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Geometry optimization speedup through a geodesic approach to internal coordinates

Journal of Chemical Physics

Hermes, Eric H.; Sargsyan, Khachik S.; Najm, H.N.; Zador, Judit Z.

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

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TYPE Journal Article YEAR 2021
DOIOSTIScopus

NWChem: Past, present, and future

Journal of Chemical Physics

Apra, E.; Edoardo; Bylaska, E.J.; De Jong, W.A.; Govind, N.; Kowalski, K.; Straatsma, T.P.; Valiev, M.; Van Dam, H.J.J.; Alexeev, Y.; Anchell, J.; Anisimov, V.; Aquino, F.W.; Atta-Fynn, R.; Autschbach, J.; Bauman, N.P.; Bernholdt, D.E.; Bhaskaran-Nair, K.; Bogatko, S.; Borowski, P.; Boschen, J.; Brabec, J.; Caue; T, Emilie; Chen, Y.; Chuev, G.N.; Cramer, C.J.; Daily, J.; Deegan, M.J.O.; Dunning, T.H.; Dupuis, M.; Dyall, K.G.; Fann, G.I.; Fischer, S.A.; Fonari, A.; Fruchtl, H.; Gagliardi, L.; Garza, J.; Gawande, N.; Ghosh, S.; Glaesemann, K.; Go; Tz, Andreas; Hammond, J.; Helms, V.; Hermes, Eric H.; Hirata, S.; Jacquelin, M.; Jensen, L.; Johnson, B.G.; Jonsson, H.; Kendall, R.A.; Klemm, M.; Kobayashi, R.; Krishnamoorthy, S.; Krishnan, M.; Lin, Z.; Lins, R.D.; Littlefield, R.J.; Logsdail, A.J.; Lopata, K.; Ma, W.; Marenich, A.V.; Martin Del Campo, J.; Mejia-Rodriguez, D.; Moore, J.E.; Mullin, J.M.; Nichols, J.A.; Nichols, P.J.; Palmer, B.; Panyala, A.; Pirojsirikul, T.; Peng, B.; Peverati, R.; Pittner, J.; Pollack, L.; Richard, R.M.; Sadayappan, P.; Silverstein, D.W.; Smith, D.M.A.; Soares, T.A.; Song, D.; Swart, M.; Taylor, H.L.; Thomas, G.S.; Truhlar, D.G.; Tsemekhman, K.; Van Voorhis, T.; Vazquez-Mayagoitia, A.; Verma, P.; Villa, O.; Vishnu, A.; Vogiatzis, K.D.; Wang, D.; Weare, J.H.; Williamson, M.J.; Windus, T.L.; Wolinski, K.; Wong, A.T.; Wu, Q.; Yang, C.; Yu, Q.; Zacharias, M.; Zhang, Z.; Zhao, Y.; Harrison, R.J.

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

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TYPE Journal Article YEAR 2020
DOIOSTIScopus
12 Results
12 Results