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2019 Fiscal Year Final Research Report

The identification and distribution of warm dark matter subhalos

Research Project

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Project/Area Number 17K14271
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Particle/Nuclear/Cosmic ray/Astro physics
Research InstitutionThe University of Tokyo

Principal Investigator

Han Jiaxin  東京大学, カブリ数物連携宇宙研究機構, 客員准科学研究員 (50791456)

Project Period (FY) 2017-04-01 – 2020-03-31
Keywordsdark matter halo / subhalo / numerical simulation / dynamical model
Outline of Final Research Achievements

The main matter content of the Universe is in the form of the so-called dark matter, that is invisible to us but affects the structure of the Universe through its gravitational effect. Although the nature of dark matter is still unknown, computer simulations can tell us that dark matter in the Universe tend to exist in dense clumps called dark matter halos, that contain plenty of subclumps called subhalos. This project aims at studying the distribution of dark matter on these halo and subhalo scales, to shed light on the nature of dark matter. We first develop a novel computer program to extract subhalos from simulations, and then study various statistical properties of these halos and subhalos. We have found the largescale distribution of halos cares about their internal structures in a complex way, while the distribution and motion of subhalos inside each halo follow universal profiles. We have used these universal profiles to accurately map out the dark matter mass in our galaxy.

Free Research Field

distribution of dark matter around halo scales

Academic Significance and Societal Importance of the Research Achievements

本研究で開発したサブハローを同定するアルゴリズムは、この種のアルゴリズムの中で最も信頼性の高いアルゴリズムの一つであり、重力レンズ効果を用いた観測結果と数値シミュレーションにおけるサブハローの分布に関しての相違を明らかにした。また、機械学習を用いることで、本研究で初めてハローの内部構造と大規模構造の相関関係が、従来考えられていたよりも複雑であることも明らかにした。それ以外にもハローの中のサブハローの分布を詳細に調べることで、サテライト銀河を用いたハロー質量の計測手法を開発し、ミルキーウェイの質量を計測する新しい手法の開発に成功した。この手法は、従来の手法に比べてより精度の高い測定を可能にした。

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Published: 2021-02-19  

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