Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities
Abstract
Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.
- Authors:
-
- Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), Basic Energy Sciences (BES); US Air Force Office of Scientific Research (AFOSR); US Army Research Office (ARO)
- OSTI Identifier:
- 1608218
- Alternate Identifier(s):
- OSTI ID: 1600063
- Grant/Contract Number:
- AC05-00OR22725; FA9550-18-1-0505; W911NF-16-1-0182
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Physical Review B
- Additional Journal Information:
- Journal Volume: 101; Journal Issue: 7; Journal ID: ISSN 2469-9950
- Publisher:
- American Physical Society (APS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; approximation methods for many-body systems; Bethe-Salpeter equation; diagrammatic methods; exact diagonalizatoin; exact solutions for many-body systems; Hubbard model; numerical techniques
Citation Formats
Raum, P., Alvarez, Gonzalo, Maier, Thomas, and Scarola, Vito. Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities. United States: N. p., 2020.
Web. doi:10.1103/PhysRevB.101.075122.
Raum, P., Alvarez, Gonzalo, Maier, Thomas, & Scarola, Vito. Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities. United States. https://doi.org/10.1103/PhysRevB.101.075122
Raum, P., Alvarez, Gonzalo, Maier, Thomas, and Scarola, Vito. Tue .
"Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities". United States. https://doi.org/10.1103/PhysRevB.101.075122. https://www.osti.gov/servlets/purl/1608218.
@article{osti_1608218,
title = {Two-particle correlation functions in cluster perturbation theory: Hubbard spin susceptibilities},
author = {Raum, P. and Alvarez, Gonzalo and Maier, Thomas and Scarola, Vito},
abstractNote = {Cluster perturbation theory (CPT) is a computationally economic method commonly used to estimate the momentum- and energy-resolved single-particle Green's function. It has been used extensively in direct comparisons with experiments that effectively measure the single-particle Green's function, e.g., angle-resolved photoemission spectroscopy. However, many experimental observables are given by two-particle correlation functions. CPT can be extended to compute two-particle correlation functions by approximately solving the Bethe-Salpeter equation. We implement this method and focus on the transverse spin susceptibility, measurable via inelastic neutron scattering or with optical probes of atomic gases in optical lattices. Finally, we benchmark the method with the one-dimensional Fermi-Hubbard model by comparing with known results.},
doi = {10.1103/PhysRevB.101.075122},
journal = {Physical Review B},
number = 7,
volume = 101,
place = {United States},
year = {Tue Feb 18 00:00:00 EST 2020},
month = {Tue Feb 18 00:00:00 EST 2020}
}
Web of Science
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