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Theory and applications of categories

Generalized information structures and their cohomology

Juan Pablo Vigneaux

Published Sep 22, 2017• 3 citations
OpenAlex

Abstract

Baudot and Bennequin introduced a cohomological construction adapted to information theory, called \emph{information cohomology}; it characterizes Shannon entropy as the only nontrivial cohomology class in degree one, for suitable coefficients. This text develops the relation between information cohomology and topos theory. To this end, we redefine information structures, as categories of random variables related by a notion of extension or refinement; classical and quantum probability spaces appear as models (or representations) of them. These generalized information structures form a category with finite products and coproducts. Information cohomology is a derived functor in the abelian category of modules over an algebra of random variables, a subcategory of the presheaf topos associated with the information structure. The cohomology is invariant under isomorphisms of generalized structures. We prove that the relatively free bar construction gives a projective object for the computation of this invariant. We provide detailed computations of $H^0$ and $H^1$ when the coefficients are functionals of classical probabilities, including the degenerate cases. In the process, we also establish the homological nature of Tsallis entropies, as the only cocycles in degree one for certain one-parameter family of modules.

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Baudot and Bennequin introduced a cohomological construction adapted to information theory, called \emph{information cohomology}; it characterizes Shannon entropy as the only nontrivial cohomology class in degree one, for suitable coefficients. This text develops the relation between information cohomology and topos theory. To this end, we redefine information structures, as categories of random variables related by a notion of extension or refinement; classical and quantum probability spaces appear as models (or representations) of them. These generalized information structures form a category with finite products and coproducts. Information cohomology is a derived functor in the abelian category of modules over an algebra of random variables, a subcategory of the presheaf topos associated with the information structure. The cohomology is invariant under isomorphisms of generalized structures. We prove that the relatively free bar construction gives a projective object for the computation of this invariant. We provide detailed computations of H0H^0H0 and H1H^1H1 when the coefficients are functionals of classical probabilities, including the degenerate cases. In the process, we also establish the homological nature of Tsallis entropies, as the only cocycles in degree one for certain one-parameter family of modules.
We introduce the category of information structures, whose objects are suitable diagrams of measurable sets that encode the possible outputs of a given family of observables and their mutual relationships of refinement; they serve as mathematical models of contextuality in classical and quantum settings.Each information structure can be regarded as a ringed site with trivial topology; the structure ring is generated by the observables themselves and its multiplication corresponds to joint measurement.We extend Baudot and Bennequin's definition of information cohomology to this setting, as a derived functor in the category of modules over the structure ring, and show explicitly that the bar construction gives a projective resolution in that category, recovering in this way the cochain complexes previously considered in the literature.Finally, we study the particular case of a one-parameter family of coefficients made of functions of probability distributions.The only 1-cocycles are Shannon entropy or Tsallis α-entropy, depending on the value of the parameter.
We propose that entropy is a universal co-homological class in a theory associated to a family of observable quantities and a family of probability distributions. Three cases are presented: (1) classical probabilities and random variables; (2) quantum probabilities and observable operators; (3) dynamic probabilities and observation trees. This gives rise to a new kind of topology for information processes, that accounts for the main information functions: entropy, mutual-informations at all orders, and Kullback–Leibler divergence and generalizes them in several ways. The article is divided into two parts, that can be read independently. In the first part, the introduction, we provide an overview of the results, some open questions, future results and lines of research, and discuss briefly the application to complex data. In the second part we give the complete definitions and proofs of the theorems A, C and E in the introduction, which show why entropy is the first homological invariant of a structure of information in four contexts: static classical or quantum probability, dynamics of classical or quantum strategies of observation of a finite system.
We develop a cohomological framework for entanglement entropy that unifies information theory, operator algebras, and noncommutative geometry. Entropy is a 1-cocycle in information cohomology; we generalize this to the quantum setting via Hochschild and cyclic cohomology. For an inclusion of von Neumann algebras N contained in M with a faithful normal state w admitting a cyclic and separating vector, and a conditional expectation E: M -> N (whose existence is equivalent to modular invariance of N by Takesaki's theorem), we construct the entanglement complex as the image of the transgression map tau_w on the relative cyclic complex, where A is a dense *-subalgebra of M and B = A intersect N. Our main result identifies entanglement cohomology with the kernel of the restriction map HC*(A) -> HC*(B), up to the connecting homomorphism d of the long exact sequence of the pair (A,B); when d = 0, the identification is exact. The relative modular cocycle u_t = (Dw : D(w|_N) o E)_t generates explicit entanglement classes when E is not w-invariant, with the Araki relative entropy as its infinitesimal generator. The framework accommodates Type III von Neumann algebras, where no local density matrix exists, and leads to a holographic proposal: a subspace of H^1_ent is conjecturally dual to linearized modular Hamiltonian perturbations of the bulk entanglement wedge. We verify the construction in finite-dimensional, type II_1, and type III_1 examples.
In the topos approach to quantum theory, the spectral presheaf plays the role of the state space of a quantum system. We show how a notion of entropy can be defined within the topos formalism using the equivalence between states and measures on the spectral presheaf. We show how this construction unifies Shannon and von Neumann entropy as well as classical and quantum Renyi entropies. The main result is that from the knowledge of the contextual entropy of a quantum state of a finite-dimensional system, one can (mathematically) reconstruct the quantum state, i.e., the density matrix, if the Hilbert space is of dimension 333 or greater. We present an explicit algorithm for this state reconstruction and relate our result to Gleason's theorem.
Abstract. We propose that entropy is a universal co-homological class in a theory associated to a family of observable quantities and a family of probability distributions. Three cases are presented: 1) classical probabilities and random variables; 2) quantum probabilities and observable operators; 3) dynamic probabilities and observation trees. This gives rise to a new kind of topology for information processes. We discuss briefly its application to complex data, in particular to the structures of information flows in biological systems. This short note summarizes results obtained during the last years by the authors. The proofs are not included, but the definitions and theorems are stated with precision.
The Global Hilbert Space Boundary Screening Theory (GHS-BST) defines physical reality as the projection of informational structures through boundary screening. This paper provides the rigorous mathematical foundations for the theory. We employ category theory to reformulate the global Hilbert space \mathcal{H}{\text{global}} and the boundary screening mechanism, and topos theory as the mathematical framework for information ontology. We construct the information category \mathcal{I}, whose objects are all possible informational structures and whose morphisms are transformations between informational structures. We prove that the five axioms of GHS-BST are consistent within this mathematical framework, and demonstrate that Hilbert space is a realization of the information category under specific representational conditions. Furthermore, we introduce the von Neumann algebraic criterion for indecomposability: \mathcal{H}{\text{global}} is indecomposable if and only if its associated operator algebra \mathcal{A}_{\text{global}} has trivial center (i.e., is a Type III factor). This provides a rigorous mathematical definition of "informational primacy." Keywords: Category Theory; Topos Theory; Information Ontology; von Neumann Algebra; Type III Factor; GHS-BST; Mathematical Foundations