Disorder information from conductance: A quantum inverse problem
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1103/PhysRevB.102.075409 http://hdl.handle.net/11449/197138 |
Resumo: | It is straightforward to calculate the conductance of a quantum device once all its scattering centers are fully specified. However, to do this in reverse, i.e., to find information about the composition of scatterers in a device from its conductance, is an elusive task. This is particularly more challenging in the presence of disorder. Here we propose a procedure in which valuable compositional information can be extracted from the seemingly noisy spectral conductance of a two-terminal disordered quantum device. In particular, we put forward an inversion methodology that can identify the nature and respective concentration of randomly-distributed impurities by analyzing energy-dependent conductance fingerprints. Results are shown for graphene nanoribbons as a case in point using both tight-binding and density functional theory simulations, indicating that this inversion technique is general, robust, and can be employed to extract structural and compositional information of disordered mesoscopic devices from standard conductance measurements. |
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Repositório Institucional da UNESP |
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Disorder information from conductance: A quantum inverse problemIt is straightforward to calculate the conductance of a quantum device once all its scattering centers are fully specified. However, to do this in reverse, i.e., to find information about the composition of scatterers in a device from its conductance, is an elusive task. This is particularly more challenging in the presence of disorder. Here we propose a procedure in which valuable compositional information can be extracted from the seemingly noisy spectral conductance of a two-terminal disordered quantum device. In particular, we put forward an inversion methodology that can identify the nature and respective concentration of randomly-distributed impurities by analyzing energy-dependent conductance fingerprints. Results are shown for graphene nanoribbons as a case in point using both tight-binding and density functional theory simulations, indicating that this inversion technique is general, robust, and can be employed to extract structural and compositional information of disordered mesoscopic devices from standard conductance measurements.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)ICTP-Simons Foundation Associate SchemeTrinity Coll Dublin, Sch Phys, Dublin 2, IrelandSao Paulo State Univ, Inst Fis Teor, BR-01140070 Sao Paulo, BrazilUniv Fed Fluminense, Inst Fis, BR-24210346 Niteroi, RJ, BrazilTrinity Coll Dublin, Ctr Res Adapt Nanostruct & Nanodevices CRANN, Dublin 2, IrelandTrinity Coll Dublin, Adv Mat & Bioengn Res AMBER, Dublin 2, IrelandSao Paulo State Univ, Inst Fis Teor, BR-01140070 Sao Paulo, BrazilFAPESP: 2017/02317-2FAPESP: 2016/01343-7FAPESP: 2017/10292-0CNPq: 308801/2015-6CNPq: 312716/2018-4FAPERJ: E-26/202.882/2018Amer Physical SocTrinity Coll DublinUniversidade Estadual Paulista (Unesp)Universidade do Estado do Rio de Janeiro (UERJ)Mukim, S.Amorim, F. P. [UNESP]Rocha, A. R. [UNESP]Muniz, R. B.Lewenkopf, C.Ferreira, M. S.2020-12-10T20:07:25Z2020-12-10T20:07:25Z2020-08-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article6http://dx.doi.org/10.1103/PhysRevB.102.075409Physical Review B. College Pk: Amer Physical Soc, v. 102, n. 7, 6 p., 2020.2469-9950http://hdl.handle.net/11449/19713810.1103/PhysRevB.102.075409WOS:000555769900005Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPhysical Review Binfo:eu-repo/semantics/openAccess2021-10-23T11:59:43Zoai:repositorio.unesp.br:11449/197138Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:12:14.352574Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Disorder information from conductance: A quantum inverse problem |
title |
Disorder information from conductance: A quantum inverse problem |
spellingShingle |
Disorder information from conductance: A quantum inverse problem Mukim, S. |
title_short |
Disorder information from conductance: A quantum inverse problem |
title_full |
Disorder information from conductance: A quantum inverse problem |
title_fullStr |
Disorder information from conductance: A quantum inverse problem |
title_full_unstemmed |
Disorder information from conductance: A quantum inverse problem |
title_sort |
Disorder information from conductance: A quantum inverse problem |
author |
Mukim, S. |
author_facet |
Mukim, S. Amorim, F. P. [UNESP] Rocha, A. R. [UNESP] Muniz, R. B. Lewenkopf, C. Ferreira, M. S. |
author_role |
author |
author2 |
Amorim, F. P. [UNESP] Rocha, A. R. [UNESP] Muniz, R. B. Lewenkopf, C. Ferreira, M. S. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Trinity Coll Dublin Universidade Estadual Paulista (Unesp) Universidade do Estado do Rio de Janeiro (UERJ) |
dc.contributor.author.fl_str_mv |
Mukim, S. Amorim, F. P. [UNESP] Rocha, A. R. [UNESP] Muniz, R. B. Lewenkopf, C. Ferreira, M. S. |
description |
It is straightforward to calculate the conductance of a quantum device once all its scattering centers are fully specified. However, to do this in reverse, i.e., to find information about the composition of scatterers in a device from its conductance, is an elusive task. This is particularly more challenging in the presence of disorder. Here we propose a procedure in which valuable compositional information can be extracted from the seemingly noisy spectral conductance of a two-terminal disordered quantum device. In particular, we put forward an inversion methodology that can identify the nature and respective concentration of randomly-distributed impurities by analyzing energy-dependent conductance fingerprints. Results are shown for graphene nanoribbons as a case in point using both tight-binding and density functional theory simulations, indicating that this inversion technique is general, robust, and can be employed to extract structural and compositional information of disordered mesoscopic devices from standard conductance measurements. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-10T20:07:25Z 2020-12-10T20:07:25Z 2020-08-05 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1103/PhysRevB.102.075409 Physical Review B. College Pk: Amer Physical Soc, v. 102, n. 7, 6 p., 2020. 2469-9950 http://hdl.handle.net/11449/197138 10.1103/PhysRevB.102.075409 WOS:000555769900005 |
url |
http://dx.doi.org/10.1103/PhysRevB.102.075409 http://hdl.handle.net/11449/197138 |
identifier_str_mv |
Physical Review B. College Pk: Amer Physical Soc, v. 102, n. 7, 6 p., 2020. 2469-9950 10.1103/PhysRevB.102.075409 WOS:000555769900005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Physical Review B |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
6 |
dc.publisher.none.fl_str_mv |
Amer Physical Soc |
publisher.none.fl_str_mv |
Amer Physical Soc |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128771266445312 |