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Related papers: Negative Probability

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Negative probabilities emerged at intermediate steps in various attempts to predict the distributions of quantum interference. There is no consensus on their meaning yet. It has been suggested (Khrennikov, 1998) that negative probabilities…

General Physics · Physics 2012-06-26 Ghenadie N. Mardari

Motivated by real-world situations found in high energy particle physics, we consider a generalisation of the likelihood-ratio estimation task to a quasiprobabilistic setting where probability densities can be negative. By extension, this…

Machine Learning · Statistics 2024-10-15 Matthew Drnevich , Stephen Jiggins , Judith Katzy , Kyle Cranmer

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of…

Probability · Mathematics 2013-06-06 Mark Burgin

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability…

Methodology · Statistics 2013-10-15 Mingyuan Zhou , Lawrence Carin

We explain, on the example of Wigner's quasiprobability distribution, how negative probabilities may be used in the foundations of probability.

Quantum Physics · Physics 2020-11-26 Yuri Gurevich , Vladimir Vovk

This article was written for the Logic in Computer Science column in the February 2015 issue of the Bulletin of the European Association for Theoretical Computer Science. The intended audience is general computer science audience. The…

Quantum Physics · Physics 2015-02-04 Andreas Blass , Yuri Gurevich

In this article, a generalized version of Negative binomial-beta exponential distribution with five parameters have been introduced. Some interesting submodels have been derived from it. A comprehensive mathematical treatment of proposed…

Statistics Theory · Mathematics 2019-05-31 Anwar Hassan , Ishfaq Shah Ahmad , Peer Bilal Ahmad

Here we briefly discuss how negative numbers, or "negative probabilities", can naturally arise in probabilistic expressions and be given an operational interpretation. Like the use of negative numbers in arithmetical expressions, the use of…

Statistical Mechanics · Physics 2019-06-14 John Realpe-Gómez

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions can be seen as a special case when the density matrix is restricted to be…

Quantum Physics · Physics 2009-01-12 Manfred K Warmuth , Dima Kuzmin

In this paper we attempt to establish a theory of negative (quasi) probability distributions from fundamental principles and apply it to the study of the double-slit experiment in quantum mechanics. We do so in a way that preserves the main…

Quantum Physics · Physics 2014-12-17 J. Acacio de Barros , Gary Oas , Patrick Suppes

In this paper one generalizes the classical probability and imprecise probability to the notion of "neutrosophic probability" in order to be able to model Heisenberg's Uncertainty Principle of a particle's behavior, Schr"dinger's Cat…

General Mathematics · Mathematics 2007-05-23 Florentin Smarandache

Negative probabilities have long been discussed in connection with the foundations of quantum mechanics. We have recently shown that, if signed measures are allowed on the hidden variables, the class of probability models which can be…

Quantum Physics · Physics 2014-07-16 Samson Abramsky , Adam Brandenburger

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions are a special case where the density matrix is restricted to be diagonal. Density…

Quantum Physics · Physics 2014-08-14 Manfred K. Warmuth , Dima Kuzmin

The negative binomial distribution has been widely used as a more flexible model than the Poisson distribution for count data. However, when the true data-generating process is Poisson, it is often challenging to distinguish it from a…

Statistics Theory · Mathematics 2026-04-07 Yingying Yang , Niloufar Dousti Mousavi , Zhou Yu , Jie Yang

Polarization quasiprobability distribution defined in the Stokes space shares many important properties with the Wigner function for the position and momentum. Most notably, they both give correct one-dimensional marginal probability…

Quantum Physics · Physics 2017-08-16 K. Yu. Spasibko , M. V. Chekhova , F. Ya. Khalili

The statistical inverse problem of estimating the probability distribution of an infinite-dimensional unknown given its noisy indirect observation is studied in the Bayesian framework. In practice, one often considers only…

Statistics Theory · Mathematics 2017-11-21 Sari Lasanen

The negative multinomial distribution is a multivariate generalization of the negative binomial distribution. In this paper, we consider the problem of estimating an unknown matrix of probabilities on the basis of observations of negative…

Statistics Theory · Mathematics 2020-10-30 Yasuyuki Hamura , Tatsuya Kubokawa

This note is sketching a simple and natural mathematical construction for explaining the probabilistic nature of quantum mechanics. It employs nonstandard analysis and is based on Feynman's interpretation of the Heisenberg uncertainty…

Quantum Physics · Physics 2007-06-13 Michel Fliess

Weak measurements of photon position can be used to obtain direct experimental evidence of the wavefunction of a photon between generation and ultimate detection. Significantly, these measurement results can also be understood as complex…

Quantum Physics · Physics 2014-06-11 Holger F. Hofmann

The emergent field of probabilistic numerics has thus far lacked clear statistical principals. This paper establishes Bayesian probabilistic numerical methods as those which can be cast as solutions to certain inverse problems within the…

Methodology · Statistics 2019-11-15 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami
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