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Core-Level Binding Energies from GW: An Efficient Full-Frequency Approach within a Localized Basis
Dorothea Golze1,2, Jan Wilhelm3, Michiel J van Setten4
1Department of Applied Physics , Aalto University , Otakaari 1 , FI-02150 Espoo , Finland.
This study introduces a new GW method for calculating core-level excitations, crucial for X-ray photoelectron spectroscopy (XPS). The advanced approach accurately predicts core-level binding energies in molecules, achieving less than 0.5 eV deviation from experiments.
Area of Science:
- Computational Chemistry
- Quantum Mechanics
- Spectroscopy
Background:
- The GW method is standard for predicting charged valence excitations.
- Existing efficient GW algorithms fail for core excitations, limiting X-ray photoelectron spectroscopy (XPS) analysis.
- Core-level calculations require specialized numerical techniques due to complex self-energy pole structures.
Purpose of the Study:
- To develop a robust GW method capable of accurately computing core-level excitations.
- To enable precise calculations of core-level binding energies for molecules and solids.
- To provide a more accurate alternative to existing methods like delta self-consistent field (ΔSCF).
Main Methods:
- A full-frequency approach on the real axis using a localized basis set.
- Implementation of the contour deformation technique for efficient self-energy calculation.
- Validation against a fully analytic GW algorithm and experimental data.
Main Results:
- The developed GW method successfully treats core levels, overcoming limitations of previous algorithms.
- Calculated core-level binding energies for small molecules and polycyclic hydrocarbons show deviations under 0.5 eV from experimental values.
- The method demonstrates high accuracy compared to density functional theory (DFT)-based approaches.
Conclusions:
- The new GW method provides accurate and efficient calculations of core-level binding energies.
- This advancement extends the applicability of GW theory to core-level spectroscopy (XPS).
- The massively parallel implementation supports computations for systems up to 100 atoms.
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