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Related papers: Information causality beyond the random access cod…

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Distinguishing between cause and effect using time series observational data is a major challenge in many scientific fields. A new perspective has been provided based on the principle of Independence of Causal Mechanisms (ICM), leading to…

Methodology · Statistics 2021-11-01 Michel Besserve , Naji Shajarisales , Dominik Janzing , Bernhard Schölkopf

We study coordination under restricted information, where classical local models fail to implement certain correlated distributions because agents cannot condition on past history. We show that quantum systems overcome this limitation even…

Quantum Physics · Physics 2026-05-08 Faisal Shah Khan

A central question in quantum information theory is to determine how well lost information can be reconstructed. Crucially, the corresponding recovery operation should perform well without knowing the information to be reconstructed. In…

Quantum Physics · Physics 2016-02-08 David Sutter , Omar Fawzi , Renato Renner

Recently, there has been much interest in a new kind of ``unspeakable'' quantum information that stands to regular quantum information in the same way that a direction in space or a moment in time stands to a classical bit string: the…

Quantum Physics · Physics 2007-05-23 Stephen D. Bartlett , Terry Rudolph , Robert W. Spekkens

In classic cases, Reichenbach's principle implies that discriminating between common causes and causality is unprincipled since the discriminative results essentially depend on the selection of possible conditional variables. For some…

Quantum Physics · Physics 2018-08-01 Mingdi Hu , Yuexian Hou

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

We present several novel identities and inequalities relating the mutual information and the directed information in systems with feedback. The internal blocks within such systems are restricted only to be causal mappings, but are allowed…

Information Theory · Computer Science 2013-01-29 Milan S. Derpich , Eduardo I. Silva , Jan Østergaard

We review a recent approach to the foundations of quantum mechanics inspired by quantum information theory. The approach is based on a general framework, which allows one to address a large class of physical theories which share basic…

Quantum Physics · Physics 2015-06-04 G. Chiribella , C. M. Scandolo

We show that recent results on the interaction of causality-respecting particles with particles on closed timelike curves derived in [Phys. Rev. A 82, 062330 (2010)] depend on ambiguous assumption about the form of the state which is…

Quantum Physics · Physics 2011-11-24 Waldemar Klobus , Andrzej Grudka , Antoni Wojcik

In modern science the efficient numerical treatment of high-dimensional problems becomes more and more important. A fundamental insight of the theory of information-based complexity (IBC for short) is that the computational hardness of a…

Numerical Analysis · Mathematics 2013-05-20 Markus Weimar

The idea that the dynamical properties of quantum systems are invariably relative to other systems has recently regained currency. Using Relational Quantum Mechanics (RQM) for a case study, this paper calls attention to a question that has…

History and Philosophy of Physics · Physics 2024-03-26 Timotheus Riedel

The language of information theory is favored in both causal reasoning and machine learning frameworks. But, is there a better language than this? In this study, we demonstrate the pitfalls of infotheoretic estimation using first order…

Information Theory · Computer Science 2021-10-26 Nithin Nagaraj

Quantum systems may contain underlying correlations which are inaccessible to computationally bounded observers. We capture this distinction through a framework that analyses bipartite states only using efficiently implementable quantum…

Quantum Physics · Physics 2026-04-20 Álvaro Yángüez , Noam Avidan , Jan Kochanowski , Thomas A. Hahn

In this paper we present and analyze an information-theoretic task that consists in learning a bit of information by spatially moving the "target" particle that encodes it. We show that, on one hand, the task can be solved with the use of…

Quantum Physics · Physics 2023-11-07 Sebastian Horvat , Borivoje Dakić

Quantum information scrambling refers to the loss of local recoverability of quantum information, which has found widespread attention from high energy physics to quantum computing. In the present analysis we propose a possible starting…

Quantum Physics · Physics 2020-05-27 Akram Touil , Sebastian Deffner

There have been a number of attempts to derive the set of quantum non-local correlations from reasonable physical principles. Here we introduce $\tilde{Q}$, a set of multipartite supra-quantum correlations that has appeared under different…

Quantum Physics · Physics 2015-02-23 Miguel Navascués , Yelena Guryanova , Matty J. Hoban , Antonio Acín

As systems are getting more autonomous with the development of artificial intelligence, it is important to discover the causal knowledge from observational sensory inputs. By encoding a series of cause-effect relations between events,…

Machine Learning · Computer Science 2020-01-16 Yuhao Wang , Vlado Menkovski , Hao Wang , Xin Du , Mykola Pechenizkiy

Information theory, rooted in computer science, and many-body physics, have traditionally been studied as (almost) independent fields. Only recently has this paradigm started to shift, with many-body physics being studied and characterized…

Disordered Systems and Neural Networks · Physics 2024-02-20 Noa Feldman , Niv Davidson , Moshe Goldstein

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

Current Reinforcement Learning (RL) methods often suffer from sample-inefficiency, resulting from blind exploration strategies that neglect causal relationships among states, actions, and rewards. Although recent causal approaches aim to…

Artificial Intelligence · Computer Science 2025-02-17 Hongye Cao , Fan Feng , Tianpei Yang , Jing Huo , Yang Gao