets of R n with given perimeter, the ball having such perimeter maximizes the volume. Equivalently, V n (A) n 1 n c(n)h n 1 ( A) for every set A (with sufficiently smooth boundary), where c(n) is a constant and H n 1 is the (n 1)-dimensional Hausdorff measure. Equality is attained when A is a ball.

(BM) isoperimetric inequality Let A R n be a bounded domain with C 1 boundary. Then where H n 1 V n (A ɛ ) V n (A) ( A) = lim, ɛ 0 + ɛ A ɛ = {x R n : dist(x, A) ɛ}

(BM) isoperimetric inequality Let A R n be a bounded domain with C 1 boundary. Then H n 1 V n (A ɛ ) V n (A) ( A) = lim, ɛ 0 + ɛ where A ɛ = {x R n : dist(x, A) ɛ} = A + ɛb, and B = {x R n : x 1} = unit ball.

(BM) isoperimetric inequality Let A R n be a bounded domain with C 1 boundary. Then H n 1 V n (A ɛ ) V n (A) ( A) = lim, ɛ 0 + ɛ where A ɛ = {x R n : dist(x, A) ɛ} = A + ɛb, and Hence B = {x R n : x 1} = unit ball. H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ

Proof of the isoperimetric inequality

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n.

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n. V n (B) 1/n lim ɛ 0 + V n (A + ɛb) 1/n V n (A) 1/n ɛ

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n. V n (B) 1/n lim ɛ 0 + V n (A + ɛb) 1/n V n (A) 1/n ɛ = 1 n V n(a) 1 n n H n 1 ( A).

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n. V n (B) 1/n lim ɛ 0 + V n (A + ɛb) 1/n V n (A) 1/n ɛ = 1 n V n(a) 1 n n H n 1 ( A). V n (A) n 1 n 1 nv n (B) 1/n Hn 1 ( A)

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n. V n (B) 1/n lim ɛ 0 + V n (A + ɛb) 1/n V n (A) 1/n ɛ = 1 n V n(a) 1 n n H n 1 ( A). V n (A) n 1 n 1 nv n (B) 1/n Hn 1 ( A) = c(n)h n 1 ( A).

Proof of the isoperimetric inequality H n 1 V n (A + ɛb) V n (A) ( A) = lim. ɛ 0 + ɛ By (BM), for every ɛ > 0 V n (A + ɛb) 1/n V n (A) 1/n + V n (ɛb) 1/n = V n (A) 1/n + ɛv n (B) 1/n. V n (B) 1/n lim ɛ 0 + V n (A + ɛb) 1/n V n (A) 1/n ɛ = 1 n V n(a) 1 n n H n 1 ( A). V n (A) n 1 n 1 nv n (B) 1/n Hn 1 ( A) = c(n)h n 1 ( A). When A is a ball this becomes an equality.

The infinitesimal form of (BM)

The infinitesimal form of (BM) By the Brunn-Minkowski inequality Vn 1/n functional. is a concave

The infinitesimal form of (BM) By the Brunn-Minkowski inequality Vn 1/n is a concave functional. Hence the second variation (or second differential) of Vn 1/n (whatever that means) must be negative semidefinite: D 2 (V 1/n n ) 0.

The infinitesimal form of (BM) By the Brunn-Minkowski inequality Vn 1/n is a concave functional. Hence the second variation (or second differential) of Vn 1/n (whatever that means) must be negative semidefinite: D 2 (V 1/n n ) 0. If we restrict our attention to convex sets, this fact amounts to a class of functional inequalities of Poincaré type on the unit sphere;

The infinitesimal form of (BM) By the Brunn-Minkowski inequality Vn 1/n is a concave functional. Hence the second variation (or second differential) of Vn 1/n (whatever that means) must be negative semidefinite: D 2 (V 1/n n ) 0. If we restrict our attention to convex sets, this fact amounts to a class of functional inequalities of Poincaré type on the unit sphere; a prototype is φ 2 dh n 1 c(n) φ 2 dh n 1, S n 1 S n 1

The infinitesimal form of (BM) By the Brunn-Minkowski inequality Vn 1/n is a concave functional. Hence the second variation (or second differential) of Vn 1/n (whatever that means) must be negative semidefinite: D 2 (V 1/n n ) 0. If we restrict our attention to convex sets, this fact amounts to a class of functional inequalities of Poincaré type on the unit sphere; a prototype is φ 2 dh n 1 c(n) φ 2 dh n 1, S n 1 S n 1 φ C 1 (S n 1 ), verifying some zero-mean condition.

Convex bodies

Convex bodies From now on we will only consider a special type of compact sets: convex bodies.

Convex bodies From now on we will only consider a special type of compact sets: convex bodies. A convex body is a compact convex subset of R n. We set K n = {convex bodies in R n }.

Convex bodies From now on we will only consider a special type of compact sets: convex bodies. A convex body is a compact convex subset of R n. We set K n = {convex bodies in R n }. K n is closed under addition and dilations: given K, L K n and α, β 0, αk + βl K n.

