| Project/Area Number |
16K17654
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Astronomy
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| Research Institution | Japan Aerospace EXploration Agency |
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Principal Investigator |
Tasker Elizabeth 国立研究開発法人宇宙航空研究開発機構, 宇宙科学研究所, 准教授 (40620373)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | catalogue / exoplanet / planet formation / neural networks / machine learning / astrophysics / planetary science / exoplanet: properites / numerical methods / catalogues / neural network / exoplanets / 理論天文学 / 惑星 |
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| Outline of Final Research Achievements |
This research explored the use of neural networks to identify trends in the exoplanet archive. Originally designed to explore the increase in planetary radius due to accretion, greater success was achieved with imputing missing properties (including planet mass and radius) based on the multidimensional density function found by the neural network. Neural networks excel at finding trends in multidimensional data that are difficult to identify through plotting or other means. Such interpolation is necessary for properties that cannot be measured through observations.
A second paper developed a simple climate code that could run on a web-browser to allow users to explore how small changes to an Earth-like planet could hav a major impact on the environment. This also utalised a neural network to render the planet and bring it to a wider audience. A third paper used the image identification of neural networks to develop an automatic crater counter on the surface of Mars.
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| Academic Significance and Societal Importance of the Research Achievements |
While many exoplanets have been found, the measured properties of individual planets is small. This situation will not change, as observation techniques are sensitive to particular properties and orbits. To understand the exoplanet catalogue, techniques must be developed to impute missing values.
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