[M-TT27] 地球惑星科学データ解析の新展開：データ駆動型アプローチ

[MTT27-01] MORB全岩組成からの溶融度とマントル原岩組成の同時推定:地球化学へのデータ駆動型解析の応用

*桑谷 立¹、永田 賢二²、赤穂 昭太郎³、岩森 光¹ (1.国立研究開発法人　海洋研究開発機構、2.東京大学、3.国立研究開発法人　産業技術総合研究所)

キーワード：データ駆動、ベイズ推論、スパースモデリング、マルコフ連鎖モンテカルロ法

Geochemical data sets, such as major, trace and isotopic compositions, preserve precious information about various physical and chemical processes. For example, bulk compositions of igneous rocks directly reflect melting of original rocks, magma mixing and rock-fluid interaction in the earth's interior. However, it has been still difficult to extract physical and chemical processes quantitatively due to many unknown factors and insufficient quality of data sets. Recently, many sophisticated data-driven methodologies have been proposed to extract useful information from high-dimensional data sets in information sciences. In this presentation, we will briefly overview data-driven analytical technologies and introduce an application to simultaneous estimation of melting degrees and a mantle source composition from MORB bulk compositions based on Bayesian estimation and Markov chain Monte Carlo (MCMC) optimization.