论文标题

贝叶斯对莫斯鲍尔光谱的哈密顿选择的推断

Bayesian Inference on Hamiltonian Selections for Mössbauer Spectroscopy

论文作者

Moriguchi, Ryota, Tsutsui, Satoshi, Katakami, Shun, Nagata, Kenji, Mizumaki, Masaichiro, Okada, Masato

论文摘要

Mössbauer光谱法提供了与材料中电子状态相关的知识,已应用于凝聚态物理和材料科学等各个领域。在基于最小二乘拟合的常规光谱分析中,材料中的超精细相互作用是根据观察到的光谱的形状确定的。在常规的光谱分析中,很难讨论超细相互作用的有效性和估计值。我们提出了一种基于贝叶斯推断的频谱分析方法,以选择超细相互作用和莫斯鲍尔参数的估计。通过比较可能的哈密顿人的贝叶斯自由能,选择了适当的哈密顿量。我们已经估计了Mössbauer参数,并通过置信区间计算每个Mössbauer参数的后验分布来评估其估计值。我们还讨论了光谱分析的准确性,以阐明数值实验的噪声强度依赖性。

Mössbauer spectroscopy, which provides knowledge related to electronic states in materials, has been applied to various fields such as condensed matter physics and material sciences. In conventional spectral analyses based on least-square fitting, hyperfine interactions in materials have been determined from the shape of observed spectra. In conventional spectral analyses, it is difficult to discuss the validity of the hyperfine interactions and the estimated values. We propose a spectral analysis method based on Bayesian inference for the selection of hyperfine interactions and the estimation of Mössbauer parameters. An appropriate Hamiltonian has been selected by comparing Bayesian free energy among possible Hamiltonians. We have estimated the Mössbauer parameters and evaluated their estimated values by calculating the posterior distribution of each Mössbauer parameter with confidence intervals. We have also discussed the accuracy of the spectral analyses to elucidate the noise intensity dependence of numerical experiments.

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