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Probability densities that are not uniquely determined by their moments are said to be "moment-indeterminate", or "M-indeterminate". Determining whether or not a density is M-indeterminate, or how to generate an M-indeterminate density, is…

Quantum Physics · Physics 2021-07-28 Rafael Sala Mayato , Patrick Loughlin , Leon Cohen

In the operator formalism of quantum mechanics, the density operator describes the complete statistics of a quantum state in terms of d^2 independent elements, where d is the number of possible outcomes for a precise measurement of an…

Quantum Physics · Physics 2014-09-30 Holger F. Hofmann

We study a subclass of POMDPs, called Deterministic POMDPs, that is characterized by deterministic actions and observations. These models do not provide the same generality of POMDPs yet they capture a number of interesting and challenging…

Artificial Intelligence · Computer Science 2012-05-14 Blai Bonet

We study the existence of densities for distributions of piecewise deterministic Markov processes. We also obtain relationships between invariant densities of the continuous time process and that of the process observed at jump times. In…

Probability · Mathematics 2020-06-03 Piotr Gwiżdż , Marta Tyran-Kamińska

Using a probabilistic approach, we derive some interesting combinatorial identities involving gamma and beta functions. These results generalize certain well-known combinatorial identities involving binomial coefficients and special…

Probability · Mathematics 2026-05-15 Palaniappan Vellaisamy , Puja Pandey

Based on a recent proof of free choices in linking equations to the experiments they describe, I clarify relations among some purely mathematical entities featured in quantum mechanics (probabilities, density operators, partial traces, and…

Quantum Physics · Physics 2014-09-15 John M. Myers

The density operator of a quantum state can be represented as a complex joint probability of any two observables whose eigenstates have non-zero mutual overlap. Transformations to a new basis set are then expressed in terms of complex…

Quantum Physics · Physics 2012-04-26 Holger F. Hofmann

We study the uncertainties of quantum mechanical observables, quantified by the standard deviation (square root of variance) in Haar-distributed random pure states. We derive analytically the probability density functions (PDFs) of the…

Quantum Physics · Physics 2022-07-22 Lin Zhang , Jinping Huang , Jiamei Wang , Shao-Ming Fei

Using a probabilistic approach, we derive several interesting identities involving beta functions. Our results generalize certain well-known combinatorial identities involving binomial coefficients and gamma functions.

Combinatorics · Mathematics 2017-09-29 P. Vellaisamy , A. Zeleke

The determination of a quantum observable from the first and second moments of its measurement outcome statistics is investigated. Operational conditions for the moments of a probability measure are given which suffice to determine the…

Quantum Physics · Physics 2010-10-19 Pekka Lahti , Juha-Pekka Pellonpaa , Kari Ylinen

The uniqueness question of the multivariate moment problem is studied by different methods: Hilbert space operators, complex function theory, polynomial approximation, disintegration, integral geometry. Most of the known results in the…

Functional Analysis · Mathematics 2008-10-07 Mihai Putinar , Konrad Schmüdgen

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

Density functional theory offers a very accurate way of computing materials properties from first principles. However, it is too expensive for modelling large-scale molecular systems whose properties are, in contrast, computed using…

Computational Physics · Physics 2016-12-12 Alexander V. Shapeev

We prove that certain quotients of entire functions are characteristic functions. Under some conditions, the probability measure corresponding to a characteristic function of that type has a density which can be expressed as a generalized…

Probability · Mathematics 2010-09-09 Albert Ferreiro-Castilla , Frederic Utzet

The quantum mechanical probability densities are compared with the probability densities treated by the theory of random variables. The relevance of their difference for the interpretation of quantum mechanics is commented.

Quantum Physics · Physics 2008-04-28 Alberto C. de la Torre

We study the probability assignment for the outcomes of time-extended measurements. We construct the class-operator that incorporates the information about a generic time-smeared quantity. These class-operators are employed for the…

Quantum Physics · Physics 2015-06-26 C. Anastopoulos , N. Savvidou

In mathematical finance and other applications of stochastic processes, it is frequently the case that the characteristic function may be known but explicit forms for density functions are not available. The simulation of any distribution…

Computational Finance · Quantitative Finance 2009-03-10 William T. Shaw , Jonathan McCabe

By using path integrals, the stochastic process associated to the time evolution of the quantum probability density is formally rewritten in terms of a stochastic differential equation, given by Newton's equation of motion with an…

Quantum Physics · Physics 2018-01-04 Marco Patriarca

A parametrization of density operators for bipartite quantum systems is proposed. It is based on the particular parametrization of the unitary group found recently by Jarlskog. It is expected that this parametrization will find interesting…

Quantum Physics · Physics 2009-10-20 Erwin Bruening , Dariusz Chruscinski , Francesco Petruccione

Probabilistic conditioning is concerned with the identification of a distribution of a random variable $X$ given a random variable $Y$. It is a cornerstone of scientific and engineering applications where modeling uncertainty is key. This…

Machine Learning · Statistics 2026-05-13 Panos Tsimpos , Edoardo Calvello , Ayoub Belhadji , Nicholas H. Nelsen
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