Quantum Chemical Density Matrix Renormalization Group Method Boosted by Machine Learning.

ABSTRACT: The use of machine learning (ML) to refine low-level theoretical calculations to achieve higher accuracy is a promising and actively evolving approach known as Δ-ML. The density matrix renormalization group (DMRG) is a powerful variational approach widely used for studying strongly correlated quantum systems. High computational efficiency can be achieved without compromising accuracy. Here, we demonstrate the potential of a simple ML model to significantly enhance the performance of the quantum chemical DMRG method.

SUBMITTER: Golub P 

PROVIDER: S-EPMC11973911 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature