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Bell inequalities or Bell-like experiments are supposed to test hidden variable theories based on three intuitive assumptions: determinism, locality and measurement independence. If one of the assumptions of Bell inequality is properly…

Quantum Physics · Physics 2018-04-19 R. Rossi , Leonardo A. M. Souza

On one side, so far a great part of the evidence accepted as proof of the alleged quantum non-locality relied on inhomogeneous Bell inequalities involving an additional assumption (no-enhancement) whose role had not been sufficiently…

Mathematical Physics · Physics 2015-03-19 David Rodríguez

In this Letter, we explore the possibility of developing Bell inequalities predicated on models using a single Local Hidden Variable (s-LHV), a strict subset of general LHV models. Because of the less strenuous constraints imposed by s-LHV…

Quantum Physics · Physics 2017-03-02 James Schneeloch , Christopher C. Tison , Paul M. Alsing

Citation and coauthor networks offer an insight into the dynamics of scientific progress. We can also view them as representations of a causal structure, a logical process captured in a graph. From a causal perspective, we can ask questions…

Digital Libraries · Computer Science 2016-12-09 Peter Wittek , Sándor Darányi , Gustaf Nelhans

Hidden variable graphical models can sometimes imply constraints on the observable distribution that are more complex than simple conditional independence relations. These observable constraints can falsify assumptions of the model that…

Methodology · Statistics 2026-05-12 Michael C. Sachs , Erin E. Gabriel , Robin J. Evans , Arvid Sjölander

We introduce Bell inequalities based on covariance, one of the most common measures of correlation. Explicit examples are discussed, and violations in quantum theory are demonstrated. A crucial feature of these covariance Bell inequalities…

Quantum Physics · Physics 2017-12-27 Victor Pozsgay , Flavien Hirsch , Cyril Branciard , Nicolas Brunner

We consider general settings of Bell inequality experiments with many parties, where each party chooses from a finite number of measurement settings each with a finite number of outcomes. We investigate the constraints that Bell…

Quantum Physics · Physics 2015-03-19 Matty J. Hoban , Joel J. Wallman , Dan E. Browne

It is shown that the Bell inequalities are closely related to the triangle inequalities involving distance functions amongst pairs of random variables with values $\left\{ 0,1\right\} $. A hidden variables model may be defined as a mapping…

Quantum Physics · Physics 2016-09-28 Emilio Santos

Quantum theory is inconsistent with any local hidden variable model as was first shown by Bell. To test Bell inequalities two separated observers extract correlations from a common ensemble of identical systems. Since quantum theory does…

Quantum Physics · Physics 2011-01-19 Shmuel Marcovitch , Benni Reznik

Quantum correlations that violate the Bell inequality cannot be explained by any (measurement independent) local hidden variable theory. However, the violation only implies incompatibility of the underlying assumptions of reality, locality,…

Quantum Physics · Physics 2024-12-30 Gen Kimura , Yugo Susuki , Kei Morisue

An experiment is described which proves, using single photons only, that the standard hidden variables assumptions (commonly used to derive Bell inequalities) are inconsistent with quantum mechanics. The analysis is very simple and…

Quantum Physics · Physics 2007-06-22 Arnold Neumaier

The Bell inequality is thought to be a common constraint shared by all models of local hidden variables that aim to describe the entangled states of two qubits. Since the inequality is violated by the quantum mechanical description of these…

General Physics · Physics 2020-08-05 David H. Oaknin

Deep latent variable models learn condensed representations of data that, hopefully, reflect the inner workings of the studied phenomena. Unfortunately, these latent representations are not statistically identifiable, meaning they cannot be…

Machine Learning · Statistics 2025-06-02 Stas Syrota , Yevgen Zainchkovskyy , Johnny Xi , Benjamin Bloem-Reddy , Søren Hauberg

Bell inequalities rely on an assumption that the probabilities of adopting configurations of hidden variables describing a system prior to measurement are independent of the choice of measured physical property, also known as measurement…

Quantum Physics · Physics 2025-09-05 Sophia M. Walls , Ian J. Ford

A semi-parametric, non-linear regression model in the presence of latent variables is introduced. These latent variables can correspond to unmodeled phenomena or unmeasured agents in a complex networked system. This new formulation allows…

Machine Learning · Statistics 2018-06-29 Jonathan Mei , José M. F. Moura

Hierarchical learning models, such as mixture models and Bayesian networks, are widely employed for unsupervised learning tasks, such as clustering analysis. They consist of observable and hidden variables, which represent the given data…

Machine Learning · Statistics 2018-01-08 Keisuke Yamazaki

Bell inequalities constitute a key tool in quantum information theory: they not only allow one to reveal nonlocality in composite quantum systems, but, more importantly, they can be used to certify relevant properties thereof. We provide a…

Quantum Physics · Physics 2020-01-22 F. Baccari , R. Augusiak , I. Šupić , J. Tura , A. Acín

We discuss models that attempt to provide an explanation for the violation of Bell inequalities at a distance in terms of hidden influences. These models reproduce the quantum correlations in most situations, but are restricted to produce…

Quantum Physics · Physics 2014-10-20 Valerio Scarani , Jean-Daniel Bancal , Antoine Suarez , Nicolas Gisin

Violation of Bell inequality (or, Bell-type inequalities) by nonlocal correlations is justified by relaxation of at least one of the plausible physical constraints used to model such inequality. Based on this fact, in this letter we present…

Quantum Physics · Physics 2015-12-31 Biswajit Paul , Kaushiki Mukherjee , Debasis Sarkar

A semi-parametric, non-linear regression model in the presence of latent variables is applied towards learning network graph structure. These latent variables can correspond to unmodeled phenomena or unmeasured agents in a complex system of…

Machine Learning · Statistics 2018-07-03 Jonathan Mei , José M. F. Moura
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