2021 Fiscal Year Annual Research Report
A Data Scientific Approach to Elucidate Multi-scale Physics of Galaxies in the Cosmos
| Project/Area Number |
21J23611
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| Allocation Type | Single-year Grants |
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| Research Institution | Nagoya University |
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Principal Investigator |
COORAY Suchetha 名古屋大学, 理学研究科, 特別研究員(DC1)
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| Project Period (FY) |
2021-04-28 – 2024-03-31
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| Keywords | Galaxies / Magnetism |
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| Outline of Annual Research Achievements |
This year, I have developed the ideas on the Galaxy Manifold, where I have incorporated various galaxy physical properties and their time evolution. The Galaxy Manifold is the fundamental quantity that relates different physical properties of galaxies and was identifies from data using advanced statistical techniques. The use of simulations was also explored. The papers are in preparation. Additionally, a new Faraday tomography technique was developed, which uses the ideas of a group of functions known as wavelets. The new method performs better than the previously published works. The paper describing it was submitted. The code for calculation was also made public.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The research on observing cosmic magnetism has progressed faster than expected where I was able to develop a new method (not originally planned). As a result, preparation of papers on the Galaxy Manifold has been slightly delayed. Overall, the progress is steady.
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| Strategy for Future Research Activity |
Firstly, I will focus on completing the current works and publishing them in reputed academic journals. Thereafter, I plan to seriously consider the use of simulation data (already begun) for the ideas of Galaxy Manifold. The use of simulations will allow us to compare the results with the current understanding of ga;laxy evolution. Additionally, simulations allow us to traverse the time evolution of galaxies, which is not possible with just observational data. Apart from from the Galaxy Manifold study, I will implement machine learning type approaches to extract physical properties of galaxies from observed Faraday rotation measurement studies. This will be a step forward in unifying the understanding of galaxies from electromagnetic radiation and from magnetic imprints.
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Research Products
(9 results)
