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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Miki Bonacci, Junfeng Qiao, Nicola Spallanzani, Antimo Marrazzo, Giovanni Pizzi, Elisa Molinari, Daniele Varsano, Andrea Ferretti, Deborah Prezzi

2023npj Computational Materials19 citationsDOIOpen Access PDF

Abstract

Abstract The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, an algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

Topics & Concepts

Computer sciencePerturbation theory (quantum mechanics)WorkflowThroughputImplementationAlgorithmDensity functional theoryInterpolation (computer graphics)Wannier functionAutomationComputational scienceArtificial intelligencePhysicsEngineeringWirelessQuantum mechanicsDatabaseMotion (physics)Mechanical engineeringProgramming languageTelecommunicationsMachine Learning in Materials ScienceAdvanced Chemical Physics StudiesPhysics of Superconductivity and Magnetism
Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows | Litcius