Ab initiocalculation of atomic solid hydrogen phases based on Gutzwiller many-body wave functions
Zhuo Ye1, Jun Liu1, Yong-Xin Yao1,2
1Ames National Laboratory-US DOE, Ames, IA 50011, United States of America.
We introduce two advanced computational methods, correlation matrix renormalization theory (CMRT) and Gutzwiller conjugate gradient minimization (GCGM), for studying crystalline hydrogen. GCGM offers superior accuracy in predicting total energies compared to CMRT and DFT.
Area of Science:
- Condensed Matter Physics
- Computational Quantum Chemistry
Background:
- Accurate theoretical modeling of crystalline hydrogen phases is crucial for understanding materials under extreme conditions.
- Existing methods like Density-Functional Theory (DFT) often struggle with strong electron correlation effects.
- Ab initio many-body methods offer a path to higher accuracy but can be computationally demanding.
Purpose of the Study:
- To investigate crystalline phases of atomic hydrogen using two novel Gutzwiller-based ab initio methods.
- To compare the accuracy and computational efficiency of Correlation Matrix Renormalization Theory (CMRT) and Gutzwiller Conjugate Gradient Minimization (GCGM).
- To benchmark these methods against Quantum Monte Carlo (QMC) and DFT results.
Main Methods:
- Application of Correlation Matrix Renormalization Theory (CMRT) utilizing Gutzwiller wave functions.
- Application of Gutzwiller Conjugate Gradient Minimization (GCGM) based on Gutzwiller wave functions.
- Benchmarking against Quantum Monte Carlo (QMC) and Density-Functional Theory (DFT) results.
Main Results:
- Both CMRT and GCGM provide more accurate results than DFT for crystalline hydrogen.
- GCGM systematically captures more correlation energy than CMRT, leading to improved total energy predictions.
- Incorporating LDA correlation energy (CMRT+Ec) enhances CMRT's agreement with QMC results.
Conclusions:
- CMRT and GCGM are robust ab initio methods for studying correlated electron systems like crystalline hydrogen.
- GCGM offers a significant improvement in accuracy over CMRT for total energy calculations.
- These Gutzwiller-based methods present a viable alternative to empirical parameterizations and computationally expensive techniques.
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