Entanglement witnesses with tensor networks: characterizing entanglement in large systems
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | http://hdl.handle.net/1843/31439 |
Resumo: | Entanglement is certainly one of the most fascinating phenomena observed in Nature, and even after decades of research in entanglement theory there is still much to be discovered and understood. In particular, there are still few results detailing and characterizing the entanglement structure in strongly correlated systems on a large scale, involving a large number of subsystems. The most typical approach for studying in detail the entanglement structure in quantum states has been through the optimization of Entanglement Witnesses, optimized by means of algorithmic techniques such as Semidefinite Programming applied to matrices. However, this matrix description renders the technique computationally nonviable for large scale systems due to the exponential growth of the dimension of the optimization parameters. All these techniques are nonviable for a relatively small number of particles (on the order of n ~ 10^1). For these reasons, Tensor Networks have attracted the attention of researchers over the last decades for being more efficient ways to describe and simulate quantum systems composed of many parts, as they are more natural and efficient descriptions of the quantum correlations between subsystems. However, few progress has been made for the detailed characterization of entanglement in such systems, and the literature still hasn't fully bridged the gap between the two formalisms. In this work, we propose a small step towards the goal of adapting the formalism of entanglement witnesses in a way which is compatible with the description of quantum systems by means of tensor networks, making it possible the characterization of entanglement in large scale systems. |
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Reinaldo Oliveira Viannahttp://lattes.cnpq.br/8413008847105670Thiago Oliveira Macielhttp://lattes.cnpq.br/0618716919641724Carlos Henrique MonkenWalber Hugo de Britohttp://lattes.cnpq.br/2536186685642316Lucas Vieira Barbosa2019-12-05T19:48:21Z2019-12-05T19:48:21Z2019-08-02http://hdl.handle.net/1843/31439Entanglement is certainly one of the most fascinating phenomena observed in Nature, and even after decades of research in entanglement theory there is still much to be discovered and understood. In particular, there are still few results detailing and characterizing the entanglement structure in strongly correlated systems on a large scale, involving a large number of subsystems. The most typical approach for studying in detail the entanglement structure in quantum states has been through the optimization of Entanglement Witnesses, optimized by means of algorithmic techniques such as Semidefinite Programming applied to matrices. However, this matrix description renders the technique computationally nonviable for large scale systems due to the exponential growth of the dimension of the optimization parameters. All these techniques are nonviable for a relatively small number of particles (on the order of n ~ 10^1). For these reasons, Tensor Networks have attracted the attention of researchers over the last decades for being more efficient ways to describe and simulate quantum systems composed of many parts, as they are more natural and efficient descriptions of the quantum correlations between subsystems. However, few progress has been made for the detailed characterization of entanglement in such systems, and the literature still hasn't fully bridged the gap between the two formalisms. In this work, we propose a small step towards the goal of adapting the formalism of entanglement witnesses in a way which is compatible with the description of quantum systems by means of tensor networks, making it possible the characterization of entanglement in large scale systems.Emaranhamento é certamente um dos fenômenos mais fascinantes observados na Natureza, e mesmo após de décadas de pesquisas na teoria de emaranhamento ainda há muito a ser descoberto e entendido. Em particular, ainda há poucos resultados detalhando e caracterizando a estrutura do emaranhamento em sistemas fortemente correlacionados em larga escala, envolvendo um número grande de subsistemas. A forma mais comum de se estudar detalhadamente a estrutura de emaranhamento em estados quânticos tem sido através da otimização de Testemunhas de Emaranhamento (Entanglement Witnesses), otimizadas utilizando-se técnicas algorítmicas como Programação Semidefinida (Semidefinite Programming) aplicada à matrizes. No entanto, esta descrição matricial torna a técnica computacionalmente inviável para sistemas em larga escala devido ao crescimento exponencial da dimensão do espaço de parâmetros a serem otimizados. Todas as técnicas se tornam inviáveis para um número relativamente pequeno de partículas (na ordem de n ~ 10^1). Por estes motivos, Redes Tensoriais (Tensor Networks) têm atraído a atenção de pesquisadores nas últimas décadas por serem formas eficientes de descrever e simular sistemas quânticos compostos de muitas partes, pois são descrições mais naturais e eficientes das correlações quânticas entre os subsistemas. No entanto, pouco tem sido feito para caracterização detalhada do emaranhamento em tais sistemas, e a literatura ainda carece de uma ponte entre os dois formalismos. Neste trabalho, propomos um primeiro pequeno passo rumo ao objetivo de adaptar o formalismo de testemunhas de emaranhamento de forma compatível com a descrição de sistemas quânticos através de redes tensoriais, tornando possível a caracterização de emaranhamento em sistemas de larga escala.CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorengUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em FísicaUFMGBrasilICX - DEPARTAMENTO DE FÍSICAInformação quânticaTeoria