Scholarlink

Abstract <p>The DEAP-3600 experiment uses a modern coordinate reconstruction algorithm that utilizes machine learning. This algorithm performed well compared to likelihood-based approaches. Here we validate our neural network based algorithm on data obtained using <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11450_2025_3567_Article_IEq5.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">\({}^{241}\)</EquationSource> <!--NuclPhys2570028Grobov-m5--> </InlineEquation>Am–<InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11450_2025_3567_Article_IEq6.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="8" /> </InlineMediaObject> <EquationSource Format="TEX">\({}^{9}\)</EquationSource> <!--NuclPhys2570028Grobov-m6--> </InlineEquation>Be radioactive source. The results obtained confirm algorithm validity.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Validating Position Reconstruction Algorithm with \({}^{\mathbf{241}}\)Am–\({}^{\mathbf{9}}\)Be Neutron Source in DEAP-3600

  • 期刊论文

  • 发表日期：

    2025年4月1日

查看全文
  • A. V. Grobov,
  • A. I. Ilyasov

摘要

Abstract

The DEAP-3600 experiment uses a modern coordinate reconstruction algorithm that utilizes machine learning. This algorithm performed well compared to likelihood-based approaches. Here we validate our neural network based algorithm on data obtained using \({}^{241}\) Am– \({}^{9}\) Be radioactive source. The results obtained confirm algorithm validity.