Tensor Decomposition of electron nano-spectroscopic data toward unempirical mapping of materials properties
| Project/Area Number |
18K04886
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 28030:Nanomaterials-related
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| Research Institution | Japan Atomic Energy Agency (2019-2020)
Nagoya University (2018) |
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Principal Investigator |
Tatsumi Kazuyoshi 国立研究開発法人日本原子力研究開発機構, 原子力科学研究部門 J－PARCセンター, 研究主幹 (00372532)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 非弾性中性子散乱 / ヒストグラムビン幅最適化 / ポアソン過程 / 実験計画 / 密度推定 / 中性子非弾性散乱 / ヒストグラム / 不均一ポアソン過程 / ビン幅最適化 / 測定時間最適化 / 高次元データ / ポアソン統計 / ビン幅 / 顕微電子分光 / 理論計算 / 行列分解 / テンソル分解 / EELS / STEM / 多変量解析 |
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| Outline of Final Research Achievements |
The purpose of this research is to statistically extract physically significant spectral information from high dimensional tensors of experimental spectral data. Due to the changes in my experimental environment, I targeted inelastic neutron scattering (INS) data which were not initially considered.
For histogram expression of the experimental INS intensity distribution, I applied a bin-widths optimization method to several experimental and phantom INS data sets. This method assumed an in-homogeneous Poisson process to generate the INS counts in a period of the energy and momentum space. The method was found to successfully extract the optimal bin-widths on the 4D axes. It was also found that the statistics was extrapolated to the data sets with different total counts and the investigator could infer the optimal bin-widths on them. This suggests that the method could be utilized to design the measurement time of INS experiments.
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| Academic Significance and Societal Importance of the Research Achievements |
J-PARC等のパルス中性子源を用いた中性子実験施設では、個々の中性子の検出をデータとして記録する。その頻度はポアソン統計に従う。一方、ポアソン統計に基づくヒストグラムのビン幅の最適化が脳神経科学分野で開発され、非弾性中性子散乱(INS)を模擬したデータにおいても適用された。本研究では、INS実験データでその有用性を実証し以下の活用が示された：①データに応じた最適ビン幅より、INS強度分布の微細構造の有意性を検視する。②微細構造を実験的に取得するのに必要な計測時間をオンラインで把握し、最適な計測時間で実験を終了する。
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Report
(4 results)
Research Products
(4 results)
