| Project/Area Number |
22KJ1537
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| Project/Area Number (Other) |
21J23611 (2021-2022)
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| Research Category |
Grant-in-Aid for JSPS Fellows
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| Allocation Type | Multi-year Fund (2023)
Single-year Grants (2021-2022) |
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| Section | 国内 |
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| Review Section |
Basic Section 15010:Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics
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| Research Institution | National Astronomical Observatory of Japan (2023)
Nagoya University (2021-2022) |
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Principal Investigator |
COORAY Suchetha 国立天文台, 科学研究部, 特別研究員(PD)
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| Project Period (FY) |
2023-03-08 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 2023: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2022: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2021: ¥800,000 (Direct Cost: ¥800,000)
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| Keywords | Galaxy formation / Cosmology / Machine learning / Galaxies / Magnetism / Machine Learning |
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| Outline of Research at the Start |
Propose a novel approach to develop a comprehensive model for the multi-scale physics of galaxies. Utilize a combination of multi-wavelength emissions, spatial information, and magnetic field data, augmented by advanced unsupervised machine learning techniques, to extract valuable insights from observational data. The primary objective is to establish a unified model that incorporates magnetism information alongside the processes influencing star formation. This endeavor aims to bridge gaps in our understanding of galaxies, enabling a more holistic view of their formation and evolution.
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| Outline of Annual Research Achievements |
This research invloves building a data-driven model of galaxy formation. Key question include answering the connection betweek galaxies and their host dark matter halos, what is controlling the formation of stars, and what is driving the diversity of oberved galaxies from the past, current, and future galaxy surveys. Answering there question help us understand how our own galaxy Milky Way, and ultimately Earth formed and evolved. Understanding galaxies is also invaluable for understanding the cosmology as properties and their spatial distributions are key probes. Therefore a complete understanding of multi-scale physics is necessary. As for now, we do not have a suffiecnt model coming from first principles. Therefore, we aim to build a data-driven model as a first step.
Over the past year, my research has focused on building a new model of dust attenuation, which is necessary to understand the properties of galaxies more accurately from observations. I am now combining the dust model with a new galaxy formation model that understands the connection between the galaxy properties and dark matter. This will allow for more accurate simualtion of galaxies in the universe. In addition, I have made significant progress towards the goal of the project by building the network with foreign institutions. Consequently, that has allowed me to obtain a postdoctoral fellowship position at Stanford University after the period of the JSPS Fellowship. I will be further developing the new galaxy formation model at Stanford.
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