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Classical machine learning models struggle with learning and prediction tasks on data sets exhibiting long-range correlations. Previously, the existence of a long-range correlational structure known as contextuality was shown to inhibit…

Quantum Physics · Physics 2026-04-28 Mariesa H. Teo , Willers Yang , James Sud , Teague Tomesh , Frederic T. Chong , Eric R. Anschuetz

Measurement incompatibility stipulates the existence of quantum measurements that cannot be carried out simultaneously on single systems. We show that the set of input-output probabilities obtained from d-dimensional classical systems…

Quantum Physics · Physics 2023-06-13 Debashis Saha , Debarshi Das , Arun Kumar Das , Bihalan Bhattacharya , A. S. Majumdar

Investigating the relationships between two sets of variables helps to understand their interactions and can be done with canonical correlation analysis (CCA). However, the correlation between the two sets can sometimes depend on a third…

Contextuality, a key resource for quantum advantage, describes systems in which the outcome of a measurement is not independent of other compatible measurements, in contrast to classical hidden-variable descriptions. We investigate the…

Quantum Physics · Physics 2025-12-08 Caroline Lima , María Rosa Preciado-Rivas , Sanchit Srivastava

The claim that there is an inconsistency of quantum-classical dynamics [1] is investigated. We point out that a consistent formulation of quantum and classical dynamics which can be used to describe quantum measurement processes is already…

Quantum Physics · Physics 2007-05-23 E. C. G. Sudarshan

A stream of conscious experience is extremely contextual; it is impacted by sensory stimuli, drives and emotions, and the web of associations that link, directly or indirectly, the subject of experience to other elements of the individual's…

Neurons and Cognition · Quantitative Biology 2013-10-30 Diederik Aerts , Jan Broekaert , Liane Gabora

Contextuality is a fundamental feature of quantum theory and is necessary for quantum computation and communication. Serious steps have therefore been taken towards a formal framework for contextuality as an operational resource. However,…

Quantum Physics · Physics 2018-04-26 Barbara Amaral , Adán Cabello , Marcelo Terra Cunha , Leandro Aolita

We unify the resource-theoretic and the cohomological perspective on quantum contextuality. At the center of this unification stands the notion of the contextual fraction. For both symmetry and parity based contextuality proofs, we…

Quantum Physics · Physics 2018-06-13 Cihan Okay , Emily Tyhurst , Robert Raussendorf

We address the issue of coupling variables which are essentially classical to variables that are quantum. Two approaches are discussed. In the first (based on collaborative work with L.Di\'osi), continuous quantum measurement theory is used…

General Relativity and Quantum Cosmology · Physics 2009-10-31 J. J. Halliwell

Quantum contextuality is the key concept which explains the fact that the result of a measurement is not independent of the context in which it is found. It is observed to be an intrinsic feature, i.e., neither entanglement nor spatial…

Quantum Physics · Physics 2023-02-23 Firat Diker , Zafer Gedik

We show that including both the system and the apparatus in the quantum description of the measurement process, and using the concept of conditional probabilities, it is possible to deduce the statistical operator of the system after a…

Quantum Physics · Physics 2008-11-29 R. Laura , L. Vanni

Despite the empirical success of foundation models, we do not have a systematic characterization of the representations that these models learn. In this paper, we establish the contexture theory. It shows that a large class of…

Machine Learning · Computer Science 2025-05-06 Runtian Zhai , Kai Yang , Che-Ping Tsai , Burak Varici , Zico Kolter , Pradeep Ravikumar

We show that the dynamics of a quantum system can be represented by the dynamics of an underlying classical systems obeying the Hamilton equations of motion. This is achieved by transforming the phase space of dimension $2n$ into a Hilbert…

Statistical Mechanics · Physics 2023-08-02 Mário j. de Oliveira

We consider deep multivariate models for heterogeneous collections of random variables. In the context of computer vision, such collections may e.g. consist of images, segmentations, image attributes, and latent variables. When developing…

Machine Learning · Computer Science 2026-02-03 Dmitrij Schlesinger , Boris Flach , Alexander Shekhovtsov

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

The concept of randomized measurements on individual particles has proven to be useful for analyzing quantum systems and is central for methods like shadow tomography of quantum states. We introduce $\textit{collective}$ randomized…

Quantum Physics · Physics 2024-08-12 Satoya Imai , Géza Tóth , Otfried Gühne

Document ranking based on probabilistic evaluations of relevance is known to exhibit non-classical correlations, which may be explained by admitting a complex structure of the event space, namely, by assuming the events to emerge from…

Information Retrieval · Computer Science 2012-05-28 Roman Zapatrin

We show, under natural assumptions for qubit systems, that measurement-based quantum computations (MBQCs) which compute a non-linear Boolean function with high probability are contextual. The class of contextual MBQCs includes an example…

Quantum Physics · Physics 2013-08-28 Robert Raussendorf

The frame of classical probability theory can be generalized by enlarging the usual family of random variables in order to encompass nondeterministic ones: this leads to a frame in which two kinds of correlations emerge: the classical…

Quantum Physics · Physics 2007-05-23 E. G. Beltrametti , S. Bugajski

Modern language models represent probability distributions over character strings as distributions over (shorter) token strings derived via a deterministic tokenizer, such as byte-pair encoding. While this approach is highly effective at…