Accelerating Nonequilibrium Green functions simulations with embedding selfenergies
| Title: | Accelerating Nonequilibrium Green functions simulations with embedding selfenergies |
|---|---|
| Authors: | Balzer, Karsten, Schlünzen, Niclas, Ohldag, Hannes, Joost, Jan-Philip, Bonitz, Michael |
| Publication Year: | 2022 |
| Collection: | Condensed Matter Physics (Other) Quantum Physics |
| Subject Terms: | Condensed Matter - Strongly Correlated Electrons, Physics - Computational Physics, Quantum Physics |
| More Details: | Real-time nonequilibrium Green functions (NEGF) have been very successful to simulate the dynamics of correlated many-particle systems far from equilibrium. However, NEGF simulations are computationally expensive since the effort scales cubically with the simulation duration. Recently we have introduced the G1--G2 scheme that allows for a dramatic reduction to time-linear scaling [Schl\"unzen, Phys. Rev. Lett. 124, 076601 (2020); Joost et al., Phys. Rev. B 101, 245101 (2020)]. Here we tackle another problem: the rapid growth of the computational effort with the system size. In many situations where the system of interest is coupled to a bath, to electric contacts or similar macroscopic systems for which a microscopic resolution of the electronic properties is not necessary, efficient simplifications are possible. This is achieved by the introduction of an embedding selfenergy -- a concept that has been successful in standard NEGF simulations. Here, we demonstrate how the embedding concept can be introduced into the G1--G2 scheme, allowing us to drastically accelerate NEGF embedding simulations. The approach is compatible with all advanced selfenergies that can be represented by the G1--G2 scheme [as described in Joost et al., Phys. Rev. B 105, 165155 (2022)] and retains the memory-less structure of the equations and their time linear scaling. As a numerical illustration we investigate the charge transfer between a Hubbard nanocluster and an additional site which is of relevance for the neutralization of ions in matter. |
| Document Type: | Working Paper |
| DOI: | 10.1103/PhysRevB.107.155141 |
| Access URL: | http://arxiv.org/abs/2211.09615 |
| Accession Number: | edsarx.2211.09615 |
| Database: | arXiv |
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| Items | – Name: Title Label: Title Group: Ti Data: Accelerating Nonequilibrium Green functions simulations with embedding selfenergies – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Balzer%2C+Karsten%22">Balzer, Karsten</searchLink><br /><searchLink fieldCode="AR" term="%22Schlünzen%2C+Niclas%22">Schlünzen, Niclas</searchLink><br /><searchLink fieldCode="AR" term="%22Ohldag%2C+Hannes%22">Ohldag, Hannes</searchLink><br /><searchLink fieldCode="AR" term="%22Joost%2C+Jan-Philip%22">Joost, Jan-Philip</searchLink><br /><searchLink fieldCode="AR" term="%22Bonitz%2C+Michael%22">Bonitz, Michael</searchLink> – Name: DatePubCY Label: Publication Year Group: Date Data: 2022 – Name: Subset Label: Collection Group: HoldingsInfo Data: Condensed Matter<br />Physics (Other)<br />Quantum Physics – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Condensed+Matter+-+Strongly+Correlated+Electrons%22">Condensed Matter - Strongly Correlated Electrons</searchLink><br /><searchLink fieldCode="DE" term="%22Physics+-+Computational+Physics%22">Physics - Computational Physics</searchLink><br /><searchLink fieldCode="DE" term="%22Quantum+Physics%22">Quantum Physics</searchLink> – Name: Abstract Label: Description Group: Ab Data: Real-time nonequilibrium Green functions (NEGF) have been very successful to simulate the dynamics of correlated many-particle systems far from equilibrium. However, NEGF simulations are computationally expensive since the effort scales cubically with the simulation duration. Recently we have introduced the G1--G2 scheme that allows for a dramatic reduction to time-linear scaling [Schl\"unzen, Phys. Rev. Lett. 124, 076601 (2020); Joost et al., Phys. Rev. B 101, 245101 (2020)]. Here we tackle another problem: the rapid growth of the computational effort with the system size. In many situations where the system of interest is coupled to a bath, to electric contacts or similar macroscopic systems for which a microscopic resolution of the electronic properties is not necessary, efficient simplifications are possible. This is achieved by the introduction of an embedding selfenergy -- a concept that has been successful in standard NEGF simulations. Here, we demonstrate how the embedding concept can be introduced into the G1--G2 scheme, allowing us to drastically accelerate NEGF embedding simulations. The approach is compatible with all advanced selfenergies that can be represented by the G1--G2 scheme [as described in Joost et al., Phys. Rev. B 105, 165155 (2022)] and retains the memory-less structure of the equations and their time linear scaling. As a numerical illustration we investigate the charge transfer between a Hubbard nanocluster and an additional site which is of relevance for the neutralization of ions in matter. – Name: TypeDocument Label: Document Type Group: TypDoc Data: Working Paper – Name: DOI Label: DOI Group: ID Data: 10.1103/PhysRevB.107.155141 – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="http://arxiv.org/abs/2211.09615" linkWindow="_blank">http://arxiv.org/abs/2211.09615</link> – Name: AN Label: Accession Number Group: ID Data: edsarx.2211.09615 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1103/PhysRevB.107.155141 Subjects: – SubjectFull: Condensed Matter - Strongly Correlated Electrons Type: general – SubjectFull: Physics - Computational Physics Type: general – SubjectFull: Quantum Physics Type: general Titles: – TitleFull: Accelerating Nonequilibrium Green functions simulations with embedding selfenergies Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Balzer, Karsten – PersonEntity: Name: NameFull: Schlünzen, Niclas – PersonEntity: Name: NameFull: Ohldag, Hannes – PersonEntity: Name: NameFull: Joost, Jan-Philip – PersonEntity: Name: NameFull: Bonitz, Michael IsPartOfRelationships: – BibEntity: Dates: – D: 17 M: 11 Type: published Y: 2022 |
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