Generating Efficient Quantum Chemistry Codes for Novel Architectures.

By A. Titov, Ivan S. Ufimtsev, Nathan Luehr, Todd J. Martinez. Journal of Chemical Theory and Computation, 2013

366 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/a311133231224f38cc3a31fe4d39d389526ea27d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. F. García-Vidal
2. J. Feist
3. Mark P. Waller
4. C. Climent
5. Javier Galego

Citations in the corpus

• Cavity Casimir-Polder Forces and Their Effects in Ground-State Chemical Reactivity (2018, methodology): “All calculations are performed with the TeraChem package [102,103].”
• Solving the scalability issue in quantum-based refinement: Q|R#1. (2017, background): “A major stumbling block towards the adoption of QR is the issue of computational scalability that is inherent in quantumchemical methods (Titov et al., 2013).”