Abstract
Numerical simulations are important for many systems. In particular, various standard computer programs have been developed for solving the quantum Schrödinger equations. However, the accuracy of these calculations is limited by computer capabilities. In this work, an iterative method is introduced to enhance the accuracy of these numerical calculations, which is otherwise prohibitive by conventional methods. The method is easily implementable and general for many systems.
Highlights
Computer simulations have aided scientists to interpret and predict numerous phenomena in physics, chemistry and biology
We do have large basis sets which can describe our systems well, in principle, but applications are prohibitive due to the extremely high computational cost. This rather general bottleneck calls for the development of methods to reach the accuracy of large basis sets[22,23,24] using relatively small basis sets
Ab initio calculations for large systems with small basis sets may already reach the limit of available computers
Summary
Computer simulations have aided scientists to interpret and predict numerous phenomena in physics, chemistry and biology. The 2013 Nobel prize in chemistry highly values the contributions of computer modeling of complex chemical and biological systems[1] The key to such a successful modeling is the reliability of the adopted force field[2,3], which is obtained by fits to experimental data or to quantum mechanical calculations. We do have large basis sets which can describe our systems well, in principle, but applications are prohibitive due to the extremely high computational cost This rather general bottleneck calls for the development of methods to reach the accuracy of large basis sets[22,23,24] (or even the complete basis set[25,26] limit) using relatively small basis sets. The numerical results of several applications are presented and discussed subsequently to demonstrate the performance of the present methods
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