Minkowski valuations on convex functions

A classification of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {SL}}(n)$$\end{document}SL(n) contravariant Minkowski valuations on convex functions and a characterization of the projection body operator are established. The associated LYZ measure is characterized. In addition, a new \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {SL}}(n)$$\end{document}SL(n) covariant Minkowski valuation on convex functions is defined and characterized.

for y ∈ R n . The operator that associates to f the convex body f is easily seen to be SL(n) contravariant, where, in general, an operator Z defined on some space of functions f : R n → R and with values in the space of convex bodies, K n , in R n is SL(n) contravariant if Z( f • φ −1 ) = φ −t Z( f ) for every function f and φ ∈ SL(n). Here φ −t is the inverse of the transpose of φ. The projection body of f turned out to be critical in Zhang's affine Sobolev inequality [52], which is a sharp affine isoperimetric inequality essentially stronger than the L 1 Sobolev inequality. The convex body f is the classical projection body (see Sect. 1 for the definition) of another convex body f , which is the unit ball of the so-called optimal Sobolev norm of f and was introduced by Lutwak et al. [38]. The operator f → f is called the LYZ operator. It is SL(n) covariant, where, in general, an operator Z defined on some space of functions f : R n → R and with values in K n is SL(n) covariant if Z( f • φ −1 ) = φ Z( f ) for every function f and φ ∈ SL(n). See also [5,11,20,21,36,37,49].
In [33], a characterization of the operators f → f and f → f as SL(n) contravariant and SL(n) covariant valuations on W 1,1 (R n ) was established. Here, a function Z defined on a lattice (L, ∨, ∧) and taking values in an abelian semigroup is called a valuation if for all f, g ∈ L. A function Z defined on some subset S of L is called a valuation on S if (1) holds whenever f, g, f ∨ g, f ∧ g ∈ S. For S the space of convex bodies, K n , in R n with ∨ denoting union and ∧ intersection, the notion of valuation is classical and it was the key ingredient in Dehn's solution of Hilbert's Third Problem in 1901 (see [22,24]). Interesting new valuations keep arising (see, for example, [23] and see [1][2][3]8,16,17,19,27,35] for some recent results on valuations on convex bodies). More recently, valuations started to be studied on function spaces. When S is a space of real valued functions, then we take u ∨ v to be the pointwise maximum of u and v while u ∧ v is the pointwise minimum. For Sobolev spaces [31,33,39] and L p spaces [34,46,47] complete classifications for valuations intertwining the SL(n) were established. See also [4,7,10,13,14,25,32,41,50]. The aim of this paper is to establish a classification of SL(n) covariant and of SL(n) contravariant Minkowski valuations on convex functions. Let Conv(R n ) denote the space of convex functions u : R n → (−∞, +∞] which are proper, lower semicontinuous and coercive. Here a function is proper if it is not identically +∞ and it is coercive if where |x| is the Euclidean norm of x. The space Conv(R n ) is one of the standard spaces in convex analysis and here it is equipped with the topology associated to epi-convergence (see Sect. 1). An operator Z : S → K n is a Minkowski valuation if (1) holds with the addition on K n being Minkowski addition (that is, K + L = {x + y : x ∈ K , y ∈ L} for K , L ∈ K n ). The projection body operator is an SL(n) contravariant Minkowski valuation on W 1,1 (R n ) while the LYZ operator itself is not a Minkowski valuation (for n ≥ 3) but a Blaschke valuation (see Sect. 1 for the definition). In our first result, we establish a classification of SL(n) contravariant Minkowski valuations on Conv(R n ). To this end, we extend the definition of projection bodies to functions ζ • u with u ∈ Conv(R n ) and ζ ∈ D n−2 (R), where, for k ≥ 0, D k (R) = ζ ∈ C(R) : ζ ≥ 0, ζ is decreasing and We call an operator Z : Conv(R n ) → K n translation invariant if Z(u • τ −1 ) = Z(u) for every u ∈ Conv(R n ) and every translation τ : R n → R n . Let n ≥ 3.

