Complexity Reduction in Large Quantum Systems: Reliable Electrostatic Embedding for Multiscale Approaches via Optimized Minimal Basis Functions
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Summary
This work presents a simple way of embedding the QM region into an effective electrostatic potential representing the environment, generated by partitioning the environment into well defined fragments, and assigning each one a set of electrostatic multipoles, which can then be used to build up the electro static potential.
- Type
- preprint
- Published
- 2017-03-20
- Cited by
- 3
- References
- 69
- Access
- Open access
- OpenAlex
- https://openalex.org/W2624789874
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:119450408
Keywords
Embedding, Granularity, Linear scale, Quantum, Scaling
References
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Cited by
- Complexity Reduction in Large Quantum Systems: Fragment Identification and Population Analysis via a Local Optimized Minimal Basis.
- Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library.
- Linear scaling DFT calculations for large Tungsten systems using an optimized local basis
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