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Efficient Implementation of Ab Initio Quantum Embedding in Periodic Systems: Density Matrix Embedding Theory.

Zhi-Hao Cui1, Tianyu Zhu1, Garnet Kin-Lic Chan1

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This study presents an efficient quantum embedding framework for ab initio density matrix embedding theory (DMET) calculations in solids. The method accurately computes ground-state properties for materials like silicon and nickel monoxide.

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Area of Science:

  • Quantum chemistry
  • Condensed matter physics
  • Computational materials science

Background:

  • Accurate electronic structure calculations are crucial for understanding material properties.
  • Traditional methods struggle with the computational cost for large, complex systems.
  • Density Matrix Embedding Theory (DMET) offers a promising approach for accurate and efficient calculations.

Purpose of the Study:

  • To develop and present an efficient quantum embedding framework for ab initio Density Matrix Embedding Theory (DMET) calculations in solids.
  • To detail the key components of the framework, including orbital selection, virtual space treatment, and integral transformations.
  • To validate the framework by applying it to diverse solid-state systems.

Main Methods:

  • Development of an efficient quantum embedding framework for ab initio DMET.
  • Detailed discussion of orbital mapping, virtual space truncation, and integral transformations.
  • Application of the framework to hexagonal boron nitride, crystalline silicon, and antiferromagnetic nickel monoxide using large embedded clusters (up to 300 orbitals).

Main Results:

  • Successful application of the ab initio DMET framework to realistic solid-state systems.
  • Accurate computation of ground-state properties, including total energy, equation of state, and magnetic moments.
  • Demonstration of the framework's capability in calculating correlation functions.

Conclusions:

  • The developed ab initio DMET framework provides an efficient and accurate method for electronic structure calculations in solids.
  • The framework is versatile and applicable to a range of materials with different electronic properties.
  • This work advances the computational capabilities for studying complex solid-state systems.