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000820360 005__ 20221109161713.0
000820360 0247_ $$2arXiv$$aarXiv:1610.09991
000820360 0247_ $$2Handle$$a2128/12643
000820360 0247_ $$2DOI$$a10.1007/978-3-319-53862-4_15
000820360 037__ $$aFZJ-2016-05691
000820360 041__ $$aEnglish
000820360 1001_ $$0P:(DE-HGF)0$$aLichtenstein, Julian$$b0$$eCorresponding author
000820360 1112_ $$aJARA High-Performance Computing Symposium$$cAachen$$d2016-10-04 - 2016-10-05$$gJHPCS$$wGermany
000820360 245__ $$aParallel adaptive integration in high-performance functional Renormalization Group computations
000820360 260__ $$bSpringer-Verlag$$c2016
000820360 300__ $$a170-184
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000820360 4900_ $$aLecture Notes in Computer Science$$v10164
000820360 500__ $$a14 pages, 4 figures
000820360 520__ $$aThe conceptual framework provided by the functional Renormalization Group (fRG) has become a formidable tool to study correlated electron systems on lattices which, in turn, provided great insights to our understanding of complex many-body phenomena, such as high-temperature superconductivity or topological states of matter. In this work we present one of the latest realizations of fRG which makes use of an adaptive numerical quadrature scheme specifically tailored to the described fRG scheme. The final result is an increase in performance thanks to improved parallelism and scalability.
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000820360 536__ $$0G:(DE-Juel1)jhpc26_20151101$$aHigh-performance functional renormalization group for two-dimensional materials (jhpc26_20151101)$$cjhpc26_20151101$$fHigh-performance functional renormalization group for two-dimensional materials$$x1
000820360 536__ $$0G:(DE-Juel1)SDLQM$$aSimulation and Data Laboratory Quantum Materials (SDLQM) (SDLQM)$$cSDLQM$$fSimulation and Data Laboratory Quantum Materials (SDLQM)$$x2
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000820360 7001_ $$0P:(DE-Juel1)167415$$aWinkelmann, Jan$$b1$$ufzj
000820360 7001_ $$0P:(DE-HGF)0$$ade la Peña, David Sánchez$$b2
000820360 7001_ $$0P:(DE-Juel1)167266$$aVidović, Toni$$b3
000820360 7001_ $$0P:(DE-Juel1)144723$$aDi Napoli, Edoardo$$b4$$ufzj
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