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Contextuality and Semi-Module Cohomology Characterization of Contextuality with Semi-Module Cechˇ Cohomology and its Relation with Cohomology of Effect Algebras Sidiney B. Montanhano Departamento de Matem´atica Aplicada Instituto de Matem´atica, Estat´ıstica e Computac¸˜ao Cient´ıfica Universidade Estadual de Campinas Campinas, S˜ao Paulo, Brazil [email protected] I present a generalized notion of obstruction in Cechˇ cohomologyon semi-modules, which allows one to characterize non-disturbing contextual behaviors with any semi-field. This framework generalizes the usual Cechˇ cohomology used in the sheaf approach to contextuality, avoiding false positives. I revise a similar work done in the framework of effect algebras with cyclic and order cohomologies and explore the relationship with the one presented here. 1 Introduction With the codification of contextuality in the presheaf formalism [7], one can use cohomological structures to explore possible detection of contextual behaviour [9, 5, 1]. But the use of Abelian groups is not justified by the empirical model structure, and violations of this characterization occur [18, 19]. To avoid these violations, a framework based on the algebraic structure of empirical models is necessary, implying in the study of cohomology on semi-modules [31, 26]. For the characterization, however, we need to use the notion of obstruction, which is absent in this generalization of cohomology. In this paper, I introduce a generalized notion of obstruction to codify the data of the difference between contexts and achieve the characterization of contextual behavior with this generalized notion of cohomology. Once the result is presented, which follows in analogy with the previous use of cohomology for identification of contextual behavior, usually in the logical sense, I revise the formalism of effect algebras and the use of cohomological tools to identify contextuality [33]. The relation between effect algebras and empirical models is close, as one can see in Ref. [38], and can be traced to the relation between different notions of contextuality [39]. I show that both cohomological frameworks, even looking so arXiv:2104.11411v2 [math.AC] 4 Sep 2021 different in their constructions, look for the description of the model as a Boolean structure. This paper is divided as follows. In section 2, it’s given a revision of contextuality and the presheaf approach. In section 3 the cohomology for empirical models and some already known results from the literature are presented. Section 4 uses the categorical structure to show how the usual cohomology forgets data from the empirical model, enabling violations, and examples of it are given. Section 5 is a naive revision on cohomology using semi-modules instead of groups. In section 6 the description of the generalized obstruction and how it characterizes R-contextual behavior is obtained, presenting the main result of this work. Section 7 revise the effect algebra approach and the cohomologies used to detect contextual behavior, and its relation with the framework presented in this paper is explored. Section 8 presents revised examples and some commentaries about cohomological contextuality and other methods to find contextual behavior, and in section 9 the conclusions and future paths are given. © S. B. Montanhano This work is licensed under the Creative Commons Attribution License. 2 Contextuality and Semi-Module Cohomology 2 Presheaf approach Contextuality can be informally understood as the impossibility of a global description of local parts of a whole. A framework to formalize this idea is the sheaf theory, more specifically the presheaf structure. Definition 1. A presheaf is a functor F : Cop → Set of a category C to the category of sets. Let C be a site, a small category equipped with a coverage J, in other words any object U ∈ C admits a collection of families of morphisms fi : Ui → Ui∈I called covering families. A presheaf on (C,J) is a sheaf if it satisfies the following axioms • Gluing: if for all i ∈ I we have si ∈ F(Ui) such that si|Ui∩Uj = s j|Ui∩Uj , then there is s ∈ F(U) satisfying si = s|Ui ; • Locality: if s,t ∈ F(U) such that s|Ui = t|Ui for all Ui, then s = t. For a presheaf, one of the axioms that define a sheaf fails. And this is what characterizes the sheaf approach to contextuality. Let’s define the structure of this approach. Measurement scenario The sheaf approach to contextuality has as fundamental objects measurements, organized as a covering through compatibility. To the covering of measurements and the possible events, we give the