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Modelling non-Markovian quantum systems using tensor networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modelling non-Markovian quantum systems using tensor networksby Aidan Strathearn.
Author:	Strathearn, Aidan.
Published:	Cham :Springer International Publishing :2020.
Description:	xv, 103 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Quantum systems.
Online resource:	https://doi.org/10.1007/978-3-030-54975-6
ISBN:	9783030549756$q(electronic bk.)

Modelling non-Markovian quantum systems using tensor networks
Strathearn, Aidan.

Modelling non-Markovian quantum systems using tensor networks[electronic resource] /by Aidan Strathearn. - Cham :Springer International Publishing :2020. - xv, 103 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Background -- Method -- Results -- Conclusion.

This thesis presents a revolutionary technique for modelling the dynamics of a quantum system that is strongly coupled to its immediate environment. This is a challenging but timely problem. In particular it is relevant for modelling decoherence in devices such as quantum information processors, and how quantum information moves between spatially separated parts of a quantum system. The key feature of this work is a novel way to represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and process tensor approaches to quantum mechanics. The tensor network methodology developed here has proven to be extremely powerful: For many situations it may be the most efficient way of calculating open quantum dynamics. This work is abounds with new ideas and invention, and is likely to have a very significant impact on future generations of physicists.

ISBN: 9783030549756$q(electronic bk.)

Standard No.: 10.1007/978-3-030-54975-6doiSubjects--Topical Terms:

696793
Quantum systems.

LC Class. No.: TK7874.885 / .S773 2020

Dewey Class. No.: 530.12011

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520 $a This thesis presents a revolutionary technique for modelling the dynamics of a quantum system that is strongly coupled to its immediate environment. This is a challenging but timely problem. In particular it is relevant for modelling decoherence in devices such as quantum information processors, and how quantum information moves between spatially separated parts of a quantum system. The key feature of this work is a novel way to represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and process tensor approaches to quantum mechanics. The tensor network methodology developed here has proven to be extremely powerful: For many situations it may be the most efficient way of calculating open quantum dynamics. This work is abounds with new ideas and invention, and is likely to have a very significant impact on future generations of physicists.
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