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Related Experiment Video

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Generation and Coherent Control of Pulsed Quantum Frequency Combs

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Pure State v-Representability of Density Matrix Embedding Theory.

Fabian M Faulstich¹, Raehyun Kim¹, Zhi-Hao Cui²

¹Department of Mathematics, University of California, Berkeley, California 94720, United States.

Journal of Chemical Theory and Computation

|January 27, 2022

Summary

This summary is machine-generated.

Density matrix embedding theory (DMET) calculations can face challenges with matching density matrices. This study introduces an augmented Lagrangian method to relax the Aufbau principle, improving accuracy in complex scenarios.

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Area of Science:

Quantum chemistry
Computational condensed matter physics

Background:

Density matrix embedding theory (DMET) requires matching density matrix blocks from high-level and low-level theories.
Practical calculations sometimes fail to achieve exact matching, leading to vanishing low-level band gaps and numerical issues.

Purpose of the Study:

To address the challenges in DMET calculations arising from the inability to achieve exact matching of density matrix blocks.
To develop a method that relaxes the noninteracting pure-state v-representability (NI-PS-V) condition, which is linked to the Aufbau principle.

Main Methods:

Developed an augmented Lagrangian method to facilitate the matching of density matrix blocks.
Relaxed the strict requirement of the Aufbau principle in constructing the low-level density matrix.

Main Results:

The augmented Lagrangian method successfully relaxed the NI-PS-V condition.
In challenging cases, relaxing the Aufbau principle led to exact matching of density matrix blocks.
The proposed method demonstrated improved accuracy in the 2D Hubbard and hydrogen model systems.

Conclusions:

The developed augmented Lagrangian method provides a robust approach to overcome limitations in DMET calculations.
Relaxing the Aufbau principle is a viable strategy for achieving accurate density matrix block matching and improving computational results.