# Efficient reconstruction of CASCI-type wave functions for a DMRG state using quantum information theory and genetic algorithm

## TL;DR

This paper presents an improved method for reconstructing CASCI-type wave functions from DMRG states using a genetic algorithm optimized by quantum information theory, enabling efficient analysis of complex molecular systems.

## Contribution

The authors introduce a novel reconstruction scheme combining genetic algorithms and quantum information theory to efficiently identify important CI expansions from DMRG wave functions.

## Key findings

- Efficient reconstruction of CASCI-type wave functions for large active spaces.
- Successful application to conjugated molecules and transition metal compounds.
- Enhanced search efficiency for significant CI expansions.

## Abstract

We improve the methodology to construct a complete active space-configuration interaction (CAS-CI) expansion for density-matrix renormalization group (DMRG) wave function using matrix-product state representation, inspired by the sampling-reconstructed CAS [SR-CAS, Boguslawski et al, J. Chem. Phys. 2011, 134, 224101] algorithm. In our scheme, a genetic algorithm, in which the "crossover" and "mutation" process can be optimized based on quantum information theory, is employed when reconstructing the CASCI-type wave function in the Hilbert space. Test analysis results for the ground and excited state wave functions of conjugated molecules and transition metal compounds illustrate that our scheme is very efficient for searching the most important CI expansions in large active spaces.