Machine Learning approach to muon spectroscopy analysis
T. Tula,
G. Möller,
J. Quintanilla
et al.
Abstract:In recent years, Artificial Intelligence techniques have proved to be very successful when applied to problems in physical sciences.Here we apply an unsupervised Machine Learning (ML) algorithm called Principal Component Analysis (PCA) as a tool to analyse the data from muon spectroscopy experiments. Specifically, we apply the ML technique to detect phase transitions in various materials. The measured quantity in muon spectroscopy is an asymmetry function, which may hold information about the distribution of t… Show more
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