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Related papers: Randomness from causally independent processes

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Causal phenomena associated with rare events occur across a wide range of engineering problems, such as risk-sensitive safety analysis, accident analysis and prevention, and extreme value theory. However, current methods for causal…

Machine Learning · Statistics 2023-07-19 Chih-Yuan Chiu , Kshitij Kulkarni , Shankar Sastry

A common assumption in causal inference from observational data is that there is no hidden confounding. Yet it is, in general, impossible to verify this assumption from a single dataset. Under the assumption of independent causal mechanisms…

Methodology · Statistics 2023-11-07 Rickard K. A. Karlsson , Jesse H. Krijthe

We prove that the distribution of the product of two correlated normal random variables with arbitrary means and arbitrary variances is infinitely divisible. We also obtain exact formulas for the probability density function of the sum of…

Probability · Mathematics 2025-06-10 Robert E. Gaunt , Saralees Nadarajah , Tibor K. Pogány

Inferring the causal direction and causal effect between two discrete random variables X and Y from a finite sample is often a crucial problem and a challenging task. However, if we have access to observational and interventional data, it…

Machine Learning · Statistics 2020-10-16 Peter Gmeiner

This paper presents a framework for Quantum causal modeling based on the interpretation of causality as a relation between an observer's probability assignments to hypothetical or counterfactual experiments. The framework is based on the…

Quantum Physics · Physics 2020-01-15 Jacques Pienaar

We study an analog of the well-known Gel'fand Pinsker Channel which uses quantum states for the transmission of the data. We consider the case where both the sender's inputs to the channel and the channel states are to be taken from a…

Quantum Physics · Physics 2016-05-04 Holger Boche , Ning Cai , Janis Nötzel

If the prior probability distributions of all possible hypothetical true means and all possible observed means of a continuous variable are conditional on the universal set of all numbers (i.e., before the nature of a study is known and a…

Methodology · Statistics 2025-06-05 Huw Llewelyn

Quantum theory can be viewed as a generalization of classical probability theory, but the analogy as it has been developed so far is not complete. Whereas the manner in which inferences are made in classical probability theory is…

Quantum Physics · Physics 2013-12-04 M. S. Leifer , R. W. Spekkens

A short, information-theoretic proof of the Kac--Bernstein theorem, which is stated as follows, is presented: For any independent random variables $X$ and $Y$, if $X+Y$ and $X-Y$ are independent, then $X$ and $Y$ are normally distributed.

Information Theory · Computer Science 2022-02-22 J. Jon Ryu , Young-Han Kim

Intrinsic randomness is generated when a quantum state is measured in any basis in which it is not diagonal. In an adversarial scenario, we quantify this randomness by the probability that a correlated eavesdropper could correctly guess the…

Quantum Physics · Physics 2026-02-19 Fionnuala Curran

We describe a new class of models of quantum space-time based on energetic causal sets and show that under natural conditions space-time emerges from them. These are causal sets whose causal links are labelled by energy and momentum and…

General Relativity and Quantum Cosmology · Physics 2016-02-22 Marina Cortês , Lee Smolin

The unpredictability of quantum physics gives rise to intrinsic randomness. In an adversarial scenario, any additional degrees of freedom must be attributed to an eavesdropper with correlations to the measurement set-up. The true randomness…

Quantum Physics · Physics 2026-05-19 Fionnuala Curran

Complex data usually results from the interaction of objects produced by different generating mechanisms. Here we introduce a universal, unsupervised and parameter-free model-oriented approach, based upon the seminal concept of algorithmic…

Artificial Intelligence · Computer Science 2018-09-14 Hector Zenil , Narsis A. Kiani , Allan A. Zea , Jesper Tegnér

A long sequence of tosses of a classical coin produces an apparently random bit string, but classical randomness is an illusion: the algorithmic information content of a classically-generated bit string lies almost entirely in the…

Quantum Physics · Physics 2007-05-23 Ulvi Yurtsever

It is well known that while the independence of random variables implies zero correlation, the opposite is not true. Namely, uncorrelated random variables are not necessarily independent. In this note we show that the implication could be…

Statistics Theory · Mathematics 2024-04-22 Piotr Jaworski , Damian Jelito , Marcin Pitera

A noncontextual system of random variables may become contextual if one adds to it a set of new variables, even if each of them is obtained by the same context-wise function of the old variables. This fact follows from the definition of…

Quantum Physics · Physics 2022-12-22 Ehtibar N. Dzhafarov , Janne V. Kujala

The goal of randomness extraction is to distill (almost) perfect randomness from a weak source of randomness. When the source yields a classical string X, many extractor constructions are known. Yet, when considering a physical randomness…

Quantum Physics · Physics 2014-05-14 Mario Berta , Omar Fawzi , Stephanie Wehner

The classical randomization criterion is an important result of statistical decision theory. Recently, a quantum analogue has been proposed, giving equivalent conditions for two sets of quantum states, ensuring existence of a quantum…

Quantum Physics · Physics 2014-04-16 Anna Jencova

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…

A recent method for causal discovery is in many cases able to infer whether X causes Y or Y causes X for just two observed variables X and Y. It is based on the observation that there exist (non-Gaussian) joint distributions P(X,Y) for…

Information Theory · Computer Science 2009-10-12 Dominik Janzing , Bastian Steudel