International Journal of Quantum Chemistry· 2013Q3
Jaguar: A high‐performance quantum chemistry software program with strengths in life and materials sciences
- 1,801citations
- Q3SCImago
- 2013year
Short summary
Jaguar is an ab initio quantum chemistry program optimized for fast electronic structure predictions in medium to large molecular systems, enabling routine computations with thousands of molecular orbitals via pseudospectral approximation and parallelization.
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Key points
- Jaguar specializes in fast electronic structure predictions for medium to large molecular systems.
- It utilizes computational methods with favorable scaling, such as DFT and local MP2.
- Performance is enhanced by pseudospectral approximation and multiple levels of parallelization.
- The program supports routine computations with several thousand molecular orbitals.
AI-generated from the title and abstract; the full text is not read.
Abstract
Jaguar is an ab initio quantum chemical program that specializes in fast electronic structure predictions for molecular systems of medium and large size. Jaguar focuses on computational methods with reasonable computational scaling with the size of the system, such as density functional theory (DFT) and local second‐order Møller–Plesset perturbation theory. The favorable scaling of the methods and the high efficiency of the program make it possible to conduct routine computations involving several thousand molecular orbitals. This performance is achieved through a utilization of the pseudospectral approximation and several levels of parallelization. The speed advantages are beneficial for applying Jaguar in biomolecular computational modeling. Additionally, owing to its superior wave function guess for transition‐metal‐containing systems, Jaguar finds applications in inorganic and bioinorganic chemistry. The emphasis on larger systems and transition metal elements paves the way toward developing Jaguar for its use in materials science modeling. The article describes the historical and new features of Jaguar, such as improved parallelization of many modules, innovations in ab initio pKa prediction, and new semiempirical corrections for nondynamic correlation errors in DFT. Jaguar applications in drug discovery, materials science, force field parameterization, and other areas of computational research are reviewed. Timing benchmarks and other results obtained from the most recent Jaguar code are provided. The article concludes with a discussion of challenges and directions for future development of the program. © 2013 Wiley Periodicals, Inc.
The authors' abstract, as published at the source. International Journal of Quantum Chemistry, 2013 · DOI ↗
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Field: Computational Theory and Mathematics
Computational Theory and MathematicsComputer Science