Theorem 1 A function Z : Conv(R n ) → K n is a continuous, monotone, SL(n) contravariant and translation invariant Minkowski valuation if and only if there exists ζ ∈ D n−2 (R) such that
for every u ∈ Conv(R n ).
It is monotone if it is decreasing or increasing. While on the Sobolev space W 1,1 (R n ) a classification of SL(n) contravariant Minkowski valuations was established in [33], no classification of SL(n) covariant Minkowski valuations was obtained on W 1,1 (R n ). On Conv(R n ), we introduce new SL(n) covariant Minkowski valuations and establish a classification theorem. For u ∈ Conv(R n ) and ζ ∈ D 0 (R), define the level set body for y ∈ R n . Hence the level set body is a Minkowski average of the level sets. Let n ≥ 3.

is a continuous, monotone, SL(n) covariant and translation invariant Minkowski valuation if and only if there exists
for every u ∈ Conv(R n ).
Here, the difference body, D K , of a convex body K is defined as D K = K + (−K ), where h(−K , y) = h(K , −y) for y ∈ R n is the support function of the central reflection of K .
While on W 1,1 (R n ) a classification of SL(n) covariant Blaschke valuations was established in [33], on Conv(R n ) we obtain a more general classification of SL(n) contravariant measure-valued valuations. For K ∈ K n , let S(K , ·) denote its surface area measure (see Sect. 1) and let M e (S n−1 ) denote the space of finite even Borel measures on S n−1 . See Sect. 3 for the definition of monotonicity and SL(n) contravariance of measures. Let n ≥ 3.
for every u ∈ Conv(R n ).
Here, for ζ ∈ D n−2 (R) and u ∈ Conv(R n ), the measure S( ζ • u , ·) is the LYZ measure of ζ • u (see Sect. 3 for the definition). The above theorem extends results by Haberl and Parapatits [18] from convex bodies to convex functions.

Preliminaries
We collect some properties of convex bodies and convex functions. Basic references are the books by Schneider [44] and Rockafellar & Wets [42]. In addition, we recall definitions and classification results on Minkowski valuations and measure-valued valuations. We work in R n and denote the canonical basis vectors by e 1 , . . . , e n . For a k-dimensional linear subspace E ⊂ R n , we write proj E : R n → E for the orthogonal projection onto E and V k for the k-dimensional volume (or Lebesgue measure) on E. Let conv(A) be the convex hull of A ⊂ R n .
The space of convex bodies, K n , is equipped with the Hausdorff metric, which is given by The subspace of convex bodies in R n containing the origin is denoted by K n 0 . Let P n denote the space of convex polytopes in R n and P n 0 the space of convex polytopes containing the origin. All these spaces are equipped with the topology coming from the Hausdorff metric. For Every sublinear function is the support function of a unique convex body. Note that for the Minkowski sum of K , L ∈ K n , we have for y ∈ R n . A second important way to describe a convex body is through its surface area measure. For a Borel set ω ⊂ S n−1 and K ∈ K n , the surface area measure S(K , ω) is the (n − 1)dimensional Hausdorff measure of the set of all boundary points of K at which there exists a unit outer normal vector of ∂ K belonging to ω. The solution to the Minkowski problem states that a finite Borel measure Y on S n−1 is the surface area measure of an n-dimensional convex body K if and only if Y is not concentrated on a great subsphere and S n−1 u d Y(u) = 0. If such a measure Y is given, the convex body K is unique up to translation.
For n-dimensional convex bodies K and L in R n , the Blaschke sum is defined as the convex body with surface area measure S(K , ·) + S(L , ·) and with centroid at the origin. We call an operator Z : S → K n a Blaschke valuation if (1) holds with the addition on K n being Blaschke addition.

Convex and quasi-concave functions
We collect results on convex and quasi-concave functions including some results on valuations on convex functions. To every convex function u : R n → (−∞, +∞], there are assigned several convex sets. The domain, dom u = {x ∈ R n : u(x) < +∞}, of u is convex and the epigraph of u, is a convex subset of R n × R. For t ∈ (−∞, +∞], the sublevel set, is convex. For u ∈ Conv(R n ), it is also compact. Note that for u, v ∈ Conv(R n ) and t ∈ R, (5) where for u ∧ v ∈ Conv(R n ) all occurring sublevel sets are either empty or in K n . We equip Conv(R n ) with the topology associated to epi-convergence. Here a sequence u k : R n → (−∞, ∞] is epi-convergent to u : R n → (−∞, ∞] if for all x ∈ R n the following conditions hold: (i) For every sequence x k that converges to x, (ii) There exists a sequence x k that converges to x such that In this case we write u = epi-lim k→∞ u k and u k epi −→ u. We remark that epi-convergence is also called -convergence.
We require some results connecting epi-convergence and Hausdorff convergence of sublevel sets. We say that We also require the so-called cone property and uniform cone property for functions and sequences of functions from Conv(R n ).
for every x ∈ R n .
for every k ∈ N and x ∈ R n .
Next, we recall some results on valuations on Conv(R n ). For K ∈ K n 0 , we define the convex function K : R n → [0, ∞] by where pos stands for positive hull, that is, pos(L) = {t z ∈ R n+1 : z ∈ L , t ≥ 0} for L ⊂ R n+1 . This means that the epigraph of K is a cone with apex at the origin and { K ≤ t} = t K for all t ≥ 0. It is easy to see that K is an element of Conv(R n ) for K ∈ K n 0 . Also the (convex) indicator function I K for K ∈ K n belongs to Conv(R n ), where I K (x) = 0 for x ∈ K and I K (x) = +∞ for x / ∈ K .
for every P ∈ P k 0 and t ∈ R, then for every t ∈ R. In particular, ψ is k-times differentiable.
If there exist k ∈ N, c k ∈ R and ψ ∈ C k (R) with lim t→+∞ ψ(t) = 0 such that The next result, which is based on [33], shows that in order to classify valuations on Conv(R n ), it is enough to know the behavior of valuations on certain functions. Lemma 1.7 ([15], Lemma 17) Let A, + be a topological abelian semigroup with cancellation law and let Z 1 , Z 2 : Conv(R n ) → A, + be continuous, translation invariant valuations. If Z 1 ( P + t) = Z 2 ( P + t) for every P ∈ P n 0 and t ∈ R, then Z 1 ≡ Z 2 on Conv(R n ). Note that ζ • u ∈ QC(R n ) for ζ ∈ D k (R) with k ≥ 0 and u ∈ Conv(R n ). A natural extension of the volume in R n is the integral with respect to the Lebesgue measure, that is, See [9] for more information.
Following [9], for f ∈ QC(R n ) and a linear subspace E ⊂ R n , we define the projection where E ⊥ is the orthogonal complement of E. For t ≥ 0, we have max where proj E on the right side denotes the usual projection onto E in R n .

