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Tensor Networks - The iTEBD Algorithm (lecture 2)
<!--HTML-->In recent years, tensor networks have become a viable alternative to Monte Carlo calculations and exact diagonalization for the simulation of many-body systems. As they represent a formulation of quantum mechanical wavefunctions with polynomially many parameters, they make calculati...
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Lenguaje: | eng |
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2019
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Acceso en línea: | http://cds.cern.ch/record/2665669 |
_version_ | 1780961955501047808 |
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author | Emonts, Patrick |
author_facet | Emonts, Patrick |
author_sort | Emonts, Patrick |
collection | CERN |
description | <!--HTML-->In recent years, tensor networks have become a viable alternative to Monte Carlo calculations and exact diagonalization for the simulation of many-body systems.
As they represent a formulation of quantum mechanical wavefunctions with polynomially many parameters, they make calculations of large systems feasible.
They have already found wide application in condensed matter physics and start to be an interesting tool for high energy physics as well.
In this lecture series, I will introduce the basic concepts of tensor networks.
We will start with an introduction of the necessary basics of quantum mechanics and linear algebra and focus on the algorithmic side of tensor networks in the second lecture. |
id | cern-2665669 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2019 |
record_format | invenio |
spelling | cern-26656692022-11-02T22:32:38Zhttp://cds.cern.ch/record/2665669engEmonts, PatrickTensor Networks - The iTEBD Algorithm (lecture 2)Inverted CERN School of Computing 2019Inverted CSC<!--HTML-->In recent years, tensor networks have become a viable alternative to Monte Carlo calculations and exact diagonalization for the simulation of many-body systems. As they represent a formulation of quantum mechanical wavefunctions with polynomially many parameters, they make calculations of large systems feasible. They have already found wide application in condensed matter physics and start to be an interesting tool for high energy physics as well. In this lecture series, I will introduce the basic concepts of tensor networks. We will start with an introduction of the necessary basics of quantum mechanics and linear algebra and focus on the algorithmic side of tensor networks in the second lecture.oai:cds.cern.ch:26656692019 |
spellingShingle | Inverted CSC Emonts, Patrick Tensor Networks - The iTEBD Algorithm (lecture 2) |
title | Tensor Networks - The iTEBD Algorithm (lecture 2) |
title_full | Tensor Networks - The iTEBD Algorithm (lecture 2) |
title_fullStr | Tensor Networks - The iTEBD Algorithm (lecture 2) |
title_full_unstemmed | Tensor Networks - The iTEBD Algorithm (lecture 2) |
title_short | Tensor Networks - The iTEBD Algorithm (lecture 2) |
title_sort | tensor networks - the itebd algorithm (lecture 2) |
topic | Inverted CSC |
url | http://cds.cern.ch/record/2665669 |
work_keys_str_mv | AT emontspatrick tensornetworkstheitebdalgorithmlecture2 AT emontspatrick invertedcernschoolofcomputing2019 |