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We introduce quantum Markov categories as a structure that refines and extends a synthetic approach to probability theory and information theory so that it includes quantum probability and quantum information theory. In this broader…

Quantum Physics · Physics 2020-12-29 Arthur J. Parzygnat

We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum Bayesian inference wherein one considers density operators…

Quantum Physics · Physics 2012-08-23 Bob Coecke , Robert W. Spekkens

The Feynman path integral representation of quantum theory is used in a non--parametric Bayesian approach to determine quantum potentials from measurements on a canonical ensemble. This representation allows to study explicitly the…

Quantum Physics · Physics 2007-05-23 J. C. Lemm , J. Uhlig , A. Weiguny

Bayes' rule $\mathbb{P}(B|A)\mathbb{P}(A)=\mathbb{P}(A|B)\mathbb{P}(B)$ is one of the simplest yet most profound, ubiquitous, and far-reaching results of classical probability theory, with applications in any field utilizing statistical…

Quantum Physics · Physics 2023-07-20 Arthur J. Parzygnat , James Fullwood

Bayesian implementation concerns decision making problems when agents have incomplete information. This paper proposes that the traditional sufficient conditions for Bayesian implementation shall be amended by virtue of a quantum Bayesian…

Data Analysis, Statistics and Probability · Physics 2018-09-24 Haoyang Wu

Bayesian inference and uncertainty quantification in a general class of non-linear inverse regression models is considered. Analytic conditions on the regression model $\{\mathscr G(\theta): \theta \in \Theta\}$ and on Gaussian process…

Statistics Theory · Mathematics 2021-04-16 François Monard , Richard Nickl , Gabriel P. Paternain

Formulating a statistical inverse problem as one of inference in a Bayesian model has great appeal, notably for what this brings in terms of coherence, the interpretability of regularisation penalties, the integration of all uncertainties,…

Statistics Theory · Mathematics 2012-12-19 Natalia A. Bochkina , Peter J. Green

Motivated by advances in categorical probability, we introduce non-commutative almost everywhere (a.e.) equivalence and disintegrations in the setting of C*-algebras. We show that C*-algebras (resp. W*-algebras) and a.e. equivalence classes…

Quantum Physics · Physics 2023-12-18 Arthur J. Parzygnat , Benjamin P. Russo

We establish a noncommutative analogue of the first fundamental theorem of classical invariant theory. For each quantum group associated with a classical Lie algebra, we construct a noncommutative associative algebra whose underlying vector…

Quantum Algebra · Mathematics 2015-05-13 G. I. Lehrer , Hechun Zhang , R. B. Zhang

We propose a general scheme for the "logic" of elementary propositions of physical systems, encompassing both classical and quantum cases, in the framework given by Non Commutative Geometry. It involves Baire*-algebras, the non-commutative…

Quantum Physics · Physics 2007-05-23 P. A. Marchetti , R. Rubele

We establish a general semiparametric Bernstein-von Mises theorem for Bayesian nonparametric priors based on continuous observations in a periodic reversible multidimensional diffusion model. We consider a wide range of functionals…

Statistics Theory · Mathematics 2025-05-23 Matteo Giordano , Kolyan Ray

The classical Bayesian posterior arises naturally as the unique solution of several different optimization problems, without the necessity of interpreting data as conditional probabilities and then using Bayes' Theorem. For example, the…

Statistics Theory · Mathematics 2012-03-02 Theodore P. Hill , Marco Dall'Aglio

Bayes' rule plays a crucial piece of logical inference in information and physical sciences alike. Its extension into the quantum regime has been the object of several recent works. These quantum versions of Bayes' rule have been expressed…

Quantum Physics · Physics 2023-06-29 Clive Cenxin Aw , Kelvin Onggadinata , Dagomir Kaszlikowski , Valerio Scarani

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over…

Statistical Mechanics · Physics 2009-10-31 J. C. Lemm , J. Uhlig , A. Weiguny

As a compact representation of joint probability distributions over a dependence graph of random variables, and a tool for modelling and reasoning in the presence of uncertainty, Bayesian networks are of great importance for artificial…

Quantum Physics · Physics 2020-10-06 Michael de Oliveira , Luis Soares Barbosa

We show that conditional expectations, optimal hypotheses, disintegrations, and adjoints of unital completely positive maps, are all instances of Bayesian inverses. We study the existence of the latter by means of the Tomita-Takesaki…

Operator Algebras · Mathematics 2023-09-28 Luca Giorgetti , Arthur J. Parzygnat , Alessio Ranallo , Benjamin P. Russo

Bayesian inference provides a rigorous framework to encapsulate our knowledge and uncertainty regarding various physical quantities in a well-defined and self-contained manner. Utilising modern tools, such Bayesian models can be constructed…

High Energy Physics - Lattice · Physics 2024-01-02 Julien Frison

We define E-theory for separable C*-algebras over second countable topological spaces and establish its basic properties. This includes an approximation theorem that relates the E-theory over a general space to the E-theories over finite…

K-Theory and Homology · Mathematics 2015-10-23 Marius Dadarlat , Ralf Meyer

In this work a quantum analogue of Bayesian inference is considered. Based on the notion of instrument, we propose a quantum analogue of Bayes' rule, which elaborates how a prior normal state updates under observations. Besides, we…

Quantum Physics · Physics 2023-01-10 Huayu Liu

In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. In the form of conditional expectation the Bayesian update…

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