Valuations on convex bodies
We collect results on valuations on convex bodies and prove two auxiliary results.

SL(n) contravariant Minkowski valuations on convex bodies
For z ∈ S n−1 , let z ⊥ be the subspace orthogonal to z. The projection body, K , of the convex body K ∈ K n is defined by for z ∈ S n−1 . More generally, for a finite Borel measure Y on S n−1 , we define its cosine transform CY : R n → R by is easily seen to be sublinear and non-negative on R n , the cosine transform CY is the support function of a convex body that contains the origin.
The projection body has useful properties concerning SL(n) transforms and translations. For φ ∈ SL(n) and any translation τ on R n , we have for all K ∈ K n . Moreover, the operator K → K is continuous and the origin is an interior 10.9] for more information on projection bodies.
We require the following result where the support function of certain projection bodies is calculated for specific vectors. Let n ≥ 2. Lemma 2.1 For P = conv{0, 1 2 (e 1 +e 2 ), e 2 , . . . , e n } and Q = conv{0, e 2 , . . . , e n } we have Proof We use induction on the dimension and start with n = 2. In this case, P is a triangle in the plane with vertices 0, 1 2 (e 1 + e 2 ) and e 2 and Q is just the line segment connecting the origin with e 2 . It is easy to see that h( P, Assume now that the statement holds for (n − 1). All the projections to be considered are simplices that are the convex hull of e n and a base in e ⊥ n which is just the projection as in the (n − 1)-dimensional case. Therefore, the corresponding (n − 1)-dimensional volumes are just 1 n−1 multiplied with the (n − 2)-dimensional volumes from the previous case. To illustrate this, we will calculate h( P, e 1 + e 2 ) and remark that the other cases are similar. Note that proj (e 1 +e 2 ) ⊥ P = conv{e n , proj (e 1 +e 2 ) ⊥ P (n−1) }, where P (n−1) is the set in R n−1 from the (n − 1)-dimensional case embedded via the identification of R n−1 and e ⊥ n ⊂ R n . Using the induction hypothesis and |e 1 + e 2 | = √ 2, we obtain and therefore h( P, e 1 + e 2 ) = 1 (n−1)! .
The first classification of Minkowski valuations was established in [28], where the projection body operator was characterized as an SL(n) contravariant and translation invariant valuation. The following strengthened version of results from [29] is due to Haberl. Let n ≥ 3.

SL(n) covariant Minkowski valuations on convex bodies
The difference body D K of a convex body K ∈ K n is defined by for every z ∈ S n−1 . The moment vector m(K ) of K is defined by and is an element of R n . We require the following result where the support function of certain moment bodies and moment vectors is calculated for specific vectors. Let n ≥ 2.
Proof It is easy to see that h(T s , e 1 ) = s and h(−T s , e 1 ) = 0. Let φ s ∈ GL(n) be such that e 1 → s e 1 and e i → e i for i = 2, . . . , n. Then T s = φ s T n , where T n = conv{0, e 1 , . . . , e n } is the standard simplex. Hence, A first classification of SL(n) covariant Minkowski valuations was established in [29], where also the difference body operator was characterized. The following result is due to Haberl. Let n ≥ 3.

