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Different analytic notions of contextuality fall into two major groups: probabilistic and strong notions of contextuality. Kochen and Specker's Theorem~0 is a demarcation criterion for differentiating between those groups. Whereas…

Quantum Physics · Physics 2025-12-10 Karl Svozil

Contextuality provides a unifying paradigm for nonclassical aspects of quantum probabilities and resources of quantum information. Unfortunately, most forms of quantum contextuality remain experimentally unexplored due to the difficulty of…

Quantum Physics · Physics 2016-03-02 Adán Cabello

Recent work has proposed using Large Language Models (LLMs) to quantify narrative flow through a measure called sequentiality, which combines topic and contextual terms. A recent critique argued that the original results were confounded by…

Computation and Language · Computer Science 2025-11-13 Amal Sunny , Advay Gupta , Vishnu Sreekumar

We introduce a preparation-dual notion of contextuality, formulated as an obstruction to stochastic extension. In parallel with the sheaf-theoretic formulation of measurement contextuality, preparation contextuality arises when locally…

Quantum Physics · Physics 2026-05-05 Tom Williams , Mina Doosti , Farid Shahandeh

There has been a growing interest, both in physics and psychology, in understanding contextuality in experimentally observed quantities. Different approaches have been proposed to deal with contextual systems, and a promising one is…

Data Analysis, Statistics and Probability · Physics 2015-11-10 J. Acacio de Barros , Janne Kujala , Gary Oas

The amount of contextuality is quantified in terms of the probability of the necessary violations of noncontextual assignments to counterfactual elements of physical reality.

Quantum Physics · Physics 2012-03-21 Karl Svozil

This paper provides a bundle perspective to contextuality by introducing new categories of contextuality scenarios based on bundles of simplicial complexes and simplicial sets. The former approach generalizes earlier work on the…

Category Theory · Mathematics 2023-08-15 Rui Soares Barbosa , Aziz Kharoof , Cihan Okay

Generalisation in machine learning often relies on the ability to encode structures present in data into an inductive bias of the model class. To understand the power of quantum machine learning, it is therefore crucial to identify the…

Quantum Physics · Physics 2023-04-19 Joseph Bowles , Victoria J Wright , Máté Farkas , Nathan Killoran , Maria Schuld

Models of a phenomenon are often developed by examining it under different experimental conditions, or measurement contexts. The resultant probabilistic models assume that the underlying random variables, which define a measurable set of…

Artificial Intelligence · Computer Science 2018-02-05 Peter D. Bruza

Results of measurements give legitimacy to a physical theory. What if acquiring these results in the first place necessitates what the same theory considers to be an interaction? In this note, we assume that theories account for…

Quantum Physics · Physics 2019-05-01 Arne Hansen , Stefan Wolf

Contextuality describes the nontrivial dependence of measurement outcomes on particular choices of jointly measurable observables. In this work we review and generalize the bundle diagram representation introduced in [S. Abramsky et al.,…

Quantum Physics · Physics 2018-11-28 Kerstin Beer , Tobias J. Osborne

In this paper, following an elementary line of thought which somewhat differs from the usual one, we prove once more that any deterministic theory predictively equivalent to quantum mechanics unavoidably exhibits a contextual character. The…

Quantum Physics · Physics 2009-11-13 GianCarlo Ghirardi , Karl Wienand

The results of behavioral experiments typically exhibit inconsistent connectedness, i.e., they violate the condition known as "no-signaling," "no-disturbance," or "marginal selectivity." This prevents one from evaluating these experiments…

Neurons and Cognition · Quantitative Biology 2017-09-05 Víctor H. Cervantes , Ehtibar N. Dzhafarov

Contextuality is a fundamental property of quantum theory and a critical resource for quantum computation. Here, we experimentally observe the arguably cleanest form of contextuality in quantum theory [A. Cabello \emph{et al.}, Phys. Rev.…

Quantum Physics · Physics 2014-12-24 Breno Marques , Johan Ahrens , Mohamed Nawareg , Adan Cabello , Mohamed Bourennane

A large body of research in machine learning is concerned with supervised learning from examples. The examples are typically represented as vectors in a multi-dimensional feature space (also known as attribute-value descriptions). A teacher…

Machine Learning · Computer Science 2007-05-23 Peter D. Turney

In his constructive and well-informed commentary, Andrei Khrennikov acknowledges a privileged status of classical probability theory with respect to statistical analysis. He also sees advantages offered by the Contextuality-by-Default…

Quantum Physics · Physics 2018-12-14 Ehtibar N. Dzhafarov , Maria Kon

This paper introduces a novel approach to Generalized Category Discovery (GCD) by leveraging the concept of contextuality to enhance the identification and classification of categories in unlabeled datasets. Drawing inspiration from human…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Tingzhang Luo , Mingxuan Du , Jiatao Shi , Xinxiang Chen , Bingchen Zhao , Shaoguang Huang

The presence of contextuality in quantum theory was first highlighted by Bell, Kochen and Specker, who discovered that for quantum systems of three or more dimensions, measurements cannot be viewed as revealing pre-existing properties of…

Quantum Physics · Physics 2017-04-07 Andrew W. Simmons , Joel J. Wallman , Hakop Pashayan , Stephen D. Bartlett , Terry Rudolph

Contextuality is the failure of "local" probabilistic models to become global ones. In this paper we introduce the notions of \emph{measurable fibre bundles}, \emph{probability fibre bundles}, and \emph{sample fibre bundle} which capture…

Probability · Mathematics 2021-03-10 Marcelo Terra Cunha

Default logic encounters some conceptual difficulties in representing common sense reasoning tasks. We argue that we should not try to formulate modular default rules that are presumed to work in all or most circumstances. We need to take…

Artificial Intelligence · Computer Science 2013-02-08 Choh Man Teng