Convex bodies From now on we will only consider a special type of compact sets: convex bodies. A convex body is a compact convex subset of R n. We set K n = {convex bodies in R n }. K n is closed under addition and dilations: given K, L K n and α, β 0, αk + βl K n. The Brunn-Minkowski inequality holds in particular in K n.

From sets to functions: the support function of a convex body

From sets to functions: the support function of a convex body The support function h K of a convex body K is defined by: h K : S n 1 R, h K (u) = sup{(u, v) v K}. h K (u) is the distance from the origin of the hyperplane supporting K, with outer unit normal u.

From sets to functions: the support function of a convex body The support function h K of a convex body K is defined by: h K : S n 1 R, h K (u) = sup{(u, v) v K}. h K (u) is the distance from the origin of the hyperplane supporting K, with outer unit normal u. The passage to support functions preserves the linear structure on K n : for every K, L K n α, β 0. h αk+βl = αh K + βh L.

Convex bodies of class C 2 + A convex body is said to be of class C 2 + if: K C 2, the Gauss curvature is strictly positive on K.

Convex bodies of class C 2 + A convex body is said to be of class C+ 2 if: K C 2, the Gauss curvature is strictly positive on K. In terms of the support function h of K:

Convex bodies of class C 2 + A convex body is said to be of class C+ 2 if: K C 2, the Gauss curvature is strictly positive on K. In terms of the support function h of K: h C 2 (S n 1 ),

Convex bodies of class C 2 + A convex body is said to be of class C+ 2 if: K C 2, the Gauss curvature is strictly positive on K. In terms of the support function h of K: h C 2 (S n 1 ), (h ij + hδ ij ) > 0 on S n 1 (h ij = second covariant derivatives of h on S n 1, δ ij = Kronecker s symbols).

Convex bodies of class C 2 + A convex body is said to be of class C+ 2 if: K C 2, the Gauss curvature is strictly positive on K. In terms of the support function h of K: h C 2 (S n 1 ), (h ij + hδ ij ) > 0 on S n 1 (h ij = second covariant derivatives of h on S n 1, δ ij = Kronecker s symbols). C := {h C 2 (S n 1 ) : (h ij + hδ ij ) > 0 on S n 1 }

Convex bodies of class C 2 + A convex body is said to be of class C+ 2 if: K C 2, the Gauss curvature is strictly positive on K. In terms of the support function h of K: h C 2 (S n 1 ), (h ij + hδ ij ) > 0 on S n 1 (h ij = second covariant derivatives of h on S n 1, δ ij = Kronecker s symbols). C := {h C 2 (S n 1 ) : (h ij + hδ ij ) > 0 on S n 1 } = {support functions of C 2 + convex bodies}.

A representation formula for the volume

A representation formula for the volume If K is of class C+ 2 and h is its support function, then V n (K) = 1 h det(h ij + hδ ij ) dh n 1. n S n 1

A representation formula for the volume If K is of class C+ 2 and h is its support function, then V n (K) = 1 h det(h ij + hδ ij ) dh n 1. n S n 1 Now we define a functional F : C R + as F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1 = V n (K) 1/n. n S n 1

A representation formula for the volume If K is of class C+ 2 and h is its support function, then V n (K) = 1 h det(h ij + hδ ij ) dh n 1. n S n 1 Now we define a functional F : C R + as F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1 = V n (K) 1/n. n S n 1 By the Brunn-Minkowski inequality, F is concave in C.

The second variation of F.

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ):

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): (D 2 F(h)φ, φ)

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): (D 2 F(h)φ, φ) = d 2 ds 2 F(h + sφ) s=0.

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): The condition (D 2 F(h)φ, φ) = d 2 ds 2 F(h + sφ) s=0. (D 2 F(h)φ, φ) 0

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): The condition (D 2 F(h)φ, φ) = d 2 ds 2 F(h + sφ) s=0. (D 2 F(h)φ, φ) 0 turns out to be equivalent to a weighted Poincaré inequality: trace(c ij )φ 2 dh n 1 c ij φ i φ j dh n 1, S n 1 S n 1 i,j

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): The condition (D 2 F(h)φ, φ) = d 2 ds 2 F(h + sφ) s=0. (D 2 F(h)φ, φ) 0 turns out to be equivalent to a weighted Poincaré inequality: trace(c ij )φ 2 dh n 1 c ij φ i φ j dh n 1, S n 1 S n 1 i,j (c ij ) > 0, (c ij ) depends on h.

The second variation of F. F(h) = [ ] 1 1/n h det(h ij + hδ ij ) dh n 1. n S n 1 For every fixed h, D 2 F(h) is a bilinear symmetric form acting on test functions φ C (S n 1 ): The condition (D 2 F(h)φ, φ) = d 2 ds 2 F(h + sφ) s=0. (D 2 F(h)φ, φ) 0 turns out to be equivalent to a weighted Poincaré inequality: trace(c ij )φ 2 dh n 1 c ij φ i φ j dh n 1, S n 1 S n 1 i,j (c ij ) > 0, (c ij ) depends on h. for every φ verifying a zero-mean condition..

