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Discrete probabilistic and algebraic dynamics: a stochastic commutative Gelfand-Naimark Theorem (1708.00091v2)

Published 31 Jul 2017 in math.FA, math-ph, math.CT, math.MP, and math.PR

Abstract: We introduce a category of stochastic maps (certain Markov kernels) on compact Hausdorff spaces, construct a stochastic analogue of the Gelfand spectrum functor, and prove a stochastic version of the commutative Gelfand-Naimark Theorem. This relates concepts from algebra and operator theory to concepts from topology and probability theory. For completeness, we review stochastic matrices, their relationship to positive maps on commutative $C*$-algebras, and the Gelfand-Naimark Theorem. No knowledge of probability theory nor $C*$-algebras is assumed and several examples are drawn from physics.

Citations (6)

Summary

  • The paper introduces a stochastic framework that generalizes the classical Gelfand-Naimark theorem using Markov kernels on compact Hausdorff spaces.
  • It employs Choquet theory to represent states as convex combinations, circumventing the Riesz-Markov-Kakutani theorem.
  • The study bridges algebra, topology, and probability, offering new insights into both classical and quantum stochastic dynamics.

A Stochastic Commutative Gelfand-Naimark Theorem: Bridging Topology and Algebra through Probability

The paper offers a profound exploration of the intersection between algebra, topology, and probability theory through the development of a stochastic analogue of the commutative Gelfand-Naimark Theorem. It introduces a category of stochastic maps, which are expressed in terms of Markov kernels on compact Hausdorff spaces, and constructs a stochastic version of the Gelfand spectrum functor. The focus is on how algebraic concepts like commutative CC^*-algebras and operator theory relate intimately with topological and probabilistic concepts, revealing new insights while generalizing classical results.

Key Contributions

Stochastic Maps and Compact Hausdorff Spaces

The category of stochastic maps is critically examined, and the paper accomplishes several significant tasks: it establishes a framework for stochastic maps (Markov kernels) on compact Hausdorff spaces and develops a method to characterize these maps using stochastic matrices. The construction of a stochastic analogue of the Gelfand spectrum functor is pivotal in expressing a functorial relationship between compact Hausdorff spaces and commutative CC^*-algebras, following the classical Gelfand-Naimark terrain.

Mathematical Foundations and Assumptions

The Gelfand-Naimark Theorem, showcasing the duality between commutative CC^*-algebras and compact Hausdorff spaces, is extended into the stochastic domain. This achievement is possible by considering continuous stochastic maps, which associate to every stochastic process a corresponding positive linear transformation between commutative CC^*-algebras. The methodology employed circumvents the need for the Riesz-Markov-Kakutani Representation Theorem, instead utilizing Choquet theory to cast states as convex combinations of measures, highlighting the constructive interplay between algebra and probability.

Theoretical and Practical Implications

The theoretical implications of the presented theorem are profound, offering a more nuanced understanding of the interplay between deterministic and non-deterministic processes within algebraic and topological frameworks. Practically, this contributes valuable insights into how quantum and classical systems can be compared and mixed within the CC^*-algebraic framework. The stochastic generalization paves the way for further research into non-commutative spaces and potentially impacts fields like quantum probability and information theory.

Stochastic Maps in Quantum Mechanics

The consideration of completely positive maps as non-deterministic dynamics in quantum theory within this framework emphasizes their importance as quantum analogues to classical stochastic processes. By detailing how composition of stochastic maps corresponds to transformations in CC^*-algebras, the paper supports the thesis that quantum operations can be naturally extended from classical probabilistic operations, highlighting this continuity within a categorical setting.

Future Directions

The paper sets the stage for further expansion into non-commutative topology. As understanding deepens around the categorical aspects of probability, future research could explore broader applications, especially in quantum information theory. Furthermore, tools from category theory could potentially lead to a refined understanding of how topological and algebraic structures derive from probabilistic systems, especially under constraints of regularity and continuity.

In conclusion, this paper enriches the dialogue between topology, algebra, and probability theory, offering a stochastic framework that not only highlights existing dualities but also opens up possibilities for new lines of inquiry in mathematics and physics. Its implications for both theoretical research and practical applications could be substantial, making this a notable contribution to the field.

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