Theorem 2.4 ([16], Theorem 6) An operator
We also require the following result which holds for n ≥ 2.

Measure-valued valuations on convex bodies
Denote by M(S n−1 ) the space of finite Borel measures on S n−1 . Following [18], for p ∈ R, we say that a valuation Y : for every map φ ∈ SL(n), every P ∈ P n 0 and every continuous p-homogeneous function b : R n \{0} → R.
The following result is due to Haberl and Parapatits. Let n ≥ 3.
for every P ∈ P n 0 .
We denote by M e (S n−1 ) the set of finite even Borel measures on S n−1 , that is, measures We remark that if in the above theorem we also require the measure Y(P, ·) to be even and hence Y : for every P ∈ P n 0 .

Measure-valued valuations on Conv(R n )
In this section, we extend the LYZ measure, that is, the surface area measure of the image of the LYZ operator, to functions ζ • u, where ζ ∈ D n−2 (R) and u ∈ Conv(R n ). First, we recall the definition of the LYZ operator on W 1,1 (R n ) by Lutwak et al. [38]. Following [38], for f ∈ W 1,1 (R n ) not vanishing a.e., we define the even Borel measure S( f , ·) on S n−1 (using the Riesz-Markov-Kakutani representation theorem) by the condition that for every b : R n → R that is even, continuous and 1-homogeneous. Since the LYZ measure S( f , ·) is even and not concentrated on a great subsphere of S n−1 (see [38]), the solution to the Minkowski problem implies that there is a unique origin-symmetric convex body f whose surface area measure is S( f , ·).
, since the level sets of u are convex bodies and ζ is non-increasing with lim s→+∞ ζ(s) = 0. Hence we may rewrite (15) as Indeed, using that b is 1-homogeneous, the co-area formula (see, for example, [6, Sect. 2.12]), Sard's theorem, and the definition of surface area measure, we obtain where H n−1 denotes the (n − 1)-dimensional Hausdorff measure. Formula (16) provides the motivation of our extension of the LYZ operator, for which we require the following result.
Proof Fix ε > 0 and u ∈ Conv(R n ). Let ρ ε ∈ C ∞ (R) denote a standard mollifying kernel such that R n ρ ε dx = 1 and ρ ε (x) ≥ 0 for all x ∈ R n while the support of ρ ε is contained in a centered ball of radius ε. Write τ ε for the translation t → t + ε on R and define ζ ε (t) for t ∈ R by It is easy to see, that ζ ε is non-negative and smooth. Since t → +ε −ε ζ(t − ε − s)ρ ε (s) ds is decreasing, ζ ε is strictly decreasing. Since we get ζ ε (t) ≥ ζ(t) for every t ∈ R. Finally, ζ ε has finite (n − 2)-nd moment, since t → e −t has finite (n − 2)-nd moment and Hence, by convexity, the substitution t = ζ ε (s) and integration by parts, we obtain where v n is the volume of the n-dimensional unit ball.
The previous lemma admits a reverse statement. Let ζ ∈ C(R) be non-negative and decreasing, and assume that for every u ∈ Conv(R n ). Then necessarily i.e. ζ ∈ D n−2 (R). Indeed, the following identity holds Therefore, substituting u(x) = |x| in (17) we immediately get (18). Identity (19) can be easily proved by the co-area formula, when ζ is smooth, strictly decreasing and it vanishes in [t 0 , +∞), for some t 0 > 0. The general case is the obtained by a standard approximation argument.

Lemma 3.2 (and Definition)
For u ∈ Conv(R n ) and ζ ∈ D n−2 (R), an even finite Borel measure S( ζ • u , ·) on S n−1 is defined by the condition that for every even continuous function b : Proof For fixed u ∈ Conv(R n ) and ζ ∈ D n−2 (R), we have for every continuous function c : S n−1 → R. Hence Lemma 3.1 shows that defines a non-negative, bounded linear functional on the space of continuous functions on S n−1 . It follows from the Riesz-Markov-Kakutani representation theorem (see, for example, [43]), that there exists a unique Borel measure Y(ζ • u, ·) on S n−1 such that for every continuous function c : S n−1 → R. Moreover, the measure is finite. For u ∈ Conv(R n ) and ζ ∈ D n−2 (R), define the even Borel measure S( ζ • u , ·) on S n−1 as (20) holds and that S( ζ • u , ·) is the unique even measure with this property.
Next, fix an even continuous function b : By Lemma 1.1, the convex sets {u k ≤ t} converge in the Hausdorff metric to {u ≤ t} for every t = min x∈R n u(x), which implies the convergence of {ζ • u k ≥ t} → {ζ • u ≥ t} for every t = max x∈R n ζ(u(x)). Since the map K → S(K , ·) is weakly continuous on the space of convex bodies, we obtain for a.e. t ≥ 0. By Lemma 1.4, there exist a, d ∈ R with a > 0 such that u k (x) > v(x) = a|x| + d and therefore ζ • u k (x) < ζ • v(x) for x ∈ R n and k ∈ N. By convexity, for every k ∈ N and t > 0 and therefore By Lemma 3.1, the function t → S n−1 |b(z)| dS({ζ • v ≥ t}, z) is integrable. Hence, we can apply the dominated convergence theorem to conclude the proof.
For p ∈ R, we say that an operator Y : for every φ ∈ SL(n) and every continuous p-homogeneous function b : R n \{0} → R. This definition generalizes (13) from convex bodies to convex functions. We say that Y is decreasing on Conv . Similarly, we define increasing and we say that Y is monotone if it is decreasing or increasing.

