Atomic Partitioning of the MPn (n = 2, 3, 4) Dynamic Electron Correlation Energy by the Interacting Quantum Atoms...

Area of Science:

• Quantum chemistry
• Computational chemistry
• Theoretical chemistry

Background:

• The interacting quantum atoms (IQA) method partitions molecular energy to provide chemical insight.
• Extending IQA to MPn wave functions captures dynamic electron correlation but is computationally expensive.
• Existing methods struggle to create machine learning training sets due to computational costs.

Purpose of the Study:

• To develop an accelerated algorithm for calculating atomically partitioned electron correlation energies.
• To enable the generation of accurate and sizeable training sets for machine learning models at the MPn level.
• To facilitate the application of quantum topological methods in computational chemistry.

Main Methods:

• Extension of the interacting quantum atoms (IQA) method to MPn (n=2, 3, 4) wave functions.
• Development of an algorithm to significantly accelerate the computation of electron correlation energies.
• Utilizing analytical integrals over whole space, avoiding the need for pairwise interatomic energies.

Main Results:

• Marked acceleration in the calculation of atomically partitioned electron correlation energies.
• Demonstration that pairwise interatomic energies are not required for the FFLUX force field.
• Feasibility of generating accurate and large training sets at the MPn level of theory.

Conclusions:

• The developed algorithm overcomes the computational bottleneck of IQA-MPn calculations.
• It is now practical to create machine learning training sets for topological atom models.
• This advancement supports the use of advanced quantum chemical methods for developing predictive models.