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We propose a data-driven technique to infer microscopic physical quantitiesfrom nuclear magnetic resonance(NMR) spectra, in which the data size andquality required for the Bayesian inference are investigated. The $^{59}$Co-NMRmeasurement of YbCo$_2$Zn$_{20}$ single crystal generates complex spectra with28 peaks. By exploiting the site symmetry in the crystal structure, theisotropic Knight shift $K_{iso}$ and nuclear quadrupole resonance(NQR)frequency $\nu_Q$ were estimated to be $K_{iso} = 0.7822 \pm 0.0090 \%$, $\nu_Q= 2.008 \pm 0.016$ MHz ( T = 20 K, H $\simeq$ 10.2 T) by analyzing only 30 datapoints from one spectrum. The estimation of $\nu_Q$ is consistent with theprecise value obtained in the NQR experiment. Our method can significantlyreduce the measurement time and the computational cost of data analysis in NMRexperiments.

Efficient NMR measurement and data analysis supported by the Bayesian inference : The case of the heavy fermion compound YbCo2Zn20