Machine-learning test of the single-ion model for dd excitations in cuprates

2026/07/17 by Maryia Zinouyeva, Leonardo Martinelli, Riccardo Arpaia +12
#cond-mat.str-el

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Abstract

We investigate dd excitations in Resonant Inelastic X-ray Scattering spectra of YBa₂Cu₃O₆ and La₂CuO₄ using the local single-ion model. The data are analyzed by conventional global fitting and by a convolutional neural network trained within the same theoretical framework. For YBa₂Cu₃O₆, the excited state energies obtained with the two methods coincide, leading to the xy, 3z²-r², xz/yz sequence for increasing energy. This result validates the use of machine learning tools for the analysis of RIXS spectra dominated by dd excitations. By contrast, for La₂CuO₄, the two methods do not converge to a single solution, revealing the limitations of the single-ion model in describing dd excitations in cuprates and pointing to the role of additional contributions beyond a purely local picture in shaping high-energy excitations.

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