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We show how to formulate physical theory taking as a starting point the set of states (geometric approach). We discuss the relation of this formulation to the conventional approach to classical and quantum mechanics and the theory of…

Quantum Physics · Physics 2021-11-24 Albert Schwarz

Many statistical models are algebraic in that they are defined by polynomial constraints or by parameterizations that are polynomial or rational maps. This opens the door for tools from computational algebraic geometry. These tools can be…

Statistics Theory · Mathematics 2007-06-13 Mathias Drton

The aim of the paper is to propose geometric descriptions of multipartite entangled states using algebraic geometry. In the context of this paper, geometric means each stratum of the Hilbert space, corresponding to an entangled state, is an…

Mathematical Physics · Physics 2013-02-12 Frédéric Holweck , Jean-Gabriel Luque , Jean-Yves Thibon

We consider optimal state discrimination in a general convex operational framework, so-called generalized probabilistic theories (GPTs), and present a general method of optimal discrimination by applying the complementarity problem from…

Quantum Physics · Physics 2017-07-11 Joonwoo Bae , D. -G. Kim , Leong-Chuan Kwek

The purpose of this paper is to build a new bridge between category theory and a generalized probability theory known as noncommutative probability or quantum probability, which was originated as a mathematical framework for quantum theory,…

Category Theory · Mathematics 2021-09-07 Hayato Saigo

Generalized coherent states for shape invariant potentials are constructed using an algebraic approach based on supersymmetric quantum mechanics. We show this generalized formalism is able to: a) supply the essential requirements necessary…

Quantum Physics · Physics 2008-11-26 A. N. F. Aleixo , A. B. Balantekin

We propose a novel algebraic framework for treating probability distributions represented by their cumulants such as the mean and covariance matrix. As an example, we consider the unsupervised learning problem of finding the subspace on…

In this review article we present different formal frameworks for the description of generalized probabilities in statistical theories. We discuss the particular cases of probabilities appearing in classical and quantum mechanics, possible…

Other Statistics · Statistics 2021-08-04 F. Holik , C. Massri , A. Plastino , M. Sáenz

Mathematical descriptions of dynamical systems are deeply rooted in topological spaces defined by non-Euclidean geometry. This paper proposes leveraging structure-rich geometric spaces for machine learning to achieve structural…

Machine Learning · Computer Science 2025-02-20 Zack Xuereb Conti , David J Wagg , Nick Pepper

We review a geometric approach to classification and examination of quantum correlations in composite systems. Since quantum information tasks are usually achieved by manipulating spin and alike systems or, in general, systems with a finite…

Quantum Physics · Physics 2019-03-27 A. Sawicki , T. Maciążek , M. Oszmaniec , K. Karnas , K. Kowalczyk-Murynka , M. Kuś

We consider a geometrization, i.e., we identify geometrical structures, for the space of density states of a quantum system. We also provide few comments on a possible application of this geometrization for composite systems.

Quantum Physics · Physics 2009-11-11 V. I. Man'ko , G. Marmo , E. C. G. Sudarshan , F. Zaccaria

It is usually believed that a picture of Quantum Mechanics in terms of true probabilities cannot be given due to the uncertainty relations. Here we discuss a tomographic approach to quantum states that leads to a probability representation…

Quantum Physics · Physics 2007-05-23 Michele Caponigro , Stefano Mancini , Vladimir I. Man'ko

Algebras of generalized functions offer possibilities beyond the purely distributional approach in modelling singular quantities in non-smooth differential geometry. This article presents an introductory survey of recent developments in…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger

We introduce the framework of general probabilistic theories (GPTs for short). GPTs are a class of operational theories that generalize both finite-dimensional classical and quantum theory, but they also include other, more exotic theories,…

Quantum Physics · Physics 2023-10-27 Martin Plávala

The principal goal of this paper is to pass all quantum probability formulas to the projective space associated to the complex Hilbert space of a given quantum system, providing a more complete geometrization of quantum theory. Quantum…

Quantum Physics · Physics 2025-02-18 Stephen Bruce Sontz

`Hypergeometric states', which are a one-parameter generalization of binomial states of the single-mode quantized radiation field, are introduced and their nonclassical properties are investigated. Their limits to the binomial states and to…

Quantum Physics · Physics 2008-11-26 Hong-Chen Fu , Ryu Sasaki

General Probabilistic Theories provide the most general mathematical framework for the theory of probability in an operationally natural manner, and generalize classical and quantum theories. In this article, we study state-discrimination…

Quantum Physics · Physics 2010-09-15 Koji Nuida , Gen Kimura , Takayuki Miyadera

Algebro-geometric methods have proven to be very successful in the study of graphical models in statistics. In this paper we introduce the foundations to carry out a similar study of their quantum counterparts. These quantum graphical…

Algebraic Geometry · Mathematics 2023-08-23 Eliana Duarte , Dmitrii Pavlov , Maximilian Wiesmann

We provide a physical prescription based on interferometry for introducing the total phase of a mixed state undergoing unitary evolution, which has been an elusive concept in the past. We define the parallel transport condition that…

Understanding the macroscopic characteristics of biological complexes demands precision and specificity in statistical ensemble modeling. One of the primary challenges in this domain lies in sampling from particular subsets of the…

Machine Learning · Computer Science 2023-07-11 Justin Diamond , Markus Lill
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