PhyslibAlpha.Mathematics.Order.PositiveDual.RieszKantorovich
The Riesz–Kantorovich formula
i. Overview
An ordered real vector space has the Riesz decomposition when a nonnegative element below a sum of two nonnegative elements splits into pieces below the summands. Vector lattices have it. Then any two positive functionals have a least upper bound, given by the Riesz–Kantorovich formula `(φ ⊔ ψ) f = sup {φ g + ψ (f - g) | 0 ≤ g ≤ f}`: the positive functionals form a lattice.
In a lattice of positive functionals, a positive functional below a sum splits into pieces below the summands, and finite families with the same sum have common refinements.
ii. Key results
- `HasRieszDecomposition E` : the Riesz decomposition. - `PositiveLinearMap.isLUB_rkSup` : the Riesz–Kantorovich formula gives the least upper bound. - `HasLatticeDualCone E` : the positive functionals form a lattice. - `HasRieszDecomposition.hasLatticeDualCone` : the Riesz decomposition makes the positive functionals a lattice. - `VectorLattice.hasLatticeDualCone` : the positive functionals on a vector lattice form a lattice. - `HasLatticeDualCone.exists_refinement` : positive functionals refine. - `PositiveLinearMap.HasRefinement` : finite families with the same sum have a common refinement.
iii. Table of contents
- A. The Riesz–Kantorovich supremum
- B. The lattice dual cone
- C. Riesz decomposition of positive functionals
- D. Finite refinement of positive functionals
iv. References
- C. D. Aliprantis and O. Burkinshaw, *Positive Operators*, Springer, 2006, ch. 1.
- E. M. Alfsen, *Compact Convex Sets and Boundary Integrals*, Springer, 1971, ch. II.
A. The Riesz–Kantorovich supremum
B. The lattice dual cone
C. Riesz decomposition of positive functionals
D. Finite refinement of positive functionals
21 declarations
Riesz decomposition property for an ordered group
For an ordered additive commutative group , the Riesz decomposition property states that for any elements such that , , and , there exist such that with and .
Vector Lattices Have the Riesz Decomposition Property
Let be a lattice-ordered group (or a vector lattice). For any elements such that , , and , there exist such that with and .
Riesz–Kantorovich supremum
Let be an ordered real vector space and let be positive linear maps. For any element , this definition calculates the Riesz–Kantorovich supremum as This value represents the best split of between the functionals and .
The set is bounded above
Let be an ordered real vector space and let be positive linear maps. For any , the set is bounded above in .
Let be an ordered real vector space and let be positive linear maps. For any elements such that , the sum is less than or equal to the Riesz–Kantorovich supremum , which is defined as .
Let be an ordered real vector space and let be positive linear maps. For any element such that and any , if for all satisfying , then the Riesz–Kantorovich supremum satisfies .
The Riesz–Kantorovich supremum is non-negative for
Let be an ordered real vector space and let be positive linear maps. For any element such that , the Riesz–Kantorovich supremum, defined as , is non-negative, i.e., .
Superadditivity of the Riesz–Kantorovich Supremum:
Let be an ordered real vector space and let be positive linear maps. Let the Riesz–Kantorovich supremum be defined as For any non-negative elements , it holds that
Additivity of the Riesz–Kantorovich Supremum on the Positive Cone
Let be an ordered real vector space that satisfies the Riesz decomposition property. Let and be positive linear maps from to . For any such that and , the Riesz–Kantorovich supremum, defined by , is additive on the positive cone:
for and
Let be an ordered real vector space where scalar multiplication by positive reals is monotonic. Let be positive linear maps. For any positive real number and any non-negative element (), the Riesz–Kantorovich supremum satisfies the following homogeneity property: where the Riesz–Kantorovich supremum is defined as .
Riesz–Kantorovich supremum as a positive linear map
Let be an ordered real vector space satisfying the Riesz decomposition property. Given two positive linear functionals , the Riesz–Kantorovich supremum is the positive linear functional on defined on the positive cone by the formula: for all . The definition extends this mapping from the positive cone to the entire space to form a complete positive linear functional.
Evaluation of the Riesz–Kantorovich supremum map for
Let be an ordered real vector space satisfying the Riesz decomposition property. Let and be positive linear functionals from to . For any non-negative element (where ), the value of the Riesz–Kantorovich supremum functional evaluated at is equal to the supremum of the values obtained by splitting between and :
The Riesz–Kantorovich Map is the Least Upper Bound of and
Let be an ordered real vector space that satisfies the Riesz decomposition property. For any two positive linear functionals , the Riesz–Kantorovich supremum map , defined for each by the formula is the least upper bound of the set with respect to the partial order on positive linear functionals.
The positive functionals on form a lattice
For an ordered real vector space over , the property `HasLatticeDualCone E` states that the space of positive linear functionals forms a join-semilattice. Specifically, for any two positive linear functionals and , there exists a positive linear functional that is their least upper bound (supremum), denoted , with respect to the partial order where if for all in .
The Riesz Decomposition Property implies the Positive Functionals form a Lattice
Let be an ordered real vector space over that is a directed order. If satisfies the Riesz decomposition property—meaning that for any such that , and , there exist such that with and —then the space of positive linear functionals on forms a lattice (i.e., for any two positive linear functionals, their least upper bound exists).
The positive linear functionals on a real vector lattice form a lattice (Riesz–Kantorovich Theorem)
Let be a real vector lattice (an ordered real vector space over that is also a lattice). Then the space of positive linear functionals on forms a lattice. That is, for any two positive linear functionals , there exists a least upper bound with respect to the partial order where if and only if for all in .
Riesz decomposition: with and
Let be an ordered real vector space such that the space of positive linear functionals on forms a lattice. For any positive linear functionals satisfying , there exist positive linear functionals and such that , , and .
Riesz refinement: splitting a sum of positive functionals into families summing to and
Let be an ordered real vector space such that the positive linear functionals on form a lattice. Let be a finite family of positive linear functionals on , and let and be positive linear functionals such that their sum equals the sum of the family: Then there exist two families of positive linear functionals and such that for each , the functional splits as , and the sums of these families satisfy:
Finite refinement property for positive linear functionals
Let be an ordered real vector space. The property `HasRefinement E` states that for any two finite families of positive linear functionals and on such that their sums are equal, i.e., , there exists a family (or "table") of positive linear functionals such that: 1. The sum of each row matches the first family: for all . 2. The sum of each column matches the second family: for all .
Let be an ordered real vector space with a directed order. If the space of positive linear functionals on forms a lattice (specifically, a join-semilattice, denoted by the property `HasLatticeDualCone E`), then satisfies the finite refinement property for positive linear functionals. This means that for any two finite families of positive linear functionals and such that their sums are equal, i.e., there exists a family of positive linear functionals such that for each , , and for each , .
Existence of a common refinement table for sums of positive linear functionals
Let be an ordered real vector space that satisfies the refinement property. Suppose and are two families of positive linear functionals on indexed by finite sets and . If the sums of these families are equal, i.e., then there exists a family of positive linear functionals such that for each , the sum over is (i.e., ), and for each , the sum over is (i.e., ).
