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2022 年度 実績報告書

データ科学的方法による銀河宇宙のマルチスケール物理学の解明

研究課題

研究課題/領域番号 21J23611
配分区分補助金
研究機関名古屋大学

研究代表者

COORAY Suchetha  名古屋大学, 理学研究科, 特別研究員(DC1)

研究期間 (年度) 2021-04-28 – 2024-03-31
キーワードGalaxies / Magnetism / Machine Learning
研究実績の概要

Over the past year, my research has focused on three primary areas: the Galaxy Manifold and star formation history estimation. Utilizing unsupervised machine learning, I successfully identified two fundamental parameters that accurately represent galaxies, aligning with current understanding. Furthermore, I developed a method employing generative models to simulate star formation histories, enabling a better match with observations and advancing our comprehension of galaxy formation history. Additionally, I collaborated with the SKA-Japan Science working group on the cosmic magnetism project, exploring the observability of galactic magnetism through simulations and investigating alternative approaches to disentangle complex magnetic field structures.

現在までの達成度 (区分)
現在までの達成度 (区分)

1: 当初の計画以上に進展している

理由

At present, the findings from my Galaxy Manifold research have been documented in a forthcoming paper, which consolidates the results of the multi-wavelength analysis of local galaxies. The paper highlights the consistent outcomes obtained using unsupervised machine learning techniques and their implications for our understanding of galaxy evolution within the vast Universe. Simultaneously, I am in the final stages of preparing a comprehensive publication on my innovative method for star formation history estimation. This approach, leveraging generative models, has shown promising results in generating simulation-like histories that closely match observations, overcoming the limitations of observational data alone.

今後の研究の推進方策

With the upcoming publication on the Galaxy Manifold research, I aim to disseminate the findings widely within the scientific community, fostering discussions and encouraging collaborations in the field of galactic analysis. Additionally, I have established a strong network of esteemed researchers in galaxy formation and machine learning. Moving forward, I plan to leverage this network and collaborate on developing a machine learning algorithm for galaxy formation that integrates multi-wavelength and multi-epoch observations. Furthermore, I will actively engage with researchers from renowned institutions such as Stanford University to explore alternative probes and innovative approaches to accurately unravel the complexities associated with galactic magnetism.

  • 研究成果

    (14件)

すべて 2022 その他

すべて 国際共同研究 (1件) 雑誌論文 (1件) (うち査読あり 1件) 学会発表 (12件) (うち国際学会 2件、 招待講演 4件)

  • [国際共同研究] University of Arizona(米国)

    • 国名
      米国
    • 外国機関名
      University of Arizona
  • [雑誌論文] Wavelets and sparsity for Faraday tomography2022

    • 著者名/発表者名
      Cooray Suchetha、Takeuchi Tsutomu T、Ideguchi Shinsuke、Akahori Takuya、Miyashita Yoshimitsu、Takahashi Keitaro
    • 雑誌名

      Publications of the Astronomical Society of Japan

      巻: 75 ページ: S85~S96

    • DOI

      10.1093/pasj/psac052

    • 査読あり
  • [学会発表] Application of machine learning in Faraday tomography2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Autumn Annual Meeting of Astronomical Society of Japan
  • [学会発表] Disentangling the connection between present-day galaxies and their star formation histories2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Autumn Annual Meeting of Astronomical Society of Japan
  • [学会発表] Disentangling galaxy star formation histories2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      9th East Asian Numerical Astrophysics Meeting
    • 国際学会
  • [学会発表] Dimensionality Reduction to Understand Galaxies2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Data Science in Astronomy 2022 - Tokyo
  • [学会発表] A Data-driven Model of Galaxy Star Formation Histories2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Observational Cosmology Workshop 2022
  • [学会発表] Generative Modeling for Galaxy Star Formation Histories2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Rironkon Symposium 2022
  • [学会発表] Understanding Galaxies through Dimensionality Reduction2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Machine Learning in Astrophysics
    • 招待講演
  • [学会発表] Machine Learning-based Approach to Understanding Galaxies2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      IPMU Astro Lunch Seminar
    • 招待講演
  • [学会発表] Galaxy Manifold with SKA2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      SKA-Japan Webinar Series
    • 招待講演
  • [学会発表] Wavelets and Sparsity for Faraday Tomography2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      SKA-Japan Workshop 2022
    • 招待講演
  • [学会発表] Generative Model of Simulated Galaxies for Fitting Observed SEDs2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Spring Annual Meeting of Astronomical Society of Japan
  • [学会発表] Learning representations of galaxies from simulations and observations2022

    • 著者名/発表者名
      Suchetha Cooray
    • 学会等名
      Galaxy Formation and Evolution in the Data Science Era - Santa Barbara, USA
    • 国際学会

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公開日: 2023-12-25  

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