Quantum Entropy and Its Use by M. Ohya, Denes Petz

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By M. Ohya, Denes Petz

This monograph, by way of now a typical reference within the box, offers an entire evaluation of quantum entropy thought, from the early days of quantum mechanics as much as the newest advancements. It employs mathematical formalism according to operator conception and practical research with a objective of constructing a finished account of the several entropy strategies, their interrelations and use. one of the rules mentioned are entropy of a quantum nation, relative entropy, mutual entropy, entropy of a rough graining and dynamical entropy. quite a few basic homes of quantum info size are built, together with the von Neumann entropy of a statistical operator and its restricting normalized model, the entropy expense. Use of quantum-entropy amounts is made in perturbation conception, vital restrict theorems, thermodynamics of spin platforms, entropic uncertainty family, and optical communique. This new softcover corrected reprint includes summaries of modern advancements additional to the ends of the chapters.

Content point » Research

Keywords » Entropie - Entropy

Related matters » utilized & Technical Physics - Quantum Physics - Theoretical and Computational Chemistry

Cover

Quantum Entropy and Its Use

Copyright

© Springer-Verlag Berlin Heidelberg 1993

ISBN 3-540-54881-5

ISBN 0-387-54881-5

Preface

Contents

Introduction

Notes and Remarks

Part I: Entropies for Finite Quantum Systems

1. primary Concepts

Notes and Remarks

2. Postulates for Entropy and Relative Entropy

Notes and Remarks

three. Convex hint Functions

Notes and Remarks.

Part II: Entropies for normal Quantum Systems

four. Modular thought and Auxiliaries

Notes and Remarks

five. Relative Entropy of States of Operator Algebras

Notes and Remarks.

6. From Relative Entropy to Entropy

Notes and Remarks

7. Functionals of Entropy Type

Notes and Remarks

Part III: Channeling Transformation and Coarse Graining

eight. Channels and Their Transpose

Notes and Remarks

nine. adequate Channels and Measurements

Notes and Remarks

10. Dynamical Entropy

Notes and Remarks

eleven. desk bound Processes

Notes and Remarks.

Part IV: Perturbation Theory

12. Perturbation of States

Notes and Remarks

thirteen. Variational Expression of Perturbational Limits

Notes and Remarks.

Part V: Miscellanea

14. imperative restrict and Quasifree Reduction

Notes and Remarks.

15. Thermodynamics of Quantum Spin Systems

Notes and Remarks.

sixteen. Entropic Uncertainty Relations

Notes and Remarks.

17. Temperley-Lieb Algebras and Index

Notes and Remarks.

18. Optical verbal exchange Processes

Notes and Remarks.

Bibliography

Subject Index

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10. If F"','PI\ — = for 'P = 'Pc > otherwise, then log Tn where 'Pc is the canonical state given by the density exp(—,3(H — The proof follows from the observation Proof. 1), we have and equality holds only in the case 'P = 0 'Pc. 10 to relative entropy we introduce perturbed functionals. Let 'P be a state (or a positive functional) on a finite quantum system and let h e A be selfadjoint. Set for the density and p for the support projection of 'Ph is given by the density matrix p exp(log + php) is understood as where log not normalized and supp 'Ph = supp h= The the perturbed functional 'P + p')).

Then the functional a fixed observ- FL(A) = Tr exp(L + log A) A defined on Proof. is concave. The function f(x) = Tr exp(L + xK) of the real variable x is differentiable in a neighbourhod of 0. The theorem is equivalent to the statement d2 L dx2 x=O <0 for all choices of S E Indeed, if f is concave then putting and K, L E A=A2 and K=A1 —A2 weget Tr exp(L + log(A2 + A(A1 — A2)) ATr exp(L + log(A2 + (A1 — A2))) + (1 — A)Tr exp(L + log A2). To compute the second derivative of f we may benefit from the norm convergent expansions log(A + xK) = logA + XTA(K) — + and = ea +I I JoJo +I Jo With the simplification B +...

Instead of selecting a subsequence we suppose that Q(n(k)) T weakly. 27) the weak limit Q(n(k))P(n(k), 6) —* T follows. Consequently, lim k—*oo P(n(k), 6)) w(T) 1 — e. 30) 1. 30) and we arrive at 0 a contradiction with (ii) if 0 <6

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