Data Repository for: Machine-learning the spectral function of a hole in a quantum antiferromagnet

DOI10.5281/zenodo.7527378Zenodo7527378MaRDI QIDQ6707978

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 11 January 2023

Copyright license: No records found.

Description

The machine-learning dataset of 51^3 ~1.310^5density of states (DOS)ofa mobile hole in thet-t-t-Jmodel theoretically generated by usingthe self-consistent Bornapproximation in the three-dimensional parameter space of t [0.5, 0.5], t [0.5, 0.5] andJ [0.2, 1.0], with each parameter sampled on a 51-pointuniform grid. The dataset israndomly partitionedinto an 80/10/10 training (T), validation (V), and testing Tsplit. Note thateach DOSA() was calculated on a 1201-point uniform grid of [6t, 6t], thenit was resampled on a301-pointuniform gridfor the forward problem and on a 354-point uniform grid for the inverse problem. The dataset used in the inverse problem is limited to the parameter space oft [0.5, 0], t [0, 0.5] andJ [0.2, 1.0].To open the enclosed .npz files, use numpy.load() in python3.

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