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Contextuality is a natural generalization of nonlocality which does not need composite systems or spacelike separation and offers a wider spectrum of interesting phenomena. Most notably, in quantum mechanics there exist scenarios where the…

Quantum Physics · Physics 2022-03-16 Matthias Kleinmann , Costantino Budroni , Jan-Åke Larsson , Otfried Gühne , Adan Cabello

We examine the logical structure of the emergence of classical stochasticity for a quantum system governed by a Pauli-type master equation. It is well-known that while such equations describe the evolution of probabilities, they do not…

Quantum Physics · Physics 2026-02-05 Xuan Du Trinh , Ismaël Septembre , Hai-Chau Nguyen

Three events in a probability space form a conjunctive fork if they satisfy specific constraints on conditional independence and covariances. Patterns of conjunctive forks within collections of events are characterized by means of systems…

Probability · Mathematics 2016-08-30 Vašek Chvátal , František Matúš , Yori Zwólš

In a previous paper, a process algebra based on ACP (Algebra of Communicating Processes) was proposed in which processes involving data can be handled by means of features originating from imperative programming. In this paper, an extension…

Logic in Computer Science · Computer Science 2026-05-19 C. A. Middelburg

We derive multiparty games that, if the winning chance exceeds a certain limit, prove the incompatibility of the parties' causal relations with any partial order. This, in turn, means that the parties exert a back-action on the causal…

General Relativity and Quantum Cosmology · Physics 2025-05-15 Eleftherios-Ermis Tselentis , Ämin Baumeler

Causal multiteam semantics is a framework where probabilistic dependencies arising from data and causation between variables can be together formalized and studied logically. We consider several logics in the setting of causal multiteam…

Logic in Computer Science · Computer Science 2023-03-22 Fausto Barbero , Jonni Virtema

Following on from the notion of (first-order) causality, which generalises the notion of being tracepreserving from CP-maps to abstract processes, we give a characterization for the most general kind of map which sends causal processes to…

Other Computer Science · Computer Science 2017-01-04 Aleks Kissinger , Sander Uijlen

The well-defined but intricate course of time evolution exhibited by many naturally occurring phenomena suggests some source of dynamic order sustaining it. In spite of its obviousness as a problem, it has remained absent from the…

Adaptation and Self-Organizing Systems · Physics 2021-03-02 R. Herrero , J. Farjas , F. Pi , G. Orriols

Over the past decade, a number of quantum processes have been proposed which are logically consistent, yet feature a cyclic causal structure. However, there is no general formal method to construct a process with an exotic causal structure…

Quantum Physics · Physics 2025-12-03 Augustin Vanrietvelde , Nick Ormrod , Hlér Kristjánsson , Jonathan Barrett

Contextuality is a particular quantum phenomenon that has no analogue in classical probability theory. Given two independent systems, a natural question is how to represent such a situation as a single test space. In other words, how…

Quantum Physics · Physics 2018-12-24 Ana Belén Sainz , Elie Wolfe

Correlations between spacelike separated measurements on entangled quantum systems are stronger than any classical correlations and are at the heart of numerous quantum technologies. In practice, however, spacelike separation is often not…

Quantum Physics · Physics 2017-11-28 Martin Ringbauer , Rafael Chaves

We demonstrate the possibility of classifying causal systems into kinds that share a common structure without first constructing an explicit dynamical model or using prior knowledge of the system dynamics. The algorithmic ability to…

Machine Learning · Statistics 2016-12-16 Benjamin C. Jantzen

The transition from classical to quantum mechanics rests on the recognition that the structure of information is not what we thought it was: there are operational, i.e., phenomenal, probabilistic correlations that lie outside the polytope…

Quantum Physics · Physics 2015-06-11 Jeffrey Bub

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time M and continuous wave function arise…

Mathematical Physics · Physics 2015-06-19 William Sulis

An order parameter, termed the maximal row correlation, is proposed for classical spin systems. Monte Carlo simulations on various Potts models suggest that this order parameter is applicable to a broad range of spin systems, including…

Statistical Mechanics · Physics 2025-09-18 Yong-Yi Tang , Yin Zhong , Hantao Lu

We study the notion of causal orders for the cases of (classical and quantum) circuits and spacetime events. We show that every circuit can be immersed into a classical spacetime, preserving the compatibility between the two causal…

Quantum Physics · Physics 2020-06-08 Nikola Paunkovic , Marko Vojinovic

There is a received wisdom about where to draw the boundary between classical and nonclassical for various types of quantum processes. For multipartite states, it is the divide between separable and entangled; for channels, the divide…

Quantum Physics · Physics 2026-01-28 Yujie Zhang , David Schmid , Yìlè Yīng , Robert W. Spekkens

Figuring out the physical rationale behind natural selection of quantum theory is one of the most acclaimed quests in quantum foundational research. This pursuit has inspired several axiomatic initiatives to derive mathematical formulation…

Continuous observation of a quantum system yields a measurement record that faithfully reproduces the classically predicted trajectory provided that the measurement is sufficiently strong to localize the state in phase space but weak enough…

Quantum Physics · Physics 2007-05-23 Shohini Ghose , Paul Alsing , Ivan Deutsch , Tanmoy Bhattacharya , Salman Habib , Kurt Jacobs

Predicting the future is an important component of decision making. In most situations, however, there is not enough information to make accurate predictions. In this paper, we develop a theory of causal reasoning for predictive inference…

Artificial Intelligence · Computer Science 2013-04-10 Thomas L. Dean , Keiji Kanazawa
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