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Related papers: Causal Coverage in Ordered Locales and Spacetimes

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Using a process-theoretic formalism, we introduce the notion of a causal-inferential theory: a triple consisting of a theory of causal influences, a theory of inferences (of both the Boolean and Bayesian varieties), and a specification of…

Quantum Physics · Physics 2021-05-21 David Schmid , John H. Selby , Robert W. Spekkens

The goal of this work, motivated by the desire to understand causality in classical and quantum gravity, is an in depth investigation of causality in classical field theories with quasilinear equations of motion, of which General Relativity…

General Relativity and Quantum Cosmology · Physics 2012-11-13 Igor Khavkine

The conflict between relativistic causality and localizability is analyzed in the light of the existence of unsharp localization observables. A theorem due to S. Schlieder is generalized, showing that the assumption of local commutativity…

Quantum Physics · Physics 2013-03-28 Paul Busch

We study the relation of causal influence between input systems of a reversible evolution and its output systems, in the context of operational probabilistic theories. We analyse two different definitions that are borrowed from the…

Quantum Physics · Physics 2021-08-04 Paolo Perinotti

Condensed mathematics, developed by Clausen and Scholze over the last few years, proposes a generalization of topology with better categorical properties. It replaces the concept of a topological space by that of a condensed set, which can…

Causal Models are like Dependency Graphs and Belief Nets in that they provide a structure and a set of assumptions from which a joint distribution can, in principle, be computed. Unlike Dependency Graphs, Causal Models are models of…

Artificial Intelligence · Computer Science 2013-03-08 John F. Lemmer

We generalize the van Kampen theorem for unions of non-connected spaces, due to R. Brown and A. R. Salleh, to the context where families of subspaces of a space B are replaced by a locally sectionable map to B.

Algebraic Topology · Mathematics 2024-12-05 Ronald Brown , George Janelidze , George Peschke

Local causal states are latent representations that capture organized pattern and structure in complex spatiotemporal systems. We expand their functionality, framing them as spacetime autoencoders. Previously, they were only considered as…

Machine Learning · Computer Science 2020-10-13 Adam Rupe , James P. Crutchfield

Quantum measurement predictions are consistent with relativity for macroscopic observations, but there is no consensus on how to explain this consistency in fundamental terms. The prevailing assumption is that the relativistic structure of…

History and Philosophy of Physics · Physics 2012-10-15 Edward J. Gillis

Causality never gained the status of a "law" or "principle" in physics. Some recent literature even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged…

Quantum Physics · Physics 2019-09-19 Giacomo Mauro D'Ariano

Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been…

Programming Languages · Computer Science 2010-04-20 James Cheney

Recently, time series classification has attracted the attention of a large number of researchers, and hundreds of methods have been proposed. However, these methods often ignore the spatial correlations among dimensions and the local…

Machine Learning · Computer Science 2024-11-28 Mingsen Du , Yanxuan Wei , Xiangwei Zheng , Cun Ji

Existing work on quantum causal structure assumes that one can perform arbitrary operations on the systems of interest. But this condition is often not met. Here, we extend the framework for quantum causal modelling to situations where a…

Quantum Physics · Physics 2023-06-07 Nick Ormrod , Augustin Vanrietvelde , Jonathan Barrett

Causality is a subject of philosophical debate and a central scientific issue with a long history. In the statistical domain, the study of cause and effect based on the notion of `fairness' in comparisons dates back several hundred years,…

Other Statistics · Statistics 2022-04-06 Erica EM Moodie , David A Stephens

A quantum causal topology is presented. This is modeled after a non-commutative scheme type of theory for the curved finitary spacetime sheaves of the non-abelian incidence Rota algebras that represent `gravitational quantum causal sets'.…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Ioannis Raptis

We develop a framework for causal inference with continuous spatiotemporal point-process outcomes under cell-level interventions and outcome spillover. Potential outcomes are indexed by full treatment allocations, and the observed…

Methodology · Statistics 2026-04-15 Conor Kresin , Duncan A. Clark , Louis Davis , Martin Hazelton

We present a compositional algebraic framework to describe the evolution of quantum fields in discretised spacetimes. We show how familiar notions from Relativity and quantum causality can be recovered in a purely order-theoretic way from…

Quantum Physics · Physics 2020-03-31 Stefano Gogioso , Maria E. Stasinou , Bob Coecke

Quantum theory allows for the superposition of causal orders between operations, i.e., for an indefinite causal order; an implication of the principle of quantum superposition. Since a higher theory might also admit this feature, an…

Quantum Physics · Physics 2024-11-08 Kuntal Sengupta

This paper provides a thorough introduction to the causal set hypothesis aimed at students, and other interested persons, with some knowledge of general relativity and nonrelativistic quantum mechanics. I elucidate the arguments for why the…

General Relativity and Quantum Cosmology · Physics 2009-10-31 David D. Reid

Discovering causal relationships from observational data, particularly in the presence of latent variables, poses a challenging problem. While current local structure learning methods have proven effective and efficient when the focus lies…

Machine Learning · Computer Science 2024-06-07 Feng Xie , Zheng Li , Peng Wu , Yan Zeng , Chunchen Liu , Zhi Geng
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