Scalable multicomponent spectral analysis for high-throughput data annotation.

Orchestrating parametric fitting of multicomponent spectra at scale is an essential yet underappreciated task in high-throughput quantification of materials and chemical composition. We present a systematic approach compatible with high-performance computing infrastructures using the MapReduce model and task-based parallelization. Our approach is realized in a software, \textit{pesfit}, to enable efficient generation of high-quality data annotation and online spectral analysis as demonstrated using experimental materials characterization datasets.