Data for A universal preconditioner for simulating condensed phase materials. Packwood, D., Kermode, J. R., Mones, L., Bernstein, N., Woolley, J., Gould, N., Ortner, C., & Csanyi, G. April, 2016.
Data for A universal preconditioner for simulating condensed phase materials [link]Paper  abstract   bibtex   
We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.
@misc{wrap78579,
           month = {April},
           title = {Data for A universal preconditioner for simulating condensed phase materials},
          author = {David Packwood and James R. Kermode and Letif Mones and Noam Bernstein and John Woolley and Nicholas Gould and Christoph Ortner and Gabor Csanyi},
       publisher = {University of Warwick, School of Engineering},
            year = {2016},
             url = {https://wrap.warwick.ac.uk/78579/},
        abstract = {We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.}
}

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