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Grassmann Extrapolation for Accelerating Geometry Optimization
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DOI：10.1021/acs.jctc.4c01417.png)
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Abstract
En 中文
This study extends the Grassmann extrapolation (G-Ext) method, which was introduced for Born-Oppenheimer molecular dynamics, to the context of geometry optimization. Using density matrices from previous optimization steps, the G-Ext approach applies a nonlinear, structure-preserving mapping onto the Grassmann manifold to provide an initial guess which accelerates the convergence of the self-consistent field (SCF) procedure. Using the optimal parameters identified by employing various descriptors and computational strategies across a diverse set of molecules, G-Ext shows excellent performance improvements, particularly with large molecular systems.
Keywords:
INITIO MOLECULAR-DYNAMICS
TRANSFORMATION
ALGORITHM
Journal
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