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Related papers: Causation, Information, and Physics

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Recent developments in the mathematical foundations of quantum mechanics have brought the theory closer to that of classical probability and statistics. On the other hand, the unique character of quantum physics sets many of the questions…

Quantum Physics · Physics 2007-05-23 O. E. Barndorff-Nielsen , R. D. Gill , P. E. Jupp

I introduce a new approach to semantic information based upon the influence of erasure operations (interventions) upon distributions of a system's future trajectories through its phase space. Semantic (meaningful) information is…

Statistical Mechanics · Physics 2024-07-11 Stuart J Bartlett

Information Theory provides a fundamental basis for analysis, and for a variety of subsequent methodological approaches, in relation to uncertainty quantification. The transversal character of concepts and derived results justifies its…

Statistics Theory · Mathematics 2024-11-27 Jose M. Angulo , Francisco J. Esquivel , Ana E. Madrid , Francisco J. Alonso

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

Ascribing to inanimate matter a possibility to receive, work on and transfer information allows us to explain quantum-mechanical phenomena including "delayed-choice"- and "Einstein-Podolsky-Rosen (EPR)"-type experiments adhering to the…

General Physics · Physics 2007-05-23 Raoul Nakhmanson

In our previous arXiv papers (more systematically the informational conception is presented in the paper "The Information as Absolute", 2010) it was rigorously shown that Matter in our Universe - and Universe as a whole - are some…

General Physics · Physics 2011-05-05 S. V. Shevchenko , V. V. Tokarevsky

Information theory is a statistical theory concerned with the relative state of detectors and physical systems. As a consequence, the classical framework of Shannon needs to be extended to deal with quantum detectors, possibly moving at…

Quantum Physics · Physics 2007-05-23 Christoph Adami

We review with a tutorial scope the information theory foundations of quantum statistical physics. Only a small proportion of the variables that characterize a system at the microscopic scale can be controlled, for both practical and…

Statistical Mechanics · Physics 2007-05-23 R. Balian

Quantum mechanics has led not only to new physical theories, but also a new understanding of information and computation. Quantum information began by yielding new methods for achieving classical tasks such as factoring and key distribution…

Quantum Physics · Physics 2007-05-23 Aram W. Harrow

The decoupling technique is a fundamental tool in quantum information theory with applications ranging from quantum thermodynamics to quantum many body physics to the study of black hole radiation. In this work we introduce the notion of…

Quantum Physics · Physics 2017-03-01 Christian Majenz , Mario Berta , Frédéric Dupuis , Renato Renner , Matthias Christandl

The notion of quantum information related to the two different perspectives of the global and local states is examined. There is circularity in the definition of quantum information because we can speak only of the information of systems…

Quantum Physics · Physics 2007-05-23 Subhash Kak

A New Mathematico-Physical and Information Theoretic Approach Examination of the available hard core information to firm up the process of unification of quantum and gravitational physics leads to the conclusion that for achieving this…

General Physics · Physics 2016-09-08 G. Suryan

Much of our experiments are designed to uncover the cause(s) and effect(s) behind a data generating mechanism (i.e., phenomenon) we happen to be interested in. Uncovering such relationships allows us to identify the true working of a…

Machine Learning · Computer Science 2023-07-11 M. Z. Naser

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Simon R. Schultz , Robin A. A. Ince , Stefano Panzeri

The problems of causality, modeling, and control for chaotic, high-dimensional dynamical systems are formulated in the language of information theory. The central quantity of interest is the Shannon entropy, which measures the amount of…

Dynamical Systems · Mathematics 2022-06-01 Adrián Lozano-Durán , Gonzalo Arranz

We introduce the coordination principle, which states that perfect coordination, in the form of agreement on a uniformly random output, among N parties is possible only if they share a common cause. This principle is purely causal and can…

Resource theories play an important role in quantum information theory, as they identify resourceful states and channels that are potentially useful for the accomplishment of tasks that would be otherwise unreachable. The elementary…

Quantum Physics · Physics 2020-09-02 A. C. S. Costa , R. M. Angelo

Quantum information and computation may serve as a source of useful axioms and ideas for the quantum logic/quantum structures project of characterizing and classifying types of physical theories, including quantum mechanics and classical…

Quantum Physics · Physics 2007-05-23 Howard Barnum

The apparent dichotomy between information-processing and dynamical approaches to complexity science forces researchers to choose between two diverging sets of tools and explanations, creating conflict and often hindering scientific…

Neurons and Cognition · Quantitative Biology 2022-01-26 Pedro A. M. Mediano , Fernando E. Rosas , Juan Carlos Farah , Murray Shanahan , Daniel Bor , Adam B. Barrett

Causal inference is a study of causal relationships between events and the statistical study of inferring these relationships through interventions and other statistical techniques. Causal reasoning is any line of work toward determining…

Software Engineering · Computer Science 2023-04-03 Patrick Chadbourne , Nasir Eisty