Scholarlink

<p>Detector and event visualization are crucial components of high-energy physics&#xa0;(HEP) experimental software. Virtual reality&#xa0;(VR) technologies and multimedia development platforms, such as Unity, offer enhanced display effects and flexible extensibility for visualization in HEP experiments. In this study, we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory&#xa0;(JUNO) experiment. This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces. The VR methodology facilitates an immersive exploration of the virtual environment in JUNO, enabling users to investigate the detector geometry, visualize event data, and tune the detector simulation and event reconstruction algorithms. Additionally, this approach supports applications in data monitoring, physics data analysis, and public outreach initiatives.</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

Unity-based virtual reality for detector and event visualization in JUNO experiment

  • 期刊论文

  • 发表日期：

    2026年2月5日

查看全文
  • Kai-Xuan Huang,
  • Tian-Zi Song,
  • Yu-Ning Su,
  • Cheng-Xin Wu,
  • Xue-Sen Wang,
  • Yu-Mei Zhang,
  • Zheng-Yun You

摘要

Detector and event visualization are crucial components of high-energy physics (HEP) experimental software. Virtual reality (VR) technologies and multimedia development platforms, such as Unity, offer enhanced display effects and flexible extensibility for visualization in HEP experiments. In this study, we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory (JUNO) experiment. This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces. The VR methodology facilitates an immersive exploration of the virtual environment in JUNO, enabling users to investigate the detector geometry, visualize event data, and tune the detector simulation and event reconstruction algorithms. Additionally, this approach supports applications in data monitoring, physics data analysis, and public outreach initiatives.