Lemma 3.3 For
defines a weakly continuous, decreasing valuation on Conv(R n ) that is SL(n) contravariant of degree 1 and translation invariant.
Proof As K → S(K , ·) is translation invariant, it follows from the definition that also S( ζ • u , ·) is translation invariant. Lemma 3.2 gives weak continuity. If u, v ∈ Conv(R n ) are such that u ≥ v, then and consequently by convexity for all s ∈ R and t > 0. For φ ∈ SL(n), and hence by the properties of the surface area measure, we obtain for every continuous 1-homogeneous function b : R n \{0} → R. Finally, let u, v ∈ Conv(R n ) be such that u ∧ v ∈ Conv(R n ). Since ζ ∈ D n−2 (R) is decreasing, we obtain by (5) and the valuation property of the surface area measure that

Hence (21) defines a valuation.
We remark that Tuo Wang [48] extended the definition of the LYZ measure from W 1,1 (R n ) to the space of functions of bounded variation, BV(R n ), using a generalization of (15). The co-area formula (see [6,Theorem 3.40]) and Lemma 3.1 imply that ζ • u ∈ BV(R n ) for every ζ ∈ D n−2 (R) and u ∈ Conv(R n ). However, our approach is slightly different from [48]. The extended operators are the same for functions in Conv(R n ) that do not vanish a.e., but we assign a non-trivial measure also to functions whose support is (n − 1)-dimensional. In this case, the LYZ measure is concentrated on a great subsphere of S n−1 and hence we are able to associate to such a function an (n − 1)-dimensional convex body as a solution of the Minkowski problem but not an n-dimensional convex body. Since Blaschke sums are defined on n-dimensional convex bodies, we do not obtain a characterization of the LYZ operator as a Blaschke valuation on Conv(R n ). Note that Wang's definition allows to extend the LYZ operator to BV(R n ) with values in the space of n-dimensional convex bodies. However, Wang's extended operators f → S( f , ·) and f → f are only semi-valuations (see [50] for the definition) but no longer valuations on BV(R n ) and Wang [50] characterizes f → f as a Blaschke semi-valuation.

SL(n) contravariant Minkowski valuations on Conv(R n )
The operator that appears in Theorem 1 is defined. It is shown that it is a continuous, monotone, SL(n) contravariant and translation invariant Minkowski valuation.
By (11) and the definition of the cosine transform, the support function of the classical projection body is the cosine transform of the surface area measure. Since the measure S( ζ • u , ·), defined in Lemma 3.2, is finite for all ζ ∈ D n−2 (R) and u ∈ Conv(R n ), the cosine transform of S( ζ • u , ·) is finite and setting for z ∈ R n , defines a convex body ζ • u for ζ ∈ D n−2 (R) and u ∈ Conv(R n ). Here we use that the cosine transform of a measure gives a non-negative and sublinear function, which also shows that ζ • u contains the origin. By the definition of the cosine transform and the definition of the LYZ measure S( ζ • u , ·), we have for ζ ∈ D n−2 (R) and u ∈ Conv(R n ). Hence the projection body of ζ • u is a Minkowski average of the classical projection bodies of the sublevel sets of ζ • u.
Using the definition of the classical projection body (11), (10), the definition (9) of projections of quasi-concave functions and (8), we also obtain for z ∈ S n−1 Thus the definition of the projection body of the function ζ • u is analog to the definition of the projection body of a convex body (11). In [5], this connection was established for functions that are log-concave and in W 1,1 (R n ).

defines a continuous, decreasing, SL(n) contravariant and translation invariant Minkowski valuation on Conv(R n ).
Proof Let ζ ∈ D n−2 (R) and u ∈ Conv(R n ). By (12) and (22), we get for every φ ∈ SL(n) and z ∈ S n−1 , Similarly, we get for every translation τ on R n and z ∈ S n−1 , Thus for every φ ∈ SL(n) and every translation τ on R n , Thus the map defined in (24) is decreasing.

