Bayesian theory for spectral deconvolution and its expansion

2014 Fiscal Year Final Research Report

• Project/Area Number: 24654118
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Mathematical physics/Fundamental condensed matter physics
• Research Institution: The University of Tokyo
• Principal Investigator: OKADA Masato 東京大学, 新領域創成科学研究科, 教授 (90233345)
• Co-Investigator(Renkei-kenkyūsha): SASAKI Takehiko 東京大学, 大学院新領域創成科学研究科, 准教授 (90242099) ; MIZOKAWA Takashi 東京大学, 大学院新領域創成科学研究科, 准教授 (90251397)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 分光学 / スペクトル分解 / ベイズ推論 / モデル選択 / 有効ハミルトニアン

Outline of Final Research Achievements

The purpose of this project is to propose the Bayesian theory for spectral deconvolution based on the framework of the Bayesian statistics. By using the Bayesian statistics, we can treat the model selection problem, which selects the optimal number of peak from the given data. The introduction of Bayesian statistics to the field of spectroscopy give the impact to the other fields. The framework of the model selection leads to the selection of parameter for the model hamiltonian from the observed data.

Free Research Field

情報統計力学