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cond-mat.mtrl-sci2023
Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra
Hiroyuki Kumazoe, Kazunori Iwamitsu, Masaki Imamura +4
We analyzed the X-ray photoemission spectra (XPS) of carbon 1s states in graphene and oxygen-intercalated graphene grown on SiC(0001) using Bayesian spectroscopy. To realize highly…
cond-mat.mtrl-sci2023
Efficient NMR measurement and data analysis supported by the Bayesian inference : The case of the heavy fermion compound YbCo2Zn20
H. Ueda, S. Katakami, S. Yoshida +4
We propose a data-driven technique to infer microscopic physical quantities from nuclear magnetic resonance(NMR) spectra, in which the data size and quality required for the Bayesi…