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:

References in zbMATH (referenced in 202 articles )

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  1. Dȩbicki, Krzysztof; Hashorva, Enkelejd; Kriukov, Nikolai: Pandemic-type failures in multivariate Brownian risk models (2022)
  2. Du, Yusong; Fan, Baoying; Wei, Baodian: A constant-time sampling algorithm for binary Gaussian distribution over the integers (2022)
  3. Flores-Gallegos, N.: Rényi’s divergence as a chemical similarity criterion (2022)
  4. Gao, Bin; Hu, Guanghui; Kuang, Yang; Liu, Xin: An orthogonalization-free parallelizable framework for all-electron calculations in density functional theory (2022)
  5. Houjou, Hirohiko; Seshimo, Masataka: Formulation of a phonon band calculation for molecular crystals using a coarse-grained coordinate approach under periodic boundary conditions (2022)
  6. Kriukov, Nikolai: Parisian & cumulative Parisian ruin probability for two-dimensional Brownian risk model (2022)
  7. Kuriki, Satoshi; Takemura, Akimichi; Taylor, Jonathan E.: The volume-of-tube method for Gaussian random fields with inhomogeneous variance (2022)
  8. Reimers, Jeffrey R.; Rätsep, Margus; Linnanto, Juha Matti; Freiberg, Arvi: Chlorophyll spectroscopy: conceptual basis, modern high-resolution approaches, and current challenges (2022)
  9. Flores-Gallegos, N.: (q)-Rényi’s entropy as a possible measure of electron correlation (2021)
  10. Guo, Theron; Rokoš, Ondřej; Veroy, Karen: Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method (2021)
  11. Higham, Nicholas J.; Liu, Xiaobo: A multiprecision derivative-free Schur-Parlett algorithm for computing matrix functions (2021)
  12. Konzou, Essomanda; Koudou, Efoévi; Gneyou, Kossi Essona: Stein’s method in two limit theorems involving the generalized inverse Gaussian distribution (2021)
  13. Kuramshina, Gulnara M.; Kochikov, Igor V.; Sharapova, Svetlana A.: Regularized \textitabinitio molecular force fields for key biological molecules: melatonin and pyridoxal-5’-phosphate methylamine Shiff base (Vitamin B6) (2021)
  14. Qiao, Wanli: Asymptotic confidence regions for density ridges (2021)
  15. Rashmi, Richa; Yadav, Komal; Lourderaj, Upakarasamy; Paranjothy, Manikandan: Second-order saddle dynamics in isomerization reaction (2021)
  16. Robert A. Shaw; J. Grant Hill: libecpint: A C++ library for the effcient evaluation of integrals over effective core potentials (2021) not zbMATH
  17. Taewon David Kim, Michael Richer, Gabriela Sánchez-Díaz, Farnaz Heidar-Zadeh, Toon Verstraelen, Ramón Alain Miranda-Quintana, Paul W. Ayers: Fanpy: A Python Library for Prototyping Multideterminant Methods in Ab Initio Quantum Chemistry (2021) arXiv
  18. Vaughn, Nathan; Gavini, Vikram; Krasny, Robert: Treecode-accelerated Green iteration for Kohn-Sham density functional theory (2021)
  19. Baudoin, Fabrice; Feng, Qi; Ouyang, Cheng: Density of the signature process of fBm (2020)
  20. Chen, Houxian; Liu, Menglin; Yan, Tianying: Molecular multipoles and (hyper)polarizabilities from the Buckingham expansion: revisited (2020)

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