arXiv subjects

Yu-Mei Zhang

Publications and source records attributed to Yu-Mei Zhang.

6 recordsLinked to original sources

arXiv2025

An event visualization software based on Phoenix for the CEPC experiment

In high-energy physics~(HEP) experiments, visualization software plays a pivotal role in detector design, offline software development, and event data analysis. The visualization tools integrate detailed detector geometry with complex event data models, providing the researchers with invaluable insights into experimental results. Phoenix is an emerging general-purpose visualization platform for the current and next-generation HEP experiments. In this study, we develop an event display software based on Phoenix for the CEPC experiment. It offers necessary functionalities for visualizing detector geometries and displaying event data, allowing the researchers to optimize detector design, test simulation and reconstruction algorithms, and analyze event data in a visualized way. Additionally, we discuss the future applications of the event display software, including its usage in online monitoring and the potential to build virtual reality projects for enhanced data visualization.

hep-ex↗

arXiv2025

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

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 offline software and provides necessary data conversion interfaces. The VR methodology facilitates an immersive exploration of the virtual environment in JUNO, enabling users to investigate 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.

physics.ins-det↗

arXiv2025

Detector description conversion and visualization in Unity for high energy physics experiments

While visualization plays a crucial role in high-energy physics (HEP) experiments, the existing detector description formats including Geant4, ROOT, GDML, and DD4hep face compatibility limitations with modern visualization platforms. This paper presents a universal interface that automatically converts these four kinds of detector descriptions into FBX, an industry standard 3D model format which can be seamlessly integrated into advanced visualization platforms like Unity. This method bridges the gap between HEP instrumental display frameworks and industrial-grade visualization ecosystems, enabling HEP experiments to harness rapid technological advancements. Furthermore, it lays the groundwork for the future development of additional HEP visualization applications, such as event display, virtual reality, and augmented reality.

hep-ex↗

arXiv2022

Method for detector description transformation to Unity and application in BESIII

Detector and event visualization are essential parts of the software used in high-energy physics (HEP) experiments. Modern visualization techniques and multimedia production platforms such as Unity provide impressive display effects and professional extensions for visualization in HEP experiments. In this study, a method for automatic detector description transformation is presented, which can convert the complicated HEP detector geometry from GDML in offline software to 3D modeling in Unity. The method was successfully applied in the BESIII experiment and can be further developed into applications such as event displays, data monitoring, or virtual reality. It has great potential in detector design, offline software development, physics analysis, and outreach for next-generation HEP experiments as well as applications in nuclear techniques for the industry.

physics.ins-det↗

arXiv2022

Improving the machine learning based vertex reconstruction for large liquid scintillator detectors with multiple types of PMTs

Precise vertex reconstruction is essential for large liquid scintillator detectors. A novel method based on machine learning has been successfully developed to reconstruct the event vertex in JUNO previously. In this paper, the performance of machine learning based vertex reconstruction is further improved by optimizing the input images of the neural networks. By separating the information of different types of PMTs as well as adding the information of the second hit of PMTs, the vertex resolution is improved by about 9.4 % at 1 MeV and 9.8 % at 11 MeV, respectively.

physics.ins-det↗

arXiv2021

A method for sharing dynamic geometry information in studies on liquid-based detectors

The liquid-based detectors are widely used in particle and nuclear physics experiments. Due to the fixed way of constructing geometry in detector simulation such as Geant4, it is usually difficult to describe the non-uniformity of liquid in detectors. We propose a method based on GDML and tessellated detector description to share the detector geometry information between Computational Fluid Dynamics (CFD) simulation software and detector simulation software. The method makes it possible to study the impact of liquid flow and non-uniformity on some key performance of the liquid-based detectors, such as event vertex reconstruction resolution. It will also be helpful in detector design and performance optimization.

physics.ins-det↗