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Cubic-Scaling All-Electron GW Calculations with a Separable Density-Fitting Space-Time Approach.
1Université Grenoble Alpes, CEA, IRIG-MEM-L_Sim, 38054 Grenoble, France.
Journal of Chemical Theory and Computation
|April 2, 2021
Summary
We developed a new computational method for electronic structure calculations, enabling accurate and efficient all-electron simulations. This approach improves the speed and scalability of quantum chemistry computations for larger systems.
Area of Science:
- Computational Chemistry
- Quantum Mechanics
- Materials Science
Background:
- Accurate electronic structure calculations are crucial for understanding material properties.
- Existing methods face challenges with computational cost and scalability for large systems.
- The GW approximation is a powerful tool for predicting electronic properties.
Purpose of the Study:
- To present a novel implementation of the GW space-time approach for efficient all-electron calculations.
- To achieve cubic scaling for electronic structure calculations using standard Gaussian basis sets.
- To benchmark the method's accuracy and scalability on various molecular systems.
Main Methods:
- Implementation of the GW space-time approach.
- Construction of independent-electron susceptibility in time representation using real-space locations.
- Optimization within a separable resolution-of-the-identity framework.
- Analytic continuation of the screened Coulomb potential.
Main Results:
- Cubic-scaling all-electron calculations achieved with standard Gaussian basis sets.
- Reproduces Coulomb-fitting calculations with meV accuracy.
- Demonstrated crossover with standard Coulomb-fitting for systems < few hundred electrons.
- Benchmarked on large molecular sets and defected hexagonal boron-nitride flakes up to 6000 electrons.
Conclusions:
- The presented GW space-time approach offers a computationally efficient and accurate method for electronic structure calculations.
- The method scales favorably, enabling the study of larger and more complex systems.
- This work provides a valuable tool for advancing research in computational chemistry and materials science.
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