001     820360
005     20221109161713.0
024 7 _ |2 arXiv
|a arXiv:1610.09991
024 7 _ |2 Handle
|a 2128/12643
024 7 _ |2 DOI
|a 10.1007/978-3-319-53862-4_15
037 _ _ |a FZJ-2016-05691
041 _ _ |a English
100 1 _ |0 P:(DE-HGF)0
|a Lichtenstein, Julian
|b 0
|e Corresponding author
111 2 _ |a JARA High-Performance Computing Symposium
|c Aachen
|d 2016-10-04 - 2016-10-05
|g JHPCS
|w Germany
245 _ _ |a Parallel adaptive integration in high-performance functional Renormalization Group computations
260 _ _ |b Springer-Verlag
|c 2016
300 _ _ |a 170-184
336 7 _ |2 ORCID
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336 7 _ |0 33
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490 0 _ |a Lecture Notes in Computer Science
|v 10164
500 _ _ |a 14 pages, 4 figures
520 _ _ |a The conceptual framework provided by the functional Renormalization Group (fRG) has become a formidable tool to study correlated electron systems on lattices which, in turn, provided great insights to our understanding of complex many-body phenomena, such as high-temperature superconductivity or topological states of matter. In this work we present one of the latest realizations of fRG which makes use of an adaptive numerical quadrature scheme specifically tailored to the described fRG scheme. The final result is an increase in performance thanks to improved parallelism and scalability.
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536 _ _ |0 G:(DE-Juel1)jhpc26_20151101
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700 1 _ |0 P:(DE-Juel1)144723
|a Di Napoli, Edoardo
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