GAUSSIAN

Gaussian is an electronic structure program, used by chemists, chemical engineers, biochemists, physicists and others for research in established and emerging areas of chemical interest. Starting from the basic laws of quantum mechanics, Gaussian predicts the energies, molecular structures, and vibrational frequencies of molecular systems, along with numerous molecular properties derived from these basic computation types. It can be used to study molecules and reactions under a wide range of conditions, including both stable species and compounds which are difficult or impossible to observe experimentally such as short-lived intermediates and transition structures. (Source: http://www.psc.edu/)


References in zbMATH (referenced in 168 articles )

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  1. Chen, Xiaojun; Kelley, C. T.: Convergence of the EDIIS algorithm for nonlinear equations (2019)
  2. Ji, Lanpeng; Liu, Peng; Robert, Stephan: Tail asymptotic behavior of the supremum of a class of chi-square processes (2019)
  3. Kristofer Björnson: TBTK: A quantum mechanics software development kit (2019) not zbMATH
  4. Saravanan, Kandasamy; Kumaradhas, Poomani: Acylguanidine-BACE1 complex: insights of intermolecular interactions and dynamics (2019)
  5. Yunqi Shao, Matti Hellström, Pavlin D. Mitev, Lisanne Knijff, Chao Zhang: PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials (2019) arXiv
  6. Bai, Long; Dȩbicki, Krzysztof; Hashorva, Enkelejd; Luo, Li: On generalised Piterbarg constants (2018)
  7. Bodroski, Zarko; Vukmirović, Nenad; Skrbic, Srdjan: Gaussian basis implementation of the charge patching method (2018)
  8. Cimrman, Robert; Novák, Matyáš; Kolman, Radek; Tuma, Miroslav; Plešek, Jiří; Vackář, Jiří: Convergence study of isogeometric analysis based on Bézier extraction in electronic structure calculations (2018)
  9. Feragen, Aasa (ed.); Hotz, Thomas (ed.); Huckemann, Stephan (ed.); Miller, Ezra (ed.): Statistics for data with geometric structure. Abstracts from the workshop held January 21--27, 2018 (2018)
  10. Hashorva, Enkelejd: Representations of (\max)-stable processes via exponential tilting (2018)
  11. Ivanovs, Jevgenijs: Zooming in on a Lévy process at its supremum (2018)
  12. Kelley, C. T.: Numerical methods for nonlinear equations (2018)
  13. Sottinen, Tommi; Viitasaari, Lauri: Conditional-mean hedging under transaction costs in Gaussian models (2018)
  14. Wang, Yizao: Extremes of (q)-Ornstein-Uhlenbeck processes (2018)
  15. Avery, Patrick; Falls, Zackary; Zurek, Eva: \textscXtalOptversion r10: an open-source evolutionary algorithm for crystal structure prediction (2017)
  16. Gyevi-Nagy, László; Tasi, Gyula: SYVA: a program to analyze symmetry of molecules based on vector algebra (2017)
  17. Hamdi, Hamidreza; Couckuyt, Ivo; Sousa, Mario Costa; Dhaene, Tom: Gaussian processes for history-matching: application to an unconventional gas reservoir (2017)
  18. Ian H. Williams, Philippe B. Wilson: SULISO: The Bath suite of vibrational characterization and isotope effect calculation software (2017) not zbMATH
  19. Khoromskaia, Venera; Khoromskij, Boris N.: Block circulant and Toeplitz structures in the linearized Hartree-Fock equation on finite lattices: tensor approach (2017)
  20. Leszczynski, Jerzy (ed.); Kaczmarek-Kedziera, Aanna (ed.); Puzyn, Tomasz (ed.); Papadopoulos, Manthos G. (ed.); Reis, Heribert (ed.); Shukla, Manoj K. (ed.): Handbook of computational chemistry (2017)

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