Classification of SL(n) contravariant Minkowski valuations
The aim of this section is to prove Theorem 1. Let n ≥ 3 and recall the definition of the cone function K from (6).
Now, for K , L ∈ K n 0 such that K ∪ L ∈ K n 0 , we have ( K + t) ∧ ( L + t) = K ∪L + t and ( K + t) ∨ ( L + t) = K ∩L + t. Using that Z is a valuation, we get which shows that Z t is a Minkowski valuation for every t ∈ R. Since Z is SL(n) contravariant, we obtain for φ ∈ SL(n) that Therefore, Z t is a continuous, SL(n) contravariant Minkowski valuation, where the continuity follows from Lemma 1.1. By Theorem 2.2, there exists a non-negative constant c t such that This defines a function ψ(t) = c t , which is continuous due to the continuity of Z. Similarly, using Z t (K ) = Z(I K + t), we obtain the function ζ .
For a continuous, SL(n) contravariant Minkowski valuation Z : Conv(R n ) → K n , we call the function ψ from Lemma 5.1 the cone growth function of Z. The function ζ is called its indicator growth function. By Lemma 1.7, we immediately get the following result.

Lemma 5.2 Every continuous, SL(n) contravariant and translation invariant Minkowski
valuation Z : Conv(R n ) → K n is uniquely determined by its cone growth function.
Next, we establish an important connection between cone and indicator growth functions.

Lemma 5.3 Let Z : Conv(R n ) → K n be a continuous, SL(n) contravariant and translation invariant Minkowski valuation. The growth functions satisfy
for every t ∈ R.
Proof We fix the (n −1)-dimensional linear subspace E = e ⊥ n of R n . Since E is of dimension (n − 1), we can identify the set of functions u ∈ Conv(R n ) such that dom u ⊆ E with Conv(R n−1 ) = Conv(E). We define Y : Conv(E) → R by Since Z is a Minkowski valuation, Y is a real valued valuation. Moreover, Y is continuous and translation invariant, since Z has these properties. By the definition of the growth functions we now get for every P ∈ P n−1 0 (E) = {P ∈ P n 0 : P ⊂ E} and t ∈ R. Hence, by Lemma 1.5, Next, we establish important properties of the cone growth function.
Proof In order to prove that ψ is decreasing, we have to show that ψ(s) ≥ ψ(t) for all s < t. Without loss of generality, we assume that s = 0, since for arbitrary s we can consider Z(u) = Z(u + s) with cone growth function ψ and ψ(0) = ψ(s). Hence, for the remainder of the proof we fix an arbitrary t > 0 and we have to show that ψ(t) ≤ ψ(0). Define the polytopes P and Q as in Lemma 2.1. Choose u t ∈ Conv(R n ) such that Thus, the valuation property of Z gives Using the translation invariance of Z and the definition of the cone growth function, this gives for the support functions Since Z(u t ) is a convex body, its support function is sublinear. This yields and Using Lemma 2.1, we obtain In order to show (25), let t in the construction above go to +∞. It is easy to see, that in this case u t is epi-convergent to P . Since ψ is decreasing and non-negative, lim t→+∞ ψ(t) = ψ ∞ exists. Taking limits in (26) therefore yields Evaluating at e 2 now gives ψ ∞ = 0.
By Lemma 1.7, we obtain the following result as an immediate corollary from the last result. We call a Minkowski valuation on Conv(R n ) trivial if Z(u) = {0} for u ∈ Conv(R n ).

Lemma 5.5 Every continuous, increasing, SL(n) contravariant and translation invariant
Minkowski valuation on Conv(R n ) is trivial. Lemma 5.3 shows that the indicator growth function ζ of a continuous, SL(n) contravariant and translation invariant Minkowski valuation Z determines its cone growth function ψ up to a polynomial of degree less than n − 1. By Lemma 5.4, lim t→∞ ψ(t) = 0 and hence the polynomial is also determined by ζ . Thus ψ is completely determined by the indicator growth function of Z and Lemma 5.2 immediately implies the following result. Lemma 5.6 Every continuous, SL(n) contravariant and translation invariant Minkowski valuation Z : Conv(R n ) → K n is uniquely determined by its indicator growth function.

