scispace - formally typeset
Search or ask a question
Institution

University of Vienna

EducationVienna, Austria
About: University of Vienna is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Population & Stars. The organization has 44686 authors who have published 95840 publications receiving 2907492 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors derived closed expressions for the head of the frequency-dependent microscopic polarizability matrix in the projector-augmented wave (PAW) methodology, resulting in dielectric properties that are largely independent of the applied potentials.
Abstract: In this work we derive closed expressions for the head of the frequency-dependent microscopic polarizability matrix in the projector-augmented wave (PAW) methodology. Contrary to previous applications, the longitudinal expression is utilized, resulting in dielectric properties that are largely independent of the applied potentials. The improved accuracy of the present approach is demonstrated by comparing the longitudinal and transversal expressions of the polarizability matrix for a number of cubic semiconductors and one insulator, i.e., Si, SiC, AlP, GaAs, and diamond (C), respectively. The methodology is readily extendable to more complicated nonlocal Hamiltonians or to the calculation of the macroscopic dielectric matrix including local field effects in the random phase or density functional approximation, which is demonstrated for the previously mentioned model systems. Furthermore, density functional perturbation theory is extended to the PAW method, and the respective results are compared to those obtained by summation over the conduction band states.

2,394 citations

Journal ArticleDOI
TL;DR: The implementation of various DFT functionals and many‐body techniques within highly efficient, stable, and versatile computer codes, which allow to exploit the potential of modern computer architectures are discussed.
Abstract: During the past decade, computer simulations based on a quantum-mechanical description of the interactions between electrons and between electrons and atomic nuclei have developed an increasingly important impact on solid-state physics and chemistry and on materials science—promoting not only a deeper understanding, but also the possibility to contribute significantly to materials design for future technologies. This development is based on two important columns: (i) The improved description of electronic many-body effects within density-functional theory (DFT) and the upcoming post-DFT methods. (ii) The implementation of the new functionals and many-body techniques within highly efficient, stable, and versatile computer codes, which allow to exploit the potential of modern computer architectures. In this review, I discuss the implementation of various DFT functionals [local-density approximation (LDA), generalized gradient approximation (GGA), meta-GGA, hybrid functional mixing DFT, and exact (Hartree-Fock) exchange] and post-DFT approaches [DFT + U for strong electronic correlations in narrow bands, many-body perturbation theory (GW) for quasiparticle spectra, dynamical correlation effects via the adiabatic-connection fluctuation-dissipation theorem (AC-FDT)] in the Vienna ab initio simulation package VASP. VASP is a plane-wave all-electron code using the projector-augmented wave method to describe the electron-core interaction. The code uses fast iterative techniques for the diagonalization of the DFT Hamiltonian and allows to perform total-energy calculations and structural optimizations for systems with thousands of atoms and ab initio molecular dynamics simulations for ensembles with a few hundred atoms extending over several tens of ps. Applications in many different areas (structure and phase stability, mechanical and dynamical properties, liquids, glasses and quasicrystals, magnetism and magnetic nanostructures, semiconductors and insulators, surfaces, interfaces and thin films, chemical reactions, and catalysis) are reviewed. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2008

2,364 citations

Journal ArticleDOI
TL;DR: The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures.
Abstract: The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures. It currently offers prediction of secondary structure from a single sequence, prediction of the consensus secondary structure for a set of aligned sequences and the design of sequences that will fold into a predefined structure. All three services can be accessed via the Vienna RNA web server at http://rna.tbi.univie.ac.at/.

2,236 citations

Journal ArticleDOI
TL;DR: The first Gaia data release, Gaia DR1 as discussed by the authors, consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues.
Abstract: Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims: A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods: The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results: Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues - a realisation of the Tycho-Gaia Astrometric Solution (TGAS) - and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of 3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr-1 for the proper motions. A systematic component of 0.3 mas should be added to the parallax uncertainties. For the subset of 94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr-1. For the secondary astrometric data set, the typical uncertainty of the positions is 10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to0.03 mag over the magnitude range 5 to 20.7. Conclusions: Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.

2,174 citations

Journal ArticleDOI
TL;DR: The ENDF/B-VII.1 library as mentioned in this paper is the most widely used data set for nuclear data analysis and has been updated several times over the last five years. But the most recent version of the ENDF-B-VI.0 library is based on the JENDL-4.0 standard.

2,171 citations


Authors

Showing all 45262 results

NameH-indexPapersCitations
Tomas Hökfelt158103395979
Wolfgang Wagner1562342123391
Hans Lassmann15572479933
Stanley J. Korsmeyer151316113691
Charles B. Nemeroff14997990426
Martin A. Nowak14859194394
Barton F. Haynes14491179014
Yi Yang143245692268
Peter Palese13252657882
Gérald Simonneau13058790006
Peter M. Elias12758149825
Erwin F. Wagner12537559688
Anton Zeilinger12563171013
Wolfgang Waltenberger12585475841
Michael Wagner12435154251
Network Information
Related Institutions (5)
Ludwig Maximilian University of Munich
161.5K papers, 5.7M citations

94% related

Heidelberg University
119.1K papers, 4.6M citations

93% related

University of Zurich
124K papers, 5.3M citations

92% related

University of Amsterdam
140.8K papers, 5.9M citations

92% related

Uppsala University
107.5K papers, 4.2M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023419
20221,085
20214,479
20204,533
20194,225