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Explicitly Correlated Electronic Structure Calculations with Transcorrelated Matrix Product Operators
Alberto Baiardi1, Michał Lesiuk1,2, Markus Reiher1
1Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland.
We introduce transcorrelated electronic Hamiltonians within the density matrix renormalization group (DMRG) algorithm. This approach improves convergence to the complete basis set limit for quantum chemistry calculations.
Area of Science:
- Quantum Chemistry
- Computational Physics
- Many-Body Methods
Background:
- Accurate electronic structure calculations are crucial in quantum chemistry.
- Conventional methods struggle with electron-electron cusp conditions.
- Matrix product states and DMRG offer a powerful framework for strongly correlated systems.
Purpose of the Study:
- To implement the transcorrelated electronic Hamiltonian within a matrix product states optimization procedure using DMRG.
- To improve the accuracy and convergence of quantum chemical calculations.
- To investigate methods for handling the computational cost of the transcorrelated Hamiltonian.
Main Methods:
- Similarity transformation of the electronic Hamiltonian with a Jastrow factor.
- Density fitting for two- and three-body integrals in the second-quantized representation.
- Encoding the non-Hermitian transcorrelated Hamiltonian as a matrix product operator.
- Optimization of the ground state wave function using imaginary-time time-dependent DMRG.
Main Results:
- Successful implementation of the transcorrelated DMRG approach.
- Demonstration on atoms and first-row diatomic molecules.
- Observed improved convergence rates to the complete basis set limit compared to conventional DMRG.
- Exploration of cost-reduction strategies for the matrix product operator representation.
Conclusions:
- Transcorrelated DMRG provides a more efficient route to accurate electronic structure.
- The method enhances convergence properties for basis set extrapolation.
- Further research can optimize the computational scaling of this promising approach.
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