PhyslibAlpha.ProbabilisticTheory.Composite.TensorCone
Composite systems
i. Overview
Two systems with observables `E` and `F` are combined into a composite system whose observables are the tensor products `E ⊗ F`. Which composite observables are nonnegative is not fixed by the parts; there are two extreme choices.
The minimal cone contains only the sums of products `x ⊗ y` of nonnegative observables: nonnegative local observations. The maximal cone contains every composite observable that no pair of local preparations `φ ⊗ ψ` can assign a negative value. A composite of `E` and `F` is any choice of nonnegative composite observables in between. Tensor products of positive maps preserve both extreme cones.
A system is nuclear when, for every other system, the maximal cone lies in the closure of the minimal cone: its composites are unique.
ii. Key results
- `Composite E F` : the observables of the composite system. - `PositiveLinearMap.tensor` : the product functional `φ ⊗ ψ`. - `minTensorCone E F`, `maxTensorCone E F` : the minimal and the maximal cone. - `mem_maxTensorCone` : the maximal cone consists of the composite observables that every product functional keeps nonnegative. - `minTensorCone_map_le`, `maxTensorCone_map_le` : tensor products of positive maps preserve the minimal and the maximal cone. - `CompositeCone E F` : a composite of `E` and `F`. - `isDominatedCone_minTensorCone` : every composite observable plus a large multiple of `1 ⊗ 1` lies in the minimal cone. - `minTensorClosure E F` : the Archimedean closure of the minimal cone. - `IsNuclear E` : composition with every Archimedean system is unique, up to closure. - `mem_maxTensorCone_iff_rslice` : for Archimedean `E`, the maximal cone consists of the composite observables that stay nonnegative when a positive functional is applied to the second factor.
iii. Table of contents
- A. Slices and product functionals
- B. The minimal and the maximal cone
- C. Tensor products of positive maps
- D. Composites
- E. The closure of the minimal cone and nuclear systems
A. Slices and product functionals
B. The minimal and the maximal cone
C. Tensor products of positive maps
D. Composites
E. The closure of the minimal cone and nuclear systems
48 declarations
Space of observables for the composite system
Given two physical systems with observable spaces and , the space of observables for the composite system is defined as the tensor product .
Tensor product of observables
For two physical systems with observable spaces and , this function maps an observable and an observable to their tensor product in the composite observable space .
Right slice map defined by a positive functional on
For a positive linear functional , the right slice map is the linear map obtained by applying to the second factor of the tensor product and identifying with . For an elementary tensor , the map is defined by .
Left slice map from to
Given a positive linear functional , the left slice map is the linear map from the tensor product to obtained by applying to the first factor. For any and , the map is defined on basic tensors by .
Let and be vector spaces over . For a positive linear functional and elements and , the right slice map applied to the elementary tensor satisfies:
Action of the Left Slice Map on Elementary Tensors:
Let and be vector spaces over . For any positive linear functional and any elements and , the left slice map applied to the elementary tensor is equal to the scalar multiplied by the vector :
Product functional on
Given two positive linear functionals and , the product functional is the linear map from the tensor product to defined by the composition . For any elementary tensor , the functional satisfies: This functional represents the joint preparation or product state in a composite system.
Action of the Product Functional on Elementary Tensors:
Let and be vector spaces over . For any positive linear functionals and , and for any elements and , the product functional applied to the elementary tensor is equal to the product of the values and :
For positive linear functionals and , and for any element of the tensor product, the product functional evaluated at satisfies: where is the right slice map obtained by applying to the second factor of the tensor product.
Let and be vector spaces over . For any positive linear functionals and , and for any element in the tensor product , the product functional applied to is equal to the functional applied to the left slice of by . That is,
Minimal tensor cone of and
Given two ordered real vector spaces and , the minimal tensor cone is a pointed cone in the tensor product consisting of all finite sums of elementary tensors where and are non-negative elements (i.e., and ).
Maximal tensor cone of and
Let and be ordered real vector spaces representing physical systems. The maximal tensor cone, denoted as , is the pointed cone in the algebraic tensor product consisting of all composite observables that are non-negative under every product of positive linear functionals. That is, if and only if for all positive linear functionals and , the product functional satisfies .
In the context of composite systems represented by ordered real vector spaces and , let and be non-negative elements (i.e., and ). Then their elementary tensor product is an element of the minimal tensor cone of the algebraic tensor product .
