Cellular dynamical mean field approach to strongly correlated systems

Gabriel Kotliar; Sergej Y. Savrasov; Gunnar Pálsson; Giulio Biroli

doi:10.1103/PhysRevLett.87.186401

Cellular dynamical mean field approach to strongly correlated systems

Gabriel Kotliar, Sergej Y. Savrasov, Gunnar Pálsson, Giulio Biroli

School of Arts and Sciences, Physics & Astronomy

Research output: Contribution to journal › Article › peer-review

92 Scopus citations

Abstract

We propose a cellular version of dynamical mean field theory which gives a natural generalization of its original single-site construction and is formulated in different sets of variables. We incorporate a possible nonorthogonality of the tight-binding basis set and prove that the resulting equations lead to manifestly causal self-energies.

Original language	English (US)
Pages (from-to)	186401-1-186401-4
Journal	Physical review letters
Volume	87
Issue number	18
DOIs	https://doi.org/10.1103/PhysRevLett.87.186401
State	Published - 2001

All Science Journal Classification (ASJC) codes

Physics and Astronomy(all)

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10.1103/PhysRevLett.87.186401

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title = "Cellular dynamical mean field approach to strongly correlated systems",

abstract = "We propose a cellular version of dynamical mean field theory which gives a natural generalization of its original single-site construction and is formulated in different sets of variables. We incorporate a possible nonorthogonality of the tight-binding basis set and prove that the resulting equations lead to manifestly causal self-energies.",

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AU - Pálsson, Gunnar

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AB - We propose a cellular version of dynamical mean field theory which gives a natural generalization of its original single-site construction and is formulated in different sets of variables. We incorporate a possible nonorthogonality of the tight-binding basis set and prove that the resulting equations lead to manifestly causal self-energies.

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DO - 10.1103/PhysRevLett.87.186401

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SP - 186401-1-186401-4

JO - Physical review letters

JF - Physical review letters

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Cellular dynamical mean field approach to strongly correlated systems

Abstract

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