Towards automating analysis of nonequilibrium X-ray Photon Correlation Spectroscopy with acquisition rate-limited time resolution

Non-equilibrium behavior is characteristic for many systems studied with X-ray Photon Correlation Spectroscopy (XPCS). Analysis of non-equilibrium XPCS data often involves manual iterative binning of quasi-equilibrium regions in an attempt to reach acceptable signal-to-noise ratios in the intensity-intensity correlation functions. Such approach often leads to loss of temporal resolution as well as accumulation of systematic errors in parameters quantifying the dynamics. In this talk, I present a new approach for automating the analysis of XPCS data that allows to preserve the temporal resolution set by the experimental acquisition rate. The analysis workflow involves use of denoising autoencoders, scaled to an arbitrary input size, algorithmic adjustment of dynamics parameters' bounds and estimation of analysis uncertainty beyond parameters' variances.