A special case

A special case If we choose h 1 (the support function of the unit ball of R n ), we obtain (c ij ) =identity matrix, and we recover φ 2 dh n 1 1 φ 2 dh n 1, S n 1 n 1 S n 1 for every φ C 1 (S n 1 ) s.t. S n 1 φdh n 1 = 0.

A special case If we choose h 1 (the support function of the unit ball of R n ), we obtain (c ij ) =identity matrix, and we recover φ 2 dh n 1 1 φ 2 dh n 1, S n 1 n 1 S n 1 for every φ C 1 (S n 1 ) s.t. S n 1 φdh n 1 = 0. This is the standard Poincaré inequality (with best constant) on S n 1.

A special case If we choose h 1 (the support function of the unit ball of R n ), we obtain (c ij ) =identity matrix, and we recover φ 2 dh n 1 1 φ 2 dh n 1, S n 1 n 1 S n 1 for every φ C 1 (S n 1 ) s.t. S n 1 φdh n 1 = 0. This is the standard Poincaré inequality (with best constant) on S n 1. (C. 2008; Saorín-Gomez, C. 2010).

Inequalities of Brunn-Minkowski type

Inequalities of Brunn-Minkowski type Let G : K n R be s.t.: G(K) 0 for every K K n ; G is α-homogeneous (α 0): G(tK) = t α G(K), t 0, K K n.

Inequalities of Brunn-Minkowski type Let G : K n R be s.t.: G(K) 0 for every K K n ; G is α-homogeneous (α 0): G(tK) = t α G(K), t 0, K K n. We say that G verifies a Brunn-Minkowski type inequality if for every K, L K n, and for every λ [0, 1]: G((1 λ)k + λl) 1/α (1 λ)g(k) 1/α + λg(l) 1/α.

Examples

Examples The following functionals verify a Brunn-Minkowski type inequality.

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume.

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume. Perimeter.

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume. Perimeter. Other functionals in convex geometry (intrinsic volumes, mixed volumes, 2-dim. affine surface area...).

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume. Perimeter. Other functionals in convex geometry (intrinsic volumes, mixed volumes, 2-dim. affine surface area...). Principal frequency (= first Dirichlet eigenvalue of the Laplace operator) (Brascamp and Lieb; Borell).

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume. Perimeter. Other functionals in convex geometry (intrinsic volumes, mixed volumes, 2-dim. affine surface area...). Principal frequency (= first Dirichlet eigenvalue of the Laplace operator) (Brascamp and Lieb; Borell). Electrostatic capacity (Borell; Caffarelli, Jerison and Lieb).

Examples The following functionals verify a Brunn-Minkowski type inequality. Volume. Perimeter. Other functionals in convex geometry (intrinsic volumes, mixed volumes, 2-dim. affine surface area...). Principal frequency (= first Dirichlet eigenvalue of the Laplace operator) (Brascamp and Lieb; Borell). Electrostatic capacity (Borell; Caffarelli, Jerison and Lieb). Many other examples coming from the world of calculus of variations and elliptic PDE s (torsional rigidity, p-capacity,...).

Other examples

Other examples Some well-known functional not obeying a Brunn-Minkowski inequality.

Other examples Some well-known functional not obeying a Brunn-Minkowski inequality. The diameter.

Other examples Some well-known functional not obeying a Brunn-Minkowski inequality. The diameter. The affine surface area in dimension n 3.

Other examples Some well-known functional not obeying a Brunn-Minkowski inequality. The diameter. The affine surface area in dimension n 3. The first Neumann eigenvalue of the Laplace operator.

Hints

Hints Is there some general phenomenon behind these examples?

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say.

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say. Maybe simpler: understand the relation between the Brunn-Minkowski inequality and other basic features, such as:

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say. Maybe simpler: understand the relation between the Brunn-Minkowski inequality and other basic features, such as: monotonicity;

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say. Maybe simpler: understand the relation between the Brunn-Minkowski inequality and other basic features, such as: monotonicity; continuity;

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say. Maybe simpler: understand the relation between the Brunn-Minkowski inequality and other basic features, such as: monotonicity; continuity; rigid motion invariance;

Hints Is there some general phenomenon behind these examples? Difficult (pointless?) to say. Maybe simpler: understand the relation between the Brunn-Minkowski inequality and other basic features, such as: monotonicity; continuity; rigid motion invariance; additivity (or valuation property): G(K L) = G(K) + G(L) G(K L), for every K, L K n such that K L K n.

A result in this direction

A result in this direction Thm. (Hug, Saorín-Gomez, C., 2012). Let G : K n R be: additive, rigid motion invariant, continuous, (n 1)-homogeneous, and assume that it verifies a Brunn-Minkowski type inequality.

A result in this direction Thm. (Hug, Saorín-Gomez, C., 2012). Let G : K n R be: additive, rigid motion invariant, continuous, (n 1)-homogeneous, and assume that it verifies a Brunn-Minkowski type inequality. Then G is a mixed volume, and in particular is monotone.