Unsupervised classification of single-particle X-ray diffraction snapshots by spectral clustering

Single-particle experiments using X-ray Free Electron Lasers produce more than 105 snapshots per hour, consisting of an admixture of blank shots (no particle intercepted), and exposures of one or more particles. Experimental data sets also often contain unintentional contamination with different species. We present an unsupervised method able to sort experimental snapshots without recourse to templates, specific noise models, or user-directed learning. The results show 90% agreement with manual classification.