Non-negative Scalar Multiplication Preserves Membership in the Minimal Tensor Cone
Let and be ordered real vector spaces and be their algebraic tensor product. Let the minimal tensor cone, denoted as , be the cone in generated by the elementary tensors of non-negative elements. For any non-negative real scalar and any element , the scalar product is also an element of .
Induction Principle for the Minimal Tensor Cone
Let and be ordered real vector spaces representing physical systems, and let be their composite system's space of observables. Let be a property of observables in and be an observable in the minimal tensor cone. If the following conditions hold: - is true for all non-negative observables and , - is true, - is true whenever and are true, - is true for all whenever is true, then is true for all in the minimal tensor cone.
The product functional equals the pairing with the dual tensor product of functionals.
Let and be ordered real vector spaces representing physical systems. Given two positive linear functionals and , let denote their product functional on the composite system . For any element , the value of the product functional is equal to the value obtained by applying the tensor product of the linear maps and (viewed as an element of the dual tensor space ) to via the canonical distribution map. Mathematically, this identity is: where is the natural map from the tensor product of dual spaces to the dual of the tensor product, .
Let and be ordered real vector spaces representing physical systems. For any composite observable , belongs to the maximal tensor cone if and only if for all positive linear functionals and , the product functional evaluates to a non-negative result on :
Let and be ordered real vector spaces representing physical systems. The minimal tensor cone is a subset of the maximal tensor cone . Mathematically, This means that every composite observable in the minimal cone (any finite sum of elementary tensors where and ) is also contained in the maximal cone (the set of observables such that for all positive linear functionals and ).
Positive Maps Preserve the Positive Cone
Let and be ordered vector spaces over . For any positive linear map , the image of the positive cone of under is contained in the positive cone of . Mathematically, if , then .
Tensor Products of Positive Maps Preserve the Minimal Cone
Let and be ordered real vector spaces. If and are positive linear maps, then the image of the minimal tensor cone of under the tensor product map is contained in the minimal tensor cone of .
Tensor products of positive maps preserve the maximal cone
Let and be ordered real vector spaces. Given positive linear maps and , the image of the maximal tensor cone of under the tensor product map is contained in the maximal tensor cone of . That is, where the maximal tensor cone of consists of those tensors such that for all positive linear functionals and .
Tensor product maps preserve membership in the minimal tensor cone
Let and be ordered real vector spaces. Let and be positive linear maps. If an element of the algebraic tensor product lies in the minimal tensor cone of , then its image under the tensor product map lies in the minimal tensor cone of .
Tensor products of positive linear maps preserve the maximal tensor cone
Let and be ordered real vector spaces representing systems of observables. Let and be positive linear maps. If a composite observable in the tensor product belongs to the maximal tensor cone of and , then its image under the tensor product map, , belongs to the maximal tensor cone of and .
Archimedean property of a tensor cone
A pointed cone of composite observables is **Archimedean** if, for every , the condition that for all implies that , where and are the identity elements of the systems and respectively.
Set-like property of `CompositeCone E F` in
The structure `CompositeCone E F` is treated as a set of elements within the tensor product . This enables the use of set-theoretic notation for composite cones, such that for any and any composite observable , the statement is well-defined and corresponds to belonging to the underlying pointed cone of .
Given a composite cone of the systems and , a composite observable belongs to the underlying pointed cone of if and only if . Here, the notation refers to the membership of in the set of nonnegative observables defined by the composite cone structure.
Extensionality for composite cones ()
Let and be systems of observables, and let be their tensor product space. For any two composite cones , if for every composite observable it holds that if and only if , then the composite cones are equal ().
Let and be physical systems with observables. For any composite cone associated with the composite system , if and are nonnegative observables ( and ), then their tensor product is an element of .
Product of Positive Functionals is Non-negative on Composite Cones
Let and be systems and let be a composite cone on the tensor product . For any positive linear functionals and , and for any composite observable , the product functional is non-negative on :
The elements of a composite cone form an -module
Given a composite cone of systems and , the set of elements in (viewed as a pointed cone) forms a module over the semiring of nonnegative real numbers . This structure inherits the addition and scalar multiplication from the underlying tensor product space .