quânticaEntanglementEntanglement witnessesEntanglement in pure statesNegative partial transposeSemidefinite programmingTensor networksMatrix product stateMatrix product operatorDensity matrix renormalization groupPartial transposeEntanglement witnesses with tensor networks: characterizing entanglement in large systemsTestemunhas de emaranhamento com redes tensoriais: caracterizando emaranhamento em sistemas grandesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALEntanglement_Witness_with_Tensor_Networks.pdfEntanglement_Witness_with_Tensor_Networks.pdfapplication/pdf2975123https://repositorio.ufmg.br/bitstream/1843/31439/1/Entanglement_Witness_with_Tensor_Networks.pdf7b0d930572890ffaf3bc86004a7470fdMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-82119https://repositorio.ufmg.br/bitstream/1843/31439/2/license.txt34badce4be7e31e3adb4575ae96af679MD52TEXTEntanglement_Witness_with_Tensor_Networks.pdf.txtEntanglement_Witness_with_Tensor_Networks.pdf.txtExtracted texttext/plain198621https://repositorio.ufmg.br/bitstream/1843/31439/3/Entanglement_Witness_with_Tensor_Networks.pdf.txt44dde9c3f346794dad82c9e9c3beac55MD531843/314392019-12-06 03:27:56.876oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2019-12-06T06:27:56Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
dc.title.alternative.pt_BR.fl_str_mv |
Testemunhas de emaranhamento com redes tensoriais: caracterizando emaranhamento em sistemas grandes |
title |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
spellingShingle |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems Lucas Vieira Barbosa Entanglement Entanglement witnesses Entanglement in pure states Negative partial transpose Semidefinite programming Tensor networks Matrix product state Matrix product operator Density matrix renormalization group Partial transpose Informação quântica Teoria quântica |
title_short |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
title_full |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
title_fullStr |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
title_full_unstemmed |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
title_sort |
Entanglement witnesses with tensor networks: characterizing entanglement in large systems |
author |
Lucas Vieira Barbosa |
author_facet |
Lucas Vieira Barbosa |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Reinaldo Oliveira Vianna |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8413008847105670 |
dc.contributor.advisor2.fl_str_mv |
Thiago Oliveira Maciel |
dc.contributor.advisor2Lattes.fl_str_mv |
http://lattes.cnpq.br/0618716919641724 |
dc.contributor.referee1.fl_str_mv |
Carlos Henrique Monken |
dc.contributor.referee2.fl_str_mv |
Walber Hugo de Brito |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/2536186685642316 |
dc.contributor.author.fl_str_mv |
Lucas Vieira Barbosa |
contributor_str_mv |
Reinaldo Oliveira Vianna Thiago Oliveira Maciel Carlos Henrique Monken Walber Hugo de Brito |
dc.subject.por.fl_str_mv |
Entanglement Entanglement witnesses Entanglement in pure states Negative partial transpose Semidefinite programming Tensor networks Matrix product state Matrix product operator Density matrix renormalization group Partial transpose |
topic |
Entanglement Entanglement witnesses Entanglement in pure states Negative partial transpose Semidefinite programming Tensor networks Matrix product state Matrix product operator Density matrix renormalization group Partial transpose Informação quântica Teoria quântica |
dc.subject.other.pt_BR.fl_str_mv |
Informação quântica Teoria quântica |
description |
Entanglement is certainly one of the most fascinating phenomena observed in Nature, and even after decades of research in entanglement theory there is still much to be discovered and understood. In particular, there are still few results detailing and characterizing the entanglement structure in strongly correlated systems on a large scale, involving a large number of subsystems. The most typical approach for studying in detail the entanglement structure in quantum states has been through the optimization of Entanglement Witnesses, optimized by means of algorithmic techniques such as Semidefinite Programming applied to matrices. However, this matrix description renders the technique computationally nonviable for large scale systems due to the exponential growth of the dimension of the optimization parameters. All these techniques are nonviable for a relatively small number of particles (on the order of n ~ 10^1). For these reasons, Tensor Networks have attracted the attention of researchers over the last decades for being more efficient ways to describe and simulate quantum systems composed of many parts, as they are more natural and efficient descriptions of the quantum correlations between subsystems. However, few progress has been made for the detailed characterization of entanglement in such systems, and the literature still hasn't fully bridged the gap between the two formalisms. In this work, we propose a small step towards the goal of adapting the formalism of entanglement witnesses in a way which is compatible with the description of quantum systems by means of tensor networks, making it possible the characterization of entanglement in large scale systems. |
publishDate |
2019 |
dc.date.accessioned.fl_str_mv |
2019-12-05T19:48:21Z |
dc.date.available.fl_str_mv |
2019-12-05T19:48:21Z |
dc.date.issued.fl_str_mv |
2019-08-02 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1843/31439 |
url |
http://hdl.handle.net/1843/31439 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Física |
dc.publisher.initials.fl_str_mv |
UFMG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
ICX - DEPARTAMENTO DE FÍSICA |
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Universidade Federal de Minas Gerais |
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