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Published on: April 8, 2020
The tensor hypercontracted parametric reduced density matrix algorithm: coupled-cluster accuracy with O(r(4))
Neil Shenvi1, Helen van Aggelen, Yang Yang
1Department of Chemistry, Duke University, Durham, North Carolina 27708, USA.
This study introduces tensor hypercontraction to efficiently compute electron repulsion integrals and excitation amplitudes for the parametric 2-electron reduced density matrix (p2RDM) algorithm, achieving accurate results with reduced computational scaling.
Area of Science:
- Quantum chemistry
- Computational physics
- Theoretical chemistry
Background:
- The parametric 2-electron reduced density matrix (p2RDM) algorithm is a powerful tool for electronic structure calculations.
- High-rank tensors, such as electron repulsion integrals and excitation amplitudes, pose a computational challenge.
- Efficient tensor decomposition methods are crucial for reducing the computational cost of quantum chemical calculations.
Purpose of the Study:
- To apply tensor hypercontraction to approximate electron repulsion integral tensors and two-particle excitation amplitudes.
- To develop a computationally efficient algorithm for the p2RDM method.
- To assess the accuracy and scalability of the proposed tensor hypercontraction approach.
Main Methods:
- Tensor hypercontraction was employed to represent high-rank tensors as products of lower-rank tensors.
- The method was applied to electron repulsion integral tensors and two-particle excitation amplitudes within the p2RDM framework.
- The computational scaling of the algorithm was analyzed, showing a dependence of O(r^4) on the number of single-particle basis functions (r).
Main Results:
- The tensor hypercontraction approach successfully approximated the electron repulsion integral tensor and two-particle excitation amplitudes.
- The developed algorithm demonstrated a favorable O(r^4) computational scaling.
- Applications to small molecules, hydrogen chains, and alkanes confirmed the practical utility and low formal scaling.
- The accuracy achieved was comparable to the standard p2RDM algorithm, falling between CCSD and CCSD(T) levels of theory.
Conclusions:
- Tensor hypercontraction offers an efficient strategy for approximating key components in the p2RDM algorithm.
- The method significantly reduces computational cost while maintaining high accuracy.
- This approach holds promise for enabling more accurate and feasible electronic structure calculations for larger systems.
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