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In this Thesis, several results in quantum information theory are collected, most of which use entropy as the main mathematical tool. *While a direct generalization of the Shannon entropy to density matrices, the von Neumann entropy behaves…

Quantum Physics · Physics 2018-10-25 Christian Majenz

Since its introduction in 2011, the partial information decomposition (PID) has triggered an explosion of interest in the field of multivariate information theory and the study of emergent, higher-order ("synergistic") interactions in…

Information Theory · Computer Science 2024-02-14 Thomas F. Varley

Quantum information processing is the emerging field that defines and realizes computing devices that make use of quantum mechanical principles, like the superposition principle, entanglement, and interference. In this review we study the…

Quantum Physics · Physics 2015-05-13 Harry Buhrman , Richard Cleve , Serge Massar , Ronald de Wolf

What are the distinct ways in which a set of predictor variables can provide information about a target variable? When does a variable provide unique information, when do variables share redundant information, and when do variables combine…

Information Theory · Computer Science 2018-05-04 Conor Finn , Joseph T Lizier

Higher-dimensional entanglement is a valuable resource for several quantum information processing tasks, and is often characterized by the Schmidt number and specific classes of entangled states beyond qubit-qubit and qubit-qutrit systems.…

Quantum Physics · Physics 2025-07-28 Bivas Mallick , Ananda G. Maity , Nirman Ganguly , A. S. Majumdar

The uncertainty principle bounds the uncertainties about incompatible measurements, clearly setting quantum theory apart from the classical world. Its mathematical formulation via uncertainty relations, plays an irreplaceable role in…

Quantum Physics · Physics 2019-08-22 Yunlong Xiao , Kun Fang , Gilad Gour

Quantum information decoupling is a fundamental primitive in quantum information theory, underlying various applications in quantum physics. We prove a novel one-shot decoupling theorem formulated in terms of quantum relative entropy…

Quantum Physics · Physics 2026-02-20 Mario Berta , Hao-Chung Cheng , Yongsheng Yao

We summarize recent developments at the interface of quantum gravity and quantum information, and discuss applications to the quantum geometry of space in loop quantum gravity. In particular, we describe the notions of link entanglement,…

General Relativity and Quantum Cosmology · Physics 2023-08-23 Eugenio Bianchi , Etera R. Livine

During a spontaneous change, a macroscopic physical system will evolve towards a macro-state with more realizations. This observation is at the basis of the Statistical Mechanical version of the Second Law of Thermodynamics, and it provides…

Statistical Mechanics · Physics 2020-04-22 Mengjie Zu , Arunkumar Bupathy , Daan Frenkel , Srikanth Sastry

The pure quantum entanglement is generalized to the case of mixed compound states on an operator algebra to include the classical and quantum encodings as particular cases. The true quantum entanglements are characterized by quantum…

Quantum Physics · Physics 2007-05-23 V. P. Belavkin

Quantum information processed in strongly correlated states of matter can provide built in hardware protection against errors. We may encode information in highly non local degrees of freedom, such as using three dimensional spin lattices…

Quantum Physics · Physics 2009-01-27 G. K. Brennen , K. Hammerer , L. Jiang , M. D. Lukin , P. Zoller

I study the mutual information between spatial subsystems in a variety of scale invariant quantum field theories. While it is derived from the bare entanglement entropy, the mutual information offers a more refined probe of the entanglement…

Quantum Physics · Physics 2010-10-21 Brian Swingle

One of the fundamental steps toward understanding a complex system is identifying variation at the scale of the system's components that is most relevant to behavior on a macroscopic scale. Mutual information provides a natural means of…

Machine Learning · Computer Science 2024-03-20 Kieran A. Murphy , Dani S. Bassett

A core feature of complex systems is that the interactions between elements in the present causally constrain each-other as the system evolves through time. To fully model all of these interactions (between elements, as well as ensembles of…

Neurons and Cognition · Quantitative Biology 2023-04-26 Thomas F. Varley

We analyze tight informationally complete measurements for arbitrarily large multipartite systems and study their configurations of entanglement. We demonstrate that tight measurements cannot be exclusively composed neither of fully…

Quantum Physics · Physics 2018-06-26 Jakub Czartowski , Dardo Goyeneche , Karol Życzkowski

Quantum correlations in an entangled many-body system are capable of storing information. Even when the information is injected by a local unitary operation to the system, the entanglement delocalizes it. In a recent study on multiple-qubit…

Quantum Physics · Physics 2020-06-04 Koji Yamaguchi , Masahiro Hotta

One of the most important questions in quantum information theory is the so-called separability problem. It involves characterizing the set of separable (or, equivalently entangled) states among mixed states of a multipartite quantum…

Quantum Physics · Physics 2014-12-16 Michał Oszmaniec

We present a quantum information-inspired framework for analyzing complex systems through multivariate time series. In this approach the system's state is encoded into a density matrix, providing a compact representation of higher-order…

Chaotic Dynamics · Physics 2025-12-17 Parsa Kafashi , Mozhgan Orujlu

We review recent progress on the information paradox. We explain why exponentially small correlations in the radiation emitted by a black hole are sufficient to resolve the original paradox put forward by Hawking. We then describe a…

High Energy Physics - Theory · Physics 2021-02-02 Suvrat Raju

We consider a set of probabilistic functions of some input variables as a representation of the inputs. We present bounds on how informative a representation is about input data. We extend these bounds to hierarchical representations so…

Machine Learning · Statistics 2015-02-03 Greg Ver Steeg , Aram Galstyan
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