Many-body perturbation theory vs. density functional theory: A systematic benchmark for band gaps of solids
arXiv:2508.05247 · doi:10.1038/s41524-025-01855-4
Abstract
We benchmark many-body perturbation theory against density functional theory (DFT) for the band gaps of solids. We systematically compare four variants using the Godby-Needs plasmon-pole approximation (-PPA), full-frequency quasiparticle (QP), full-frequency quasiparticle self-consistent (QS), and QS augmented with vertex corrections in (QS) against the currently best performing and popular density functionals mBJ and HSE06. Our results show that -PPA calculations offer only a marginal accuracy gain over the best DFT methods, however at a higher cost. Replacing the PPA with a full-frequency integration of the dielectric screening improves the predictions dramatically, almost matching the accuracy of the QS. The QS removes starting-point bias, but systematically overestimates experimental gaps by about . Adding vertex corrections to the screened Coulomb interaction, i.e., performing a QS calculation, eliminates the overestimation, producing band gaps that are so accurate that they even reliably flag questionable experimental measurements.
References in corpus (38)
- Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials
- Advanced capabilities for materials modelling with Quantum ESPRESSO
- Optimized norm-conserving Vanderbilt pseudopotentials
- The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table
- Yambo: an \textit{ab initio} tool for excited state calculations
- BerkeleyGW: A Massively Parallel Computer Package for the Calculation of the Quasiparticle and Optical Properties of Materials and Nanostructures
- Libxc: a library of exchange and correlation functionals for density functional theory
- Quasiparticle self-consistent method; a basis for the independent-particle approximation
- Machine learning modeling of superconducting critical temperature
- A better measure of relative prediction accuracy for model selection and model estimation
- GPAW: An open Python package for electronic-structure calculations
- Ab-initio Prediction of Conduction Band Spin Splitting in Zincblende Semiconductors
- Electron-Phonon Interaction in Tetrahedral Semiconductors
- Cubic scaling : towards fast quasiparticle calculations
- Adequacy of Approximations in GW Theory
- Questaal: a package of electronic structure methods based on the linear muffin-tin orbital technique
- Many-body perturbation theory using the density-functional concept: beyond the GW approximation
- Prediction of Ambient Pressure Conventional Superconductivity above 80K in Thermodynamically Stable Hydride Compounds
- Comparing electron-phonon coupling strength in diamond, silicon and silicon carbide: First-principles study
- Electronic structure of Na, K, Si, and LiF from self-consistent solution of Hedin's equations including vertex corrections
- Electronic structure of alkaline earth and post-transition metal oxides
- Self-consistent solution of Hedin's equations: semiconductors/insulators
- Accurate energy bands calculated by the hybrid quasiparticle self-consistent GW method implemented in the ecalj package
- Density functional theory study of the electronic structure of fluorite CuSe
- QS: Quasiparticle Self consistent with ladder diagrams in
- All-electron quasi-particle self-consistent band structures for SrTiO including lattice polarization corrections in different phase
- An Optimally-Tuned Starting Point for Single-Shot Calculations of Solids
- Optical response and band structure of LiCoO2 including electron-hole interaction effects
- Self-consistent GW method: O(N) algorithm for polarizability and self energy
- Full versus quasi-particle self consistency in vertex corrected GW approaches
- Frequency dependence in GW made simple using a multi-pole approximation
- Hydrogen Diffusion in Magnesium Using Machine Learning Potentials: a comparative study
- Electron-phonon coupling from GW perturbation theory: Practical workflow combining BerkeleyGW, ABINIT, and EPW
- Efficient full frequency GW for metals using a multipole approach for the dielectric screening
- Deep learning of spectra: Predicting the dielectric function of semiconductors
- Beyond quasi-particle self-consistent for molecules with vertex corrections
- Modelling complex proton transport phenomena -- Exploring the limits of fine-tuning and transferability of foundational machine-learned force fields
- Band gaps and phonons of quasi-bulk rocksalt ScN