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| 001 | 185571 | ||
| 005 | 20221109161711.0 | ||
| 037 | _ | _ | |a FZJ-2014-06997 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Di Napoli, Edoardo |0 P:(DE-Juel1)144723 |b 0 |e Corresponding Author |u fzj |
| 111 | 2 | _ | |a 25th Umbrella Symposium |c Aachen |d 2011-12-13 - 2011-12-15 |w Germany |
| 245 | _ | _ | |a Estimating the number of eigenvalues in a interval using the eigenproblem resolvent |
| 260 | _ | _ | |c 2011 |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1418813274_22426 |2 PUB:(DE-HGF) |x Invited |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 520 | _ | _ | |a Symmetric generalized eigenvalue problems arise in many applications in chemistry physics and engineering. In several cases only a small fraction of the eigenpairs, usually located in a interval at one of the extremities of the spectrum, is required. Obtaining previous knowledge of the number of eigenvalues within the interval boudaries is often beneficial. For instance, for those iterative methods where a projector is used in conjunction with a Rayleigh-Ritz quotient this is an essential ingredient for reducing the number of iterations and increasing the accuracy. We present a potentially inexpensive technique to estimate the number of eigenvalues in a generic interval based on numerical manipulations of the eigenproblem resolvent. |
| 536 | _ | _ | |a 411 - Computational Science and Mathematical Methods (POF2-411) |0 G:(DE-HGF)POF2-411 |c POF2-411 |f POF II |x 0 |
| 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 |
| 773 | _ | _ | |y 2011 |
| 909 | C | O | |o oai:juser.fz-juelich.de:185571 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)144723 |
| 913 | 2 | _ | |a DE-HGF |b Key Technologies |l Supercomputing & Big Data |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |
| 913 | 1 | _ | |a DE-HGF |b Schlüsseltechnologien |l Supercomputing |1 G:(DE-HGF)POF2-410 |0 G:(DE-HGF)POF2-411 |2 G:(DE-HGF)POF2-400 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF2 |
| 914 | 1 | _ | |y 2014 |
| 920 | _ | _ | |l no |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a conf |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
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