重力レンズ解析による宇宙暗黒物質地図と深層学習の応用

白崎, 正人

doi:10.51094/jxiv.65

##article.authors##

白崎, 正人国立天文台研究力強化戦略室

DOI:

https://doi.org/10.51094/jxiv.65

キーワード:

宇宙暗黒物質、重力レンズ、深層学習、生成モデル、敵対的生成ネットワーク

抄録

大規模な天文観測データの解析により, 我々の宇宙には光で直接検出できない (あるいは非常に検出が難しい) 物質が存在することが示唆されている. そのような物質は宇宙暗黒物質と呼ばれ, 過去から現在まで宇宙の至る所に遍く存在する一方で, その存在は既存の物理学の範疇では説明できない. 暗黒物質の正体を解明するために, 暗黒物質が宇宙のどこにどれくらい集まっているか–暗黒物質地図–を観測的に明らかにすることは重要である. 光で観測することが難しい暗黒物質の地図を描くための有力な手法として, 重力レンズ解析が近年注目を集めている. 重力レンズ効果とは, 遠方にある銀河などの天体の像が, 観測者と天体の間に存在する物質の重力によって歪むという一般相対性理論によって予言される現象である. 現在, 世界各地で進む銀河撮像観測では, 重力レンズ効果により生じる銀河のわずかな歪みから視線方向にある暗黒物質の存在量を推定する重力レンズ解析が精力的に行われている. 本稿では, 現代宇宙論の概要, 重力レンズ解析の基礎的な事項をまとめ, 近年特に盛り上がりを見せている重力レンズ解析における深層学習の応用について, 筆者らの最近の研究内容を交えながら解説する.

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