Proof of Theorem 1
If ζ ∈ D n−2 (R), then Lemma 4.1 shows that the operator u → ζ • u defines a continuous, decreasing, SL(n) contravariant and translation invariant Minkowski valuation on Conv(R n ).
Conversely, let a continuous, monotone, SL(n) contravariant and translation invariant Minkowski valuation Z be given and let ζ be its indicator growth function. Lemma 5.5 implies that we may assume that Z is decreasing. It follows from the definition of ζ in Lemma 5.1 that ζ is non-negative and continuous. To see that ζ is decreasing, note that by the definition of ζ in Lemma 5.1, for every t ∈ R and that Z is decreasing. By Lemma 5.3 combined with Lemma 1.6, the function ζ has finite (n − 2)-nd moment. Thus ζ ∈ D n−2 (R).
For u = I P + t with P ∈ P n 0 and t ∈ R, we obtain by (22) that for every z ∈ S n−1 . Hence ζ • (I P + t) = ζ(t) P for P ∈ P n 0 and t ∈ R. By Lemma 4.1, defines a continuous, decreasing, SL(n) contravariant and translation invariant Minkowski valuation on Conv(R n ) and ζ is its indicator growth function. Thus Lemma 5.6 completes the proof of the theorem.

Classification of measure-valued valuations
The aim of this section is to prove Theorem 3. Let n ≥ 3.
for every K ∈ K n 0 and t ∈ R.
As in the proof of Lemma 5.1, we see that Y t is a weakly continuous valuation that is SL(n) contravariant of degree 1 for every t ∈ R. By Theorem 2.6 and (14), for t ∈ R, there is c t ≥ 0 such that Y t (K , ·) = Y( K + t, ·) = c t S(K , ·) + S(−K , ·) for all K ∈ K n 0 . This defines a non-negative function ψ(t) = 1 2 c t . Since t → Y( K +t, S n−1 ) is continuous, also ψ is continuous. The result for indicator functions and ζ follows along similar lines.
For a weakly continuous valuation Y : Conv(R n ) → M e (S n−1 ) that is SL(n) contravariant of degree 1, we call the function ψ from Lemma 6.1, the cone growth function of Y and we call the function ζ its indicator growth function.
is a weakly continuous valuation that is SL(n) contravariant of degree 1 and translation invariant, then Moreover, ψ is decreasing and lim t→+∞ ψ(t) = 0.
Proof Recall that the cosine transform C Y(u, ·) is the support function of a convex body that contains the origin for every u ∈ Conv(R n ). By the properties of Y, this induces a continuous, SL(n) contravariant and translation invariant Minkowski valuation Z : Conv(R n ) → K n via h(Z(u), y) = 1 2 C Y(u, ·)(y) for y ∈ R n . By Lemma 6.1, we have for every K ∈ K n 0 , t ∈ R and y ∈ R n . Hence, by Lemma 5.1, the function ψ is the cone growth function of Z. Similarly, it can be seen, that ζ is the indicator growth function of Z. The result now follows from Lemma 5.3 and Lemma 5.4.

Lemma 6.3 Every weakly continuous, increasing valuation
Proof Since Y is increasing, Lemma 6.1 implies that for s < t for every K ∈ K n 0 . Hence, ψ is an increasing function. By Lemma 6.2, ψ ≡ 0. Lemma 1.7 implies that Y is trivial.

of degree 1 and translation invariant is uniquely determined by its indicator growth function.
Proof By Lemma 6.2, we have lim t→+∞ ψ(t) = 0 and ζ(t) = (−1) n−1 (n−1)! d n−1 dt n−1 ψ(t). This shows that ζ uniquely determines ψ. Since Lemma 1.7 implies that Y is determined by its cone growth function, this implies the statement of the lemma.

Proof of Theorem 3
By Lemma 3.3, the map Y : Conv(R n ) → M e (S n−1 ) defined in (3) is a weakly continuous, decreasing valuation that is SL(n) contravariant of degree 1 and translation invariant.
Conversely, let Y : Conv(R n ) → M e (S n−1 ) be a weakly continuous, monotone valuation that is SL(n) contravariant of degree 1 and translation invariant. Let ζ : R → [0, ∞) be its indicator growth function. If Y is increasing, then Lemma 6.3 shows that Y is trivial. Hence we may assume that Y is decreasing. Lemma 6.2 combined with Lemma 1.6 implies that ζ ∈ D n−2 (R). Now, for u = I K + t with K ∈ K n 0 and t ∈ R we obtain by Lemma 6.1 and by the definition of S( ζ • u , ·) in Lemma 3.2 that Y(u, ·) = 1 2 ζ(t)(S(K , ·) + S(−K , ·)) = S( ζ • u , ·). By Lemma 3.3, defines a weakly continuous, decreasing valuation on Conv(R n ) that is SL(n) contravariant of degree 1 and translation invariant and ζ is its indicator growth function. Thus Lemma 6.4 completes the proof of the theorem.

