[M-GI33] データ駆動地球惑星科学

[MGI33-P02] Bayesian modeling of the equation-of-state by integration of various data sets for liquid iron in Earth’s outer core

*松村 太郎次郎¹、桑山 靖弘²、上木 賢太³、桑谷 立³、安藤 康伸¹、永田 賢二⁴、伊藤 伸一⁵、長尾 大道⁵ (1.国立研究開発法人産業技術総合研究所、2.東京大学大学院理学系研究科、3.国立研究開発法人海洋研究開発機構、4.国立研究開発法人物質・材料研究機構、5.東京大学地震研究所 )

Bayesian modeling of the equation-of-state (EoS) was demonstrated to constrain P-wave velocity (V_P) and density (ρ) of liquid iron under Earth’s outer-core conditions. We collected six data sets obtained by high-pressure (P) and high-temperature (T) experiments and ab initio molecular dynamics simulations in previous works. These data sets were integrated into one to estimate the parameters of EoS. However, as the type of observed data depends on the approach, integrated data set includes some unobserved data. To analyze such data set, we performed an analysis based on Bayesian inference. Our analysis successfully estimated the posterior probability distribution of the parameters and unobserved data by using the Hamiltonian Monte Carlo method. These posterior probability distributions enable us to calculate P– V_P andP–ρ profiles of liquid iron along the adiabatic P–T profile together with the associated credible intervals. Bayesian modeling of the EoS enables estimation of EoS’s parameters, integration of data sets that include unobserved data and evaluation of uncertainty ranges of physical properties, such as V_P and ρ, which are important for comparison with seismological properties of the core.