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Related papers: Analysing causal structures using Tsallis entropie…

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Reichenbach's principle states that in a causal structure, correlations of classical information can stem from a common cause in the common past or a direct influence from one of the events in correlation to the other. The difficulty of…

Quantum Physics · Physics 2018-06-19 Ämin Baumeler , Julien Degorre , Stefan Wolf

Inferring causal relations from experimental observations is of primal importance in science. Instrumental tests provide an essential tool for that aim, as they allow one to estimate causal dependencies even in the presence of unobserved…

A comparative study of one-dimensional quantum structures which allow analytic expressions for the position and momentum R\'{e}nyi $R(\alpha)$ and Tsallis $T(\alpha)$ entropies, focuses on extracting the most characteristic physical…

Quantum Physics · Physics 2019-01-15 O. Olendski

Quantum correlations arising in Bell experiments, involving a physical source that emits a quantum state to a number of observers, have been intensively studied over the last decades. Much less is known about the nature of quantum…

Quantum Physics · Physics 2016-03-01 Armin Tavakoli

Instrumental variables allow the estimation of cause and effect relations even in presence of unobserved latent factors, thus providing a powerful tool for any science wherein causal inference plays an important role. More recently, the…

Quantum Physics · Physics 2019-09-20 Davide Poderini , Rafael Chaves , Iris Agresti , Gonzalo Carvacho , Fabio Sciarrino

Bell non-local correlations cannot be naturally explained in a fixed causal structure. This serves as a motivation for considering models where no global assumption is made beyond logical consistency. The assumption of a fixed causal order…

Quantum Physics · Physics 2016-04-06 Ämin Baumeler , Stefan Wolf

Causal networks beyond that in the paradigmatic Bell's theorem can lead to new kinds and applications of non-classical behavior. Their study, however, has been hindered by the fact that they define a non-convex set of correlations and only…

Quantum Physics · Physics 2023-11-16 Giulio Camillo , Pedro Lauand , Davide Poderini , Rafael Rabelo , Rafael Chaves

Verlinde has recently conjectured, via a Beckenstein-like thought experiment, that gravitation, instead of being an elementary force, is an emergent entropic one. This rather surprising conjecture was actually proved in [Physica A {\bf 505}…

General Physics · Physics 2018-12-20 A. Plastino , M. C. Rocca

The Tsallis entropy barrier or the roundness barrier based dynamic stochastic resonance mechanisms are put forward and simulated. The systems with various Tsallis q values exhibit the effects of emergence as a result of the noise-induced…

Statistical Mechanics · Physics 2008-08-19 Xiangjun Feng

It is difficult to extract reliable criteria for causal locality from the limited ingredients found in textbook quantum theory. In the end, Bell humbly warned that his eponymous theorem was based on criteria that "should be viewed with the…

Quantum Physics · Physics 2024-02-28 Jacob A. Barandes

A classical fluid splitter produces the same patterns of energy redistribution as a Stern-Gerlach quantum device, with rotationally invariant coefficients of correlation between molecular paths. Alternative settings express a cosine squared…

General Physics · Physics 2026-04-23 Ghenadie N. Mardari

Entanglement entropy in causal sets offers a fundamentally covariant characterisation of quantum field degrees of freedom. A known result in this context is that the degrees of freedom consist of a number of contributions that have…

High Energy Physics - Theory · Physics 2023-11-27 Théo Keseman , Hans J. Muneesamy , Yasaman K. Yazdi

The notion of group entropy is proposed. It enables to unify and generalize many different definitions of entropy known in the literature, as those of Boltzmann-Gibbs, Tsallis, Abe and Kaniadakis. Other new entropic functionals are…

Statistical Mechanics · Physics 2015-05-28 Piergiulio Tempesta

Causal Structure Learning (CSL), also referred to as causal discovery, amounts to extracting causal relations among variables in data. CSL enables the estimation of causal effects from observational data alone, avoiding the need to perform…

Machine Learning · Computer Science 2025-02-12 Fabrizio Russo , Francesca Toni

For noncomposite systems in classical and quantum domains, we obtain new inequalities such as the subadditivity and strong subadditivity conditions for Shannon entropies and information determined by the probability distributions and for…

Quantum Physics · Physics 2015-06-19 Margarita A Man'ko , Vladimir I Man'ko

Complex processes often arise from sequences of simpler interactions involving a few particles at a time. These interactions, however, may not be directly accessible to experiments. Here we develop the first efficient method for unravelling…

Quantum Physics · Physics 2022-06-24 Ge Bai , Ya-Dong Wu , Yan Zhu , Masahito Hayashi , Giulio Chiribella

The notion of entropy penetrates much of science. A key feature of the all-important notion of Boltzmann-Gibbs-Shannon entropy is its extensivity (additivity over independent subsystems). However, there is a need for other quantities. In…

Mathematical Physics · Physics 2008-07-29 Flemming Topsoe

The Tsallis and R\'enyi entropies are important quantities in the information theory, statistics and related fields because the Tsallis entropy is an one parameter generalization of the Shannon entropy and the R\'enyi entropy includes…

Quantum Physics · Physics 2014-12-24 Yusuke Ide , Norio Konno , Junji Shikata

Quantum mechanics challenges our intuition on the cause-effect relations in nature. Some fundamental concepts, including Reichenbach's common cause principle or the notion of local realism, have to be reconsidered. Traditionally, this is…

Quantum Physics · Physics 2020-12-04 Mariami Gachechiladze , Nikolai Miklin , Rafael Chaves

Classical causal and statistical inference methods typically assume the observed data consists of independent realizations. However, in many applications this assumption is inappropriate due to a network of dependences between units in the…

Machine Learning · Computer Science 2019-07-02 Rohit Bhattacharya , Daniel Malinsky , Ilya Shpitser