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Related papers: Causality in Dense Matter

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Causal discovery problems use a set of observations to deduce causality between variables in the real world, typically to answer questions about biological or physical systems. These observations are often recorded at regular time…

Signal Processing · Electrical Eng. & Systems 2026-02-24 Kurt Butler , Damian Machlanski , Panagiotis Dimitrakopoulos , Sotirios A. Tsaftaris

This paper presents an brief review of some recent work on the causal set approach to quantum gravity. Causal sets are a discretisation of spacetime that allow the symmetries of GR to be preserved in the continuum approximation. One…

General Relativity and Quantum Cosmology · Physics 2010-03-31 Joe Henson

We describe the interface between measure theoretic probability and causal inference by constructing causal models on probability spaces within the potential outcomes framework. We find that measure theory provides a precise and instructive…

Statistics Theory · Mathematics 2019-07-04 Irineo Cabreros , John D. Storey

We present an overview of the decision-theoretic framework of statistical causality, which is well-suited for formulating and solving problems of determining the effects of applied causes. The approach is described in detail, and is related…

Statistics Theory · Mathematics 2020-04-28 A. Philip Dawid

The scattering matrix which describes low-energy, non-relativistic scattering of spin-1/2 fermions interacting via finite-range potentials can be obtained from a geometric action principle in which space and time do not appear explicitly…

Quantum Physics · Physics 2022-04-13 Silas R. Beane , Roland C. Farrell

A physical theory of experiments carried out in a space-time region can accommodate a detector localized in another space-like separated region, in three, not necessarily exclusive, ways: 1) the detector formally collapses physical states…

Quantum Physics · Physics 2007-05-23 George Svetlichny

A usual causal requirement on a viable theory of matter is that the speed of sound be at most the speed of light. In view of various recent papers querying this limit, the question is revisited here. We point to various issues confronting…

General Relativity and Quantum Cosmology · Physics 2008-11-26 George Ellis , Roy Maartens , Malcolm MacCallum

We provide theoretical and empirical evidence for a type of asymmetry between causes and effects that is present when these are related via linear models contaminated with additive non-Gaussian noise. Assuming that the causes and the…

Machine Learning · Statistics 2016-02-23 Daniel Hernández-Lobato , Pablo Morales-Mombiela , David Lopez-Paz , Alberto Suárez

Deep Learning models have shown success in a large variety of tasks by extracting correlation patterns from high-dimensional data but still struggle when generalizing out of their initial distribution. As causal engines aim to learn…

Machine Learning · Computer Science 2024-01-02 Gaël Gendron , Michael Witbrock , Gillian Dobbie

Causality is one of the most fundamental -- and yet elusive -- concepts in physics. From its intuitive role in everyday experience to its formal and often implicit role in scientific theories, causality has challenged philosophers and…

Popular Physics · Physics 2026-01-05 Alessandro De Angelis

The fundamental theories of physics are local theories, depending on local interactions of local variables. It is not clear if and how strictly local theories can produce non-local variables that have causal effectiveness. Yet, non-local…

Adaptation and Self-Organizing Systems · Physics 2015-11-06 J. H. van Hateren

Using symmetric boundary conditions at separated times, I show analytically that both the time ordering of (macroscopic) causality and the direction of entropy increase follow from these boundary conditions. In particular, when the…

Statistical Mechanics · Physics 2007-05-23 L. S. Schulman

We describe and contrast two distinct problem areas for statistical causality: studying the likely effects of an intervention ("effects of causes"), and studying whether there is a causal link between the observed exposure and outcome in an…

Statistics Theory · Mathematics 2021-04-02 A. Philip Dawid , Monica Musio

I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers Kronig relations. The specification of causality in terms of temporal differential eqations then shows us the way to write down dynamical…

Classical Physics · Physics 2018-06-04 Paul Kinsler

The controversy between relativistic causality and quantum non-locality can be resolved by establishing the general relativistic background of quantum non-locality.

General Relativity and Quantum Cosmology · Physics 2007-05-23 Erast B. Gliner

We propose a new definition of actual causes, using structural equations to model counterfactuals.We show that the definitions yield a plausible and elegant account ofcausation that handles well examples which have caused problems forother…

Artificial Intelligence · Computer Science 2013-01-14 Joseph Y. Halpern , Judea Pearl

We develop a theoretical model to investigate wave propagation in media with random time-varying properties, where temporal fluctuations lead to complex scattering dynamics. Focusing on the ensemble-averaged field, we derive an exact…

Optics · Physics 2026-02-24 Romain Pierrat , Julia Rocha , Rémi Carminati

This survey paper covers the breadth and depth of time-series and spatiotemporal causality methods, and their applications in Earth Science. More specifically, the paper presents an overview of causal discovery and causal inference,…

Data Analysis, Statistics and Probability · Physics 2024-09-04 Sahara Ali , Uzma Hasan , Xingyan Li , Omar Faruque , Akila Sampath , Yiyi Huang , Md Osman Gani , Jianwu Wang

Signal causality, the prohibition of superluminal information transmission, is the fundamental property shared by quantum measurement theory and relativity, and it is the key to understanding the connection between nonlocal measurement…

Quantum Physics · Physics 2011-07-05 Edward J. Gillis

Probabilities of causation are fundamental to individual-level explanation and decision making, yet they are inherently counterfactual and not point-identifiable from data in general. Existing bounds either disregard available covariates,…

Artificial Intelligence · Computer Science 2026-02-17 Yuxuan Xie , Ang Li