Automating the Next Level: High-throughput GW

High-throughput calculations can be seen as one of the key technologies in obtaining large datasets of materials properties. Performing these in an precise way (computationally correct and converged) requires already at the DFT level sophisticated scripts for job generation, execution, error handling and date processing. At the more accurate level of many-body perturbation theory the demands become even more stringent. Basically a ‘one parameter set fits all' approach does not work anymore and individual converged parameter-sets and computational settings need to be determined. We present the approaches developed to tackle this problem for GW calculations with the Pymatgen/Abipy framework. We discuss our approach of automatic convergence testing, dynamical test grid extension and data analysis. As a first application we calculate the quasi-particle spectrum of 100+ solids. This ensemble size allows for the statistically relevant extraction of correlations between converged input parameters and observables from the KS spectrum