Minimal composite cone of and
For two systems with ordered real vector spaces of observables and , the minimal composite cone is the composite structure on the tensor product whose positive cone is the minimal tensor cone. This cone is generated by the set of elementary tensors where and are nonnegative observables in and respectively.
Maximal composite cone of and
For two ordered real vector spaces and representing physical systems, the maximal composite cone is the composite structure on the tensor product whose set of nonnegative elements is defined by the maximal tensor cone. This cone consists of all tensors such that for every pair of positive linear functionals and , the product functional yields a non-negative result, i.e., .
is Archimedean
A composite cone is **Archimedean** if for every composite observable , the condition that for all implies that . Here, and denote the identity elements of the systems and respectively.
-linear map for
Given a composite cone of systems and and a fixed non-negative element (such that ), `tmulRight` is the -linear map from the positive cone of to the cone defined by . This map embeds non-negative observables of into the composite system by tensoring them on the right with the fixed observable .
The value of is
Let and be real vector spaces and be a composite cone. Given a non-negative element (i.e., ), let be the -linear map defined by tensoring on the right with . For any , the image of under this map is equal to the tensor product in .
-linear map for
Given a composite cone of systems and and a fixed non-negative element (such that ), `tmulLeft` is the -linear map from the positive cone of to the cone defined by . This map embeds non-negative observables of into the composite system by tensoring them on the left with the fixed observable .
Let and be systems and be a composite cone of and . For any non-negative observable (where ) and any element in the positive cone , the value of the -linear map applied to is the tensor product of and : where denotes the tensor product in .
Every is a difference of elements in the minimal tensor cone
For any element in the tensor product , there exist elements and in the minimal tensor cone of and such that . In this context, the minimal tensor cone is the set of all finite sums of elementary tensors where and are non-negative elements. Thus, every composite observable can be expressed as a difference of two sums of products of non-negative observables.
is in the minimal tensor cone
For any observables and , there exists a real number such that the composite observable belongs to the minimal tensor cone of the composite system . Specifically, for sufficiently large such that and , the identity shows that the expression is a sum of products of nonnegative observables.
for some
Let and be ordered real vector spaces with identity observables and . For any element in the algebraic tensor product , there exists a real number such that the element belongs to the minimal tensor cone of .
The Minimal Tensor Cone is Dominated by
In the composite system of two ordered vector spaces and with units and , the minimal tensor cone is dominated by the tensor product of the units . That is, for any element , there exists a scalar such that lies in the minimal tensor cone.
Archimedean closure of the minimal tensor cone
The Archimedean closure of the minimal tensor cone in the algebraic tensor product of two observable spaces and . A composite observable belongs to this set if, for every , the element lies within the minimal tensor cone, where and are the identity elements of the respective systems.
Minimal Tensor Cone is a Subset of its Archimedean Closure
The minimal tensor cone of the algebraic tensor product of two observable spaces and is a subset of its Archimedean closure.
Archimedean Closure of the Minimal Tensor Cone Maximal Tensor Cone
In the algebraic tensor product of two observable spaces and , the Archimedean closure of the minimal tensor cone is a subset of the maximal tensor cone. That is, This means that if an element has the property that lies in the minimal tensor cone for all , then it necessarily satisfies for all pairs of positive linear functionals and .
An Archimedean cone containing the minimal tensor cone contains its closure
Let and be observable spaces and let be their algebraic tensor product. Let be a pointed cone that is Archimedean, meaning that for any , if for all , then . If contains the minimal tensor cone of , then it also contains the Archimedean closure of the minimal tensor cone.
An Archimedean composite cone contains the Archimedean closure of the minimal tensor cone
Let and be observable spaces and be their algebraic tensor product. If a composite cone is Archimedean, then it contains the Archimedean closure of the minimal tensor cone. That is, A composite cone is said to be Archimedean if for every composite observable , the condition that for all implies that , where and are the identity elements of the respective systems.
System is nuclear
A system is said to be **nuclear** if for every Archimedean system , the maximal tensor cone is contained within the Archimedean closure of the minimal tensor cone. That is, for any Archimedean system , we have the inclusion: This condition ensures that the choice of a composite cone between the minimal and maximal cones is unique up to Archimedean closure.
Let be an Archimedean ordered real vector space and be an ordered real vector space. An element in the tensor product belongs to the maximal tensor cone if and only if for every positive linear functional , the right slice is a non-negative element of . Here, the right slice is the linear map defined on elementary tensors by .
