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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

A fully simultaneously optimizing genetic approach to the highly excited coupled-cluster factorization problem.

Anna Engels-Putzka¹, Michael Hanrath

¹Institute for Theoretical Chemistry, University of Cologne, Greinstraße 4, 50939 Cologne, Germany.

The Journal of Chemical Physics

|April 5, 2011

Summary

This study introduces a novel coupled-cluster factorization method using a genetic algorithm, achieving significant speedups for quantum chemistry calculations. The approach optimizes intermediate reuse and common factor identification for enhanced computational efficiency.

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Area of Science:

Quantum Chemistry
Computational Chemistry
Theoretical Chemistry

Background:

Coupled-cluster (CC) methods are essential for accurate electronic structure calculations.
Efficient implementation of CC methods is crucial for tackling complex molecular systems.
Factorization of CC equations presents a significant computational challenge.

Purpose of the Study:

To develop and implement a novel, simultaneous optimization strategy for coupled-cluster factorization.
To improve the computational efficiency of high-level coupled-cluster calculations.
To assess the performance of the new factorization method against existing implementations.

Main Methods:

A genetic algorithm is employed to optimize contraction order, identify reusable intermediates, and factor common terms.
The method considers all projection levels in a single optimization step.
Performance is benchmarked against one-term-at-a-time strategies and established quantum chemistry software.

Main Results:

The developed factorization method achieves speedups of up to 4 compared to traditional approaches.
A theoretical lower bound for the highest order scaling cost is derived and met by the implementation.
Significant performance improvements are observed for highly excited coupled-cluster algorithms.

Conclusions:

The novel coupled-cluster factorization strategy offers substantial computational gains.
This method provides a more efficient route to high-level quantum chemical calculations.
The implementation demonstrates competitive and often superior performance to existing methods.