name measurement scenario [2]. Definition 2. A measurement scenario hX,U ,(Ox)x∈X i is a hypergraph hX,U i, that will be called a scenario, plus some additional structure, usually enough to identify it as a simplicial complex1. X is the set of measurements, and U a covering of contexts, a family of sets of compatible measurements2. The sets (Ox)x∈X for each x ∈ X are called outcome sets, with their elements the possible events of each measurement. In this paper, we will suppose that outcome sets are finite, and therefore one can define an outcome set O for all the measurements x, and codify any Ox through an injective function fx : Ox → O. We just need to ignore elements that aren’t in the image of fx, such that these elements aren’t in the measure’s support. We will work with the set of events of contexts (OU )U∈U , and this construction will be implied. We will also work with a measurement scenario with a simplicial complex structure of contexts. Sheaf of events We can formalize the structure of events as a sheaf. First, the covering U will be restricted here to maximal contexts, that will be denoted also by U , so that hX,U i can be understood as a set X with a 3 covering U of maximal contexts Uj∈I indexed by an ordered set I . As the intersection of contexts is a context, we can define the inclusion morphism ρ( jk, j) : Uj ∩Uk → Uj, which turns the set of contexts and the inclusion morphisms in a small category.4 Therefore we can understand a scenario as a small category. 1See Ref. [28] for a justified construction of the measurement scenario. 2A formal definition of compatibility can be found in Ref. [23]. A set of measurements A is compatible if there is a measurement that can recover all the measurements of A with marginalization and classical post-processing. 3Given a covering, one can construct with unions and intersections a locale, a ”pointless space”. It means that the measure- ments aren’t the fundamental objects, turning the minimal contexts into the ”effective” measurements of the scenario, which depend on how one chooses the covering. A physical example of refinement is spin degeneration, where refinement occurs by applying a suitable magnetic field. 4From Ref. [25] we can see that the category of contexts with the inclusion is a site. S. B. Montanhano 3 Definition 3. The outcome sets are defined by a functor E : hX,U iop → Set, with E :: U 7→ OU and E :: ρ 7→ ρ′, such that for each element U ∈ U we have an outcome set OU of the context and ρ′ the restriction to the outcome sets. U These outcome spaces are by definition the tensor product O = x∈U Ox, representing all the com- bined outcomes. The morphisms of the hX,U i are reversed as restrictions ρ( j,k j) : Uj → Uj ∩Uk where N ′ j k j the intersection Uj ∩Uk is denoted by the indices jk, and they are mapped to ρ ( j,k j) : O → O :: s j 7→ U s j|k j. Elements s ∈ O of the image of a sheaf, and of a presheaf, are called local sections if U 6= X, and global sections if U = X. E ′ A compatible family is a family of sections {si ∈ (i)}i∈I such that for all j and k holds ρ ( j, jk)(s j)= ′ ρ (k, jk)(sk) ∈ E ( jk). The Gluing axiom says that the existence of a compatible family implies the ex- istence of a global section s ∈ E (X) that satisfies s| j = s j for all j. The locality axiom says that if two global sections agree on all the elements of the covering, then they are the same. For the outcomes, these axioms can be interpreted as the independence and uniqueness of events concerning contexts, and we will assume they hold. Proposition 4. By independence and uniqueness of events, the functor E is a sheaf in the site of mea- surements and contexts, called the sheaf of events of a given measurement scenario. R-empirical model R-empirical models are defined usually with a semi-ring R, such as the Boolean semi-ring B, the reals R, or the probability semi-ring R+. The choice of an R defines a way to probe the model. Definition 5. A generic semi-ring is a set R equipped with two binary operations + and · such that (R,+) is a commutative monoid with 0R: • (a + b)+ c = a + (b + c) • 0R + a = a + 0R = a • a + b = b + a (R,·) is a monoid with 1R: • (a · b) · c = a · (b · c) • a · 1R = 1R · a = a the multiplication distributes: • a · (b + c)= a · b + a · c • (a + b) · c = a · c + b · c and 0R annihilates: • a · 0R = 0R · a = 0R. D U OU To define R-empirical models, we use another functor R : Set → Set :: O 7→ µR , taking a OU P U OU U set of local events to the set R-measures defined on it µp : O → R that satisfiesnµR (oO )= 1R, U OU in analogy with probabilistic measure.
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