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Gutzwiller method for heavy electrons
Abstract
The Kondo limit of the periodic Anderson model is studied with use of the Gutzwiller method. Because of the nonanalytic form of the energy gain due to hybridization, a small number of electrons are promoted out of the f-level giving rise to an almost-localized Fermi-liquid state of the f electrons. Both symmetric and asymmetric limits of the Anderson model are discussed and in the former case the difference between the lattice and single-site problems is examined. A comparison is made to other examples of almost-localized Fermi liquids which are based on the Hubbard model. Finally the consequences of disorder in the Anderson model are examined.
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Citations
Cited by
Georges, A., Kotliar, G., Krauth, W., & Rozenberg, M. J. (1996) · Reviews of Modern Physics · doi:10.1103/revmodphys.68.13 · Cited by 6,901
Correlated Lattice Fermions ind=∞Dimensions
Metzner, W., & Vollhardt, D. (1989) · Physical Review Letters · doi:10.1103/physrevlett.62.324 · Cited by 2,346
Antiferromagnetic correlations in almost-localized Fermi liquids
Gros, C., Joynt, R., & Rice, T. M. (1987) · Physical Review B · doi:10.1103/physrevb.36.381 · Cited by 422
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Metadata
- Authors
- Rice, T. M., & Ueda, K.
- Venue
- Physical Review B
- Publisher
- American Physical Society (APS)
- Published
- 1986-11-01
- Volume
- 34
- Issue
- 9
- Pages
- 6420-6427
- ISSN
- 0163-1829 (ISSN-L)
- OpenAlex
- W2058865077
- Cited by
- 249
- References
- 0
- FWCI
- 10.44
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Gutzwiller method for heavy electrons. https://app.cochat.ai/papers/10.1103/physrevb.34.6420
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- Rice, T. M., & Ueda, K. (1986). Gutzwiller method for heavy electrons. Physical Review B. https://doi.org/10.1103/physrevb.34.6420
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
