2016
DOI: 10.1103/physrevd.94.114509
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Adaptive aggregation-based domain decomposition multigrid for twisted mass fermions

Abstract: The Adaptive Aggregation-based Domain Decomposition Multigrid method [1] is extended for two degenerate flavors of twisted mass fermions. By fine-tuning the parameters we achieve a speed-up of the order of hundred times compared to the conjugate gradient algorithm for the physical value of the pion mass. A thorough analysis of the aggregation parameters is presented, which provides a novel insight into multigrid methods for lattice QCD independently of the fermion discretization.

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Cited by 67 publications
(70 citation statements)
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“…Thus, a tuning of the precision of the solver has to be carried out. To invert the Dirac operator, we use the adaptive multigrid solver with twisted mass fermion support [96] and require the residual to be r HP =10 −10 for HP inversions. After testing different values of the residual for LP inversions, we find that the stopping criterion…”
Section: Lattice Techniquesmentioning
confidence: 99%
“…Thus, a tuning of the precision of the solver has to be carried out. To invert the Dirac operator, we use the adaptive multigrid solver with twisted mass fermion support [96] and require the residual to be r HP =10 −10 for HP inversions. After testing different values of the residual for LP inversions, we find that the stopping criterion…”
Section: Lattice Techniquesmentioning
confidence: 99%
“…Thus, the identification of the ground-state is presently possible only in the case ofss andcc vector mesons. To improve the statistics we took a significative advantage by using the DD − αAMG solver [45], which has allowed us to increase by a factor of 5 the number of stochastic sources in the case of the strange quark. In this way we find that the quality of the plateaux, shown in figure 5, is acceptable in the strange sector and nice in the charm one.…”
Section: Ground-state Identificationmentioning
confidence: 99%
“…We use a three-level DD-αAMG method optimized for TM fermions [3]. No instabilities in the iterations count are seen along the whole simulations.…”
Section: Discussionmentioning
confidence: 99%
“…The DD-αAMG approach has been adapted in Ref. [3] to the Wilson TM operator D(±µ) = D ± iµΓ 5 . Due to the Γ 5 -compatibility, the coarse operator reads similarly to the fine operator, i.e.…”
Section: Dd-αamg Methodsmentioning
confidence: 99%
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