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Analysis Method of Laser-accelerated Sub-GeV-class Proton Tracks in Emulsion Cloud Chamber using Deep Learning Technique

https://repo.qst.go.jp/records/83746
https://repo.qst.go.jp/records/83746
f5b065ec-2e08-4828-bed1-abb290b9f2f1
Item type 会議発表用資料 / Presentation(1)
公開日 2021-10-26
タイトル
タイトル Analysis Method of Laser-accelerated Sub-GeV-class Proton Tracks in Emulsion Cloud Chamber using Deep Learning Technique
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_c94f
資源タイプ conference object
アクセス権
アクセス権 metadata only access
アクセス権URI http://purl.org/coar/access_right/c_14cb
著者 Tanabe, Hiroyuki

× Tanabe, Hiroyuki

WEKO 1009462

Tanabe, Hiroyuki

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Takafumi, Asai

× Takafumi, Asai

WEKO 1009463

Takafumi, Asai

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Masato, Kanasaki

× Masato, Kanasaki

WEKO 1009464

Masato, Kanasaki

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Satoshi, Jinno

× Satoshi, Jinno

WEKO 1009465

Satoshi, Jinno

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Nobuko, Kitagawa

× Nobuko, Kitagawa

WEKO 1009466

Nobuko, Kitagawa

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Tomoya, Yamauchi

× Tomoya, Yamauchi

WEKO 1009467

Tomoya, Yamauchi

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Kunihiro, Morishima

× Kunihiro, Morishima

WEKO 1009468

Kunihiro, Morishima

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Yuji, Fukuda

× Yuji, Fukuda

WEKO 1009469

Yuji, Fukuda

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Tanabe, Hiroyuki

× Tanabe, Hiroyuki

WEKO 1009470

en Tanabe, Hiroyuki

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Takafumi, Asai

× Takafumi, Asai

WEKO 1009471

en Takafumi, Asai

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Yuji, Fukuda

× Yuji, Fukuda

WEKO 1009472

en Yuji, Fukuda

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抄録
内容記述タイプ Abstract
内容記述 In the interaction between intense laser and the target matter, near-100-MeV proton acceleration is demonstrated. It offers that the potential to realize a energy saving compact particle accelerators in the future. To understand the acceleration process mechanism, precise measurement of both the energy spectrum and the two-dimensional distribution is required. Against this background, we have developed a new measurement method for laser-accelerated sub-GeV-class protons using the nuclear emulsion. Based on the Multiple Coulomb Scattering (MCS) method in an Emulsion Cloud Chamber (ECC), which is a stack of nuclear emulsion films and scatterer plates, the incident energies were inversely evaluated by the scattering angle. The proof-of-principle simulation has been conducted with GEANT-4 Monte Carlo code. To analyze the proton tracks, we have applied the deep learning technique to obtain the incident energy from the amount of MCS in each layer of nuclear emulsion. The median of energy determination coefficient is 0.73 with ramp activation function. The coefficients of the present studies are equal or smaller than the conventional regression model, and we are trying to improve the determination coefficient by optimization of the calculation conditions.
会議概要(会議名, 開催地, 会期, 主催者等)
内容記述タイプ Other
内容記述 ICMaSS2021
発表年月日
日付 2021-11-05
日付タイプ Issued
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