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Related papers: Information causality from an entropic and a proba…

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We study the informational underpinnings of thermodynamics and statistical mechanics, using an abstract framework, general probabilistic theories, capable of describing arbitrary physical theories. This allows one to abstract the…

Quantum Physics · Physics 2019-01-25 Carlo Maria Scandolo

This paper investigates the powers and limitations of quantum entanglement in the context of cooperative games of incomplete information. We give several examples of such nonlocal games where strategies that make use of entanglement…

Quantum Physics · Physics 2010-01-11 Richard Cleve , Peter Hoyer , Ben Toner , John Watrous

We study a sequential social learning model in which there is uncertainty about the informativeness of a common signal-generating process. Rational agents arrive in order and make decisions based on the past actions of others and their…

Theoretical Economics · Economics 2025-07-01 Wanying Huang

Quantum mechanics and information theory are among the most important scientific discoveries of the last century. Although these two areas initially developed separately it has emerged that they are in fact intimately related. In this…

Quantum Physics · Physics 2009-11-07 V. Vedral

Thermodynamic entropy is not an entirely satisfactory measure of information of a quantum state. This entropy for an unknown pure state is zero, although repeated measurements on copies of such a pure state do communicate information. In…

Quantum Physics · Physics 2015-06-26 Subhash Kak

The form and justification of inductive inference rules depend strongly on the representation of uncertainty. This paper examines one generic representation, namely, incomplete information. The notion can be formalized by presuming that the…

Artificial Intelligence · Computer Science 2013-04-15 Norman C. Dalkey

Causality is a seminal concept in science: Any research discipline, from sociology and medicine to physics and chemistry, aims at understanding the causes that could explain the correlations observed among some measured variables. While…

Causal diagrams based on do intervention are useful tools to formalize, process and understand causal relationship among variables. However, the do intervention has controversial interpretation of causal questions for non-manipulable…

Artificial Intelligence · Computer Science 2020-06-03 Gong Heyang , Zhu Ke

Causality is omnipresent in scientists' verbalisations of their understanding, even though we have no formal consensual scientific definition for it. In Automata Networks, it suffices to say that automata "influence" one another to…

Other Computer Science · Computer Science 2016-10-28 Mathilde Noual

Quantum information theory is the study of the achievable limits of information processing within quantum mechanics. Many different types of information can be accommodated within quantum mechanics, including classical information, coherent…

Quantum Physics · Physics 2007-05-23 M. A. Nielsen

We consider the information causality in the multi-receiver random access codes. Therein, no receiver can gain any information only from classical communication. We claim the following statement. Information causality still holds even with…

Quantum Physics · Physics 2013-05-30 Li-Yi Hsu

This paper deals with the problem of estimating the probability that one event was a cause of another in a given scenario. Using structural-semantical definitions of the probabilities of necessary or sufficient causation (or both), we show…

Artificial Intelligence · Computer Science 2013-01-18 Jin Tian , Judea Pearl

We introduce the concept of entropic nonsignaling correlations, i.e., entropies arising from probabilistic theories that are compatible with the fact that we cannot transmit information instantaneously. We characterize and show the…

Quantum Physics · Physics 2016-06-16 Rafael Chaves , Costantino Budroni

Complexity measures in the context of the Integrated Information Theory of consciousness try to quantify the strength of the causal connections between different neurons. This is done by minimizing the KL-divergence between a full system…

Methodology · Statistics 2021-02-09 Carlotta Langer , Nihat Ay

The no-signaling constraints state that the probability distribution of the outputs of any subset of parties is independent of the inputs of the complementary set; here we re-examine these to see how they arise from relativistic causality.…

Quantum Physics · Physics 2019-04-30 Paweł Horodecki , Ravishankar Ramanathan

Recently, it has been shown that the causality and information flow between two time series can be inferred in a rigorous and quantitative sense, and, besides, the resulting causality can be normalized. A corollary that follows is, in the…

Data Analysis, Statistics and Probability · Physics 2020-01-30 X. San Liang , Xiuqun Yang

By relating and ordering events, causality constitutes a pivotal feature of our world. On the one hand, there are information-theoretic notions of causality defined in terms of the information processing ability of agents and on the other…

Quantum Physics · Physics 2023-04-26 Maarten Grothus

A crucial task for secure communication networks is to determine the minimum of physical requirements to certify a cryptographic protocol. A widely accepted candidate for certification is the principle of relativistic causality which is…

We pedagogically present the information theory as originally established, explaining its essential ideas and paying attention to the expression employed to measure the amount of information. Also we discussed relationships between…

Quantum Physics · Physics 2019-12-10 Wallas S. Nascimento , Marcos M. de Almeida , Frederico V. Prudente

Causal influences are at the core of any empirical science, the reason why its quantification is of paramount relevance for the mathematical theory of causality and applications. Quantum correlations, however, challenge our notion of cause…

Quantum Physics · Physics 2023-09-20 Lucas Hutter , Rafael Chaves , Ranieri Nery , George Moreno , Daniel J. Brod