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The GAPS Project for Ultra-High Sensitivity Observation of Cosmic Ray Antiparticles in the Search for Dark Matter

Research Project

Project/Area Number 22K14065
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 15020:Experimental studies related to particle-, nuclear-, cosmic ray and astro-physics
Research InstitutionJapan Aerospace EXploration Agency

Principal Investigator

Masahiro Yamatani  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, 招聘職員 (80896275)

Project Period (FY) 2022-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2023: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2022: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Keywords反重陽子 / ダークマター探索 / 宇宙線 / 反粒子 / 気球 / 宇宙線物理
Outline of Research at the Start

地球に飛来する宇宙線は、宇宙形成過程やダークマターの理解における重要なプロープであり, 今日でもガンマ線や反粒子などを対象とした多様な宇宙線観測実験が行われている。通常, 宇宙線反重陽子数は極微少であるが、ダークマターが存在することでその数が2桁から3桁ほど増加する可能性が指摘されている。GAPSはこの宇宙線反重陽子を検出することでダークマターの間接的探索を行う。本研究は、機械学習をベースにした解析を取り込むことで、宇宙線反重陽子の発見感度を向上させる。2022年度に予定されている南極長期飛翔実験で得たデータに開発した解析手法を適用し, 宇宙線反重陽子の検出を目指す。

Outline of Final Research Achievements

We have significantly improved the understanding capability of cosmic ray antideuterons for the Antarctic balloon experiment GAPS. This progress was achieved by optimizing Boosted Decision Trees (BDT) and incorporating novel machine-learning methodologies, containing the augmentation of learning variables and the meticulous adjustment of learning parameters. Notably, this approach has demonstrated considerable usefulness in identifying antiprotons and antihelium. Furthermore, enhancements to the precision of velocity (β) reconstruction for low-energy antiparticles have effectively mitigated bias. Integrating features derived from Bragg curve fitting has also strengthened antideuterons' discrimination capability. Moreover, developing a machine learning framework has notably increased the efficiency of data analysis, concomitantly elevating both the celerity and accuracy of the analyses. These substantial strides represent a foundational achievement for prospective research endeavors.

Academic Significance and Societal Importance of the Research Achievements

ダークマターは宇宙の質量の大部分を占めるとされながら、その正体は未解明であり、宇宙の根本的な理解を深める上で非常に重要な意義を持つ。そのような課題を解決するには、ダークマターが関わるエネルギーの大きさ、既知物質との相互作用などに関する多種多様な仮説に基づく観測手法を用いた、多角的なアプローチを取ることが求められる。本実験の宇宙線反重陽子を用いたダークマターの間接探索実験は、これまで確認されなかったエネルギー領域をターゲットにしており、ダークマター探索実験の中でも重要な位置を占める。またこの研究は先端技術の開発を促進し、計測技術やデータ解析技術の向上をもたらす。

Report

(3 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • Research Products

    (4 results)

All 2023 2022

All Journal Article (2 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 2 results,  Open Access: 2 results) Presentation (2 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] New Particle Identification Approach with Convolutional Neural Networks in GAPS2023

    • Author(s)
      Masahiro YAMATANI, Yusuke NAKAGAMI, Hideyuki FUKE, Akiko KAWACHI, Masayoshi KOZAI, Yuki SHIMIZU, Tetsuya YOSHIDA
    • Journal Title

      Journal of Evolving Space Activities

      Volume: 1 Issue: 0 Pages: n/a

    • DOI

      10.57350/jesa.9

    • ISSN
      2758-1802
    • Related Report
      2022 Research-status Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Sensitivity of the GAPS experiment to low-energy cosmic-ray antiprotons2023

    • Author(s)
      F. Rogers, T. Aramaki, M. Yamatani, 他 (53人中47番目)
    • Journal Title

      Astroparticle Physics

      Volume: 145 Pages: 102791-102791

    • DOI

      10.1016/j.astropartphys.2022.102791

    • Related Report
      2022 Research-status Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Presentation] Antiparticles identification for the GAPS experiment2022

    • Author(s)
      M.Yamatani
    • Organizer
      RIKEN iTHEMS Dark Matter Workshop
    • Related Report
      2022 Research-status Report
    • Int'l Joint Research
  • [Presentation] New Particle Identification Approach with Convolutional Neural Network in GAPS2022

    • Author(s)
      Masahiro Yamatani
    • Organizer
      The 33rd International Symposium and Space Technology and Science
    • Related Report
      2022 Research-status Report
    • Int'l Joint Research

URL: 

Published: 2022-04-19   Modified: 2025-01-30  

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