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We prove an entropic uncertainty relation for two quantum channels, extending the work of Frank and Lieb for quantum measurements. This is obtained via a generalized strong super-additivity (SSA) of quantum entropy. Motivated by Petz's…

Quantum Physics · Physics 2023-01-23 Li Gao , Marius Junge , Nicholas LaRacuente

Strong subadditivity of von Neumann entropy, proved in 1973 by Lieb and Ruskai, is a cornerstone of quantum coding theory. All other known inequalities for entropies of quantum systems may be derived from it. Here we prove a new inequality…

Quantum Physics · Physics 2007-05-23 Noah Linden , Andreas Winter

Information plays an important role in our understanding of the physical world. We hence propose an entropic measure of information for any physical theory that admits systems, states and measurements. In the quantum and classical world,…

Quantum Physics · Physics 2010-05-04 Anthony J. Short , Stephanie Wehner

The von Neumann entropy plays a vital role in quantum information theory. The von Neumann entropy determines, e.g., the capacities of quantum channels. Also, entropies of composite quantum systems are important for future quantum networks,…

Quantum Physics · Physics 2018-10-31 Christian Majenz

The entropy of probability distribution defined by Shannon has several extensions. R\'enyi entropy is one of the general extensions of Shannon entropy and is widely used in engineering, physics, and so on. On the other hand, the quantum…

Mathematical Physics · Physics 2019-09-04 Farrukh Mukhamedov , Kyouhei Ohmura , Noboru Watanabe

An uncertainty relation for the R\'enyi entropies of conjugate quantum observables is used to obtain a strong Heisenberg limit of the form ${\rm RMSE} \geq f(\alpha)/(\langle N\rangle+\frac12)$, bounding the root mean square error of any…

Quantum Physics · Physics 2022-11-21 Michael J. W. Hall

We review with a tutorial scope the information theory foundations of quantum statistical physics. Only a small proportion of the variables that characterize a system at the microscopic scale can be controlled, for both practical and…

Statistical Mechanics · Physics 2007-05-23 R. Balian

We investigate the relation between the scaling of block entropies and the efficient simulability by Matrix Product States (MPS), and clarify the connection both for von Neumann and Renyi entropies (see Table I). Most notably, even states…

Quantum Physics · Physics 2009-11-13 Norbert Schuch , Michael M. Wolf , Frank Verstraete , J. Ignacio Cirac

We study a proper definition of R\'enyi mutual information (RMI) in quantum field theory as defined via the Petz R\'enyi relative entropy. Unlike the standard definition, the RMI we compute is a genuine measure of correlations between…

High Energy Physics - Theory · Physics 2023-01-16 Jonah Kudler-Flam

In the estimation theory context, we generalize the notion of Shannon's entropy power to the R\'{e}nyi-entropy setting. This not only allows to find new estimation inequalities, such as the R\'{e}nyi-entropy based De Bruijn identity,…

Quantum Physics · Physics 2021-04-07 Petr Jizba , Jacob Dunningham , Martin Prokš

The von Neumann entropy and the subentropy of a mixed quantum state are upper and lower bounds, respectively, on the accessible information of any ensemble consistent with the given mixed state. Here we define and investigate a set of…

Quantum Physics · Physics 2007-05-23 Sarah R. Nichols , William K. Wootters

Relative entropy is the standard measure of distinguishability in classical and quantum information theory. In the classical case, its loss under channels admits an exact chain rule, while in the quantum case only asymptotic, regularized…

Quantum Physics · Physics 2026-05-26 Giulio Gasbarri , Matt Hoogsteder-Riera

This dissertation investigates relative entropies, also called generalized divergences, and how they can be used to characterize information-theoretic tasks in quantum information theory. The main goal is to further refine characterizations…

Quantum Physics · Physics 2016-11-29 Felix Leditzky

We investigate the situation when a normal positive linear unital map on a semifinite von Neumann algebra leaving the trace invariant does not change fixed quantum Renyi's entropy of the density of a normal state. It is also shown that such…

Operator Algebras · Mathematics 2023-02-07 Andrzej Łuczak , Hanna Podsędkowska , Rafał Wieczorek

In local quantum circuits with charge conservation, we initialize the system in random product states and study the dynamics of the Renyi entanglement entropy $R_\alpha$. We rigorously prove that $R_\alpha$ with Renyi index $\alpha>1$ at…

Quantum Physics · Physics 2020-12-21 Yichen Huang

Even if a probability distribution is properly normalizable, its associated Shannon (or von Neumann) entropy can easily be infinite. We carefully analyze conditions under which this phenomenon can occur. Roughly speaking, this happens when…

Statistical Mechanics · Physics 2013-04-04 Valentina Baccetti , Matt Visser

We formulate limits to perception under continuous quantum measurements by comparing the quantum states assigned by agents that have partial access to measurement outcomes. To this end, we provide bounds on the trace distance and the…

Quantum Physics · Physics 2021-12-30 Luis Pedro García-Pintos , Adolfo del Campo

We consider 3d N>= 2 superconformal field theories on a branched covering of a three-sphere. The Renyi entropy of a CFT is given by the partition function on this space, but conical singularities break the supersymmetry preserved in the…

High Energy Physics - Theory · Physics 2015-06-16 Tatsuma Nishioka , Itamar Yaakov

The zero-entropy-density conjecture states that the entropy density, defined as the limit of S(N)/N at infinity, vanishes for all translation-invariant pure states on the spin chain. Or equivalently, S(N), the von Neumann entropy of such a…

Mathematical Physics · Physics 2009-11-11 S. Farkas , Z. Zimboras

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li