SL(n) covariant Minkowski valuations on Conv(R n )
The operator that appears in Theorem 2 is discussed. It is shown that it is a continuous, monotone, SL(n) covariant and translation invariant Minkowski valuation. Moreover, a geometric interpretation is derived.
We require the following results.
Proof Fix ε > 0 and u ∈ Conv(R n ). Let ρ ε ∈ C ∞ (R) denote a standard mollifying kernel such that R n ρ ε (x) dx = 1, supp ρ ε ⊆ B ε (0) and ρ ε (x) ≥ 0 for all x ∈ R n . Write τ ε for the translation t → t + ε on R and define ζ ε (t) for t ∈ R as As in the proof of Lemma 3.1, it is easy to see that ζ ε is smooth and strictly decreasing and that +∞ 0 ζ ε (t) dt < +∞.
Moreover, ζ ε (t) > ζ(t) ≥ 0 for every t ∈ R. Hence, {ζ • u ≥ t} ⊆ {ζ ε • u ≥ t} for every t ≥ 0 and therefore it suffices to show that for every z ∈ S n−1 . By Lemma 1.3, there exist constants a, b ∈ R with a > 0 such that u(x) > v(x) = a|x| + b for all x ∈ R n . Hence, by substituting t = ζ ε (s) and by integration by parts, we obtain which concludes the proof.
for every z ∈ S n−1 . Since the integral in the definition of [ζ • u] converges by Lemma 7.1, this shows that u → [ζ • u] is well-defined and decreasing on Conv(R n ). Now, let u ∈ Conv(R n ) and u k ∈ Conv(R n ) be such that epi-lim k→∞ u k = u. By Lemma 1.1, the sets {u k ≤ t} converge in the Hausdorff metric to the set {u ≤ t} for every t = min x∈R n u(x), which is equivalent to the convergence {ζ • u k ≥ t} → {ζ • u ≥ t} for every t = max x∈R n ζ(u(x)). By Lemma 1.4, there exist constants a, b ∈ R with a > 0 such that for every k ∈ N and x ∈ R n u k (x) > v(x) = a|x| + b and therefore ζ(u k (x)) < ζ (v(x)) for every x ∈ R n and k ∈ N and hence also for every t ≥ 0, k ∈ N and z ∈ S n−1 where we have used the symmetry of v. By Lemma 7.1, we can apply the dominated convergence theorem, which shows that u → [ζ • u] is continuous.
Finally, since u → {ζ • u ≥ t} defines an SL(n) covariant Minkowski valuation for every t > 0, it is easy to see that also u → [ζ • u] has these properties.
Let f = ζ • u with ζ ∈ D 0 (R) and u ∈ Conv(R n ). Write E(z) for the linear span of z ∈ S n−1 . By the definition of the level set body, the difference body, the projection of a quasi-concave function (9), and (10), we have This corresponds to the geometric interpretation of the projection body from (23). for every s ∈ R, where τ r is the translation x → x + re 1 . By translation invariance, the valuation property and Lemma 8.2, this gives h(Z(u h r + t), e 1 ) = h(Z( T r/ h + t), e 1 ) − h(Z( T r/ h + t + h), e 1 ) for every t ∈ R. Note, that by Lemma 1. The function ζ = −ψ appearing in the above Lemma is called the indicator growth function of Z. Lemma 8.3 shows that the indicator growth function ζ of a continuous, SL(n) covariant and translation invariant Minkowski valuation Z determines its cone growth function ψ up to a constant. Since lim t→∞ ψ(t) = 0, the constant is also determined by ζ . Thus ψ is completely determined by the indicator growth function of Z and Lemma 1.7 implies the following result. Conversely, let now a continuous, monotone, SL(n) covariant and translation invariant Minkowski valuation Z be given and let ζ be its indicator growth function. Lemma 8.5 implies that we may assume that Z is decreasing. By Lemma 8.7, the valuation Z is uniquely determined by ζ . For P = [0, e 1 ] ∈ P n 0 , we have h(Z(I P + t), e 1 ) = ζ(t) h(D P, e 1 ) = ζ(t) for every t ∈ R. Since Z is decreasing, also ζ is decreasing. Since ζ = −ψ , it follows from Lemma 8.3 that Thus ζ ∈ D 0 (R).
For u = I P + t with arbitrary P ∈ P n 0 and t ∈ R, we have for every z ∈ S n−1 . Hence D [ζ • (I P + t)] = ζ(t) D P for P ∈ P n 0 and t ∈ R. By Lemma 7.3, defines a continuous, decreasing, SL(n) covariant and translation invariant Minkowski valuation on Conv(R n ) and ζ is its indicator growth function. Thus Lemma 8.7 completes the proof of the theorem.