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001 | 812018 | ||
005 | 20221109161713.0 | ||
024 | 7 | _ | |a arXiv:1604.06296 |2 arXiv |
024 | 7 | _ | |a 10.1016/j.cpc.2016.12.013 |2 doi |
024 | 7 | _ | |a 2128/13743 |2 Handle |
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037 | _ | _ | |a FZJ-2016-04315 |
082 | _ | _ | |a 004 |
100 | 1 | _ | |a Lichtenstein, J. |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
245 | _ | _ | |a High-performance functional Renormalization Group calculations for interacting fermions |
260 | _ | _ | |a Amsterdam |c 2017 |b North Holland Publ. Co. |
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520 | _ | _ | |a We derive a novel computational scheme for functional Renormalization Group (fRG) calculations for interacting fermions on 2D lattices. The scheme is based on the exchange parametrization fRG for the two-fermion interaction, with additional insertions of truncated partitions of unity. These insertions decouple the fermionic propagators from the exchange propagators and lead to a separation of the underlying equations. We demonstrate that this separation is numerically advantageous and may pave the way for refined, large-scale computational investigations even in the case of complex multiband systems. Furthermore, on the basis of speedup data gained from our implementation, it is shown that this new variant facilitates efficient calculations on a large number of multi-core CPUs. We apply the scheme to the $t$,$t'$ Hubbard model on a square lattice to analyze the convergence of the results with the bond length of the truncation of the partition of unity. In most parameter areas, a fast convergence can be observed. Finally, we compare to previous results in order to relate our approach to other fRG studies. |
536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
536 | _ | _ | |a High-performance functional renormalization group for two-dimensional materials (jhpc26_20151101) |0 G:(DE-Juel1)jhpc26_20151101 |c jhpc26_20151101 |f High-performance functional renormalization group for two-dimensional materials |x 1 |
536 | _ | _ | |a Simulation and Data Laboratory Quantum Materials (SDLQM) (SDLQM) |0 G:(DE-Juel1)SDLQM |c SDLQM |f Simulation and Data Laboratory Quantum Materials (SDLQM) |x 2 |
536 | _ | _ | |a Simulation and Data Laboratory Quantum Materials (SDLQM) (SDLQM) |0 G:(DE-Juel1)SDLQM |c SDLQM |f Simulation and Data Laboratory Quantum Materials (SDLQM) |x 2 |
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700 | 1 | _ | |a de la Peña, D. Sánchez |0 P:(DE-HGF)0 |b 1 |
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700 | 1 | _ | |a Honerkamp, C. |0 P:(DE-HGF)0 |b 4 |
700 | 1 | _ | |a Maier, S. A. |0 P:(DE-HGF)0 |b 5 |
773 | _ | _ | |a 10.1016/j.cpc.2016.12.013 |0 PERI:(DE-600)1466511-6 |p 100-110 |t Computer physics communications |v 213 |y 2017 |x 0010-4655 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/812018/files/1604.06296v2.pdf |y OpenAccess |
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