arXiv subjects

Jiaheng Zou

Publications and source records attributed to Jiaheng Zou.

10 recordsLinked to original sources

arXiv2025

Multi-threaded Simulation Software for the JUNO Experiment

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose experiment under construction in southern China. JUNO aims to determine the neutrino mass ordering and precisely measure the neutrino oscillation parameters by detecting reactor neutrinos from nuclear power plants. In addition to reactor neutrinos, JUNO can study atmospheric neutrinos, solar neutrinos, geo-neutrinos, supernova burst neutrinos, the Diffuse Supernova Neutrino Background (DSNB), and nucleon decay, covering an energy range from keV to TeV. JUNO consists of a 20 kton liquid scintillator detector, equipped with 17,612 20-inch PMTs and 25,600 3-inch PMTs, achieving a 3\% energy resolution (at 1~MeV). Precise simulation plays a crucial role in the experiment. Developed using the SNiPER framework and Geant4 toolkit, the JUNO simulation software is a key component of the JUNO offline software (JUNOSW). The large detector size and the broad energy range of interest pose challenges for detector simulation in terms of CPU time and memory consumption. As the computing nodes shift to include multiple integrated CPU cores, traditional single-threaded computing model can lead to large memory footprints and inefficient use of system resources. Multi-threading on many-core architectures can significantly improve resource utilization. This paper introduces the design and implementation of multi-threaded simulation software for the JUNO experiment.

physics.ins-det↗

arXiv2024

CEPC-on-Gaussino: an application of Gaussino simulation framework for CEPC experiment

The Circular Electron Positron Collider (CEPC) is a future Higgs factory to measure the Higgs boson properties. Like the other future experiments, the simulation software plays a crucial role in CEPC for detector designs, algorithm optimization and physics studies. Due to similar requirements, the software stack from the Key4hep project has been adopted by CEPC. As the initial application of Key4hep, a simulation framework has been developed for CEPC based on DD4hep, EDM4hep and k4FWCore since 2020. However, the current simulation framework for CEPC lacks support for the parallel computing. To benefit from the multi-threading techniques, the Gaussino project from the LHCb experiment has been chosen as the next simulation framework in Key4hep. This contribution presents the application of Gaussino for CEPC. The development of the CEPC-on-Gaussino prototype will be shown and the simulation of a tracker detector will be demonstrated.

physics.ins-det↗

arXiv2024

Muon/Pion Identification at BESIII based on Variational Quantum Classifier

In collider physics experiments, particle identification (PID), i. e. the identification of the charged particle species in the detector is usually one of the most crucial tools in data analysis. In the past decade, machine learning techniques have gradually become one of the mainstream methods in PID, usually providing superior discrimination power compared to classical algorithms. In recent years, quantum machine learning (QML) has bridged the traditional machine learning and the quantum computing techniques, providing further improvement potential for traditional machine learning models. In this work, targeting at the $μ^{\pm} /π^{\pm}$ discrimination problem at the BESIII experiment, we developed a variational quantum classifier (VQC) with nine qubits. Using the IBM quantum simulator, we studied various encoding circuits and variational ansatzes to explore their performance. Classical optimizers are able to minimize the loss function in quantum-classical hybrid models effectively. A comparison of VQC with the traditional multiple layer perception neural network reveals they perform similarly on the same datasets. This illustrates the feasibility to apply quantum machine learning to data analysis in collider physics experiments in the future.

hep-ex↗

arXiv2023

The Key4hep software stack: Beyond Future Higgs factories

The Key4hep project aims to provide a turnkey software solution for the full experiment lifecycle, based on established community tools. Several future collider communities (CEPC, CLIC, EIC, FCC, and ILC) have joined to develop and adapt their workflows to use the common data model EDM4hep and common framework. Besides sharing of existing experiment workflows, one focus of the Key4hep project is the development and integration of new experiment independent software libraries. Ongoing collaborations with projects such as ACTS, CLUE, PandoraPFA and the OpenDataDector show the potential of Key4hep as an experiment-independent testbed and development platform. In this talk, we present the challenges of an experiment-independent framework along with the lessons learned from discussions of interested communities (such as LUXE) and recent adopters of Key4hep in order to discuss how Key4hep could be of interest to the wider HEP community while staying true to its goal of supporting future collider designs studies.

hep-ex↗

arXiv2023

Key4hep: Progress Report on Integrations

Detector studies for future experiments rely on advanced software tools to estimate performance and optimize their design and technology choices. The Key4hep project provides a flexible turnkey solution for the full experiment life-cycle based on established community tools such as ROOT, Geant4, DD4hep, Gaudi, podio and spack. Members of the CEPC, CLIC, EIC, FCC, and ILC communities have joined to develop this framework and have merged, or are in the progress of merging, their respective software environments into the Key4hep stack. These proceedings will give an overview over the recent progress in the Key4hep project: covering the developments towards adaptation of state-of-the-art tools for simulation (DD4hep, Gaussino), track and calorimeter reconstruction (ACTS, CLUE), particle flow (PandoraPFA), analysis via RDataFrame, and visualization with Phoenix, as well as tools for testing and validation.

hep-ex↗

arXiv2023

Simulation Software of the JUNO Experiment

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose experiment, under construction in southeast China, that is designed to determine the neutrino mass ordering and precisely measure neutrino oscillation parameters. Monte Carlo simulation plays an important role for JUNO detector design, detector commissioning, offline data processing, and physics processing. The JUNO experiment has the world's largest liquid scintillator detector instrumented with many thousands of PMTs. The broad energy range of interest, long lifetime, and the large scale present data processing challenges across all areas. This paper describes the JUNO simulation software, highlighting the challenges of JUNO simulation and solutions to meet these challenges, including such issues as support for time-correlated analysis, event mixing, event correlation and handling the simulation of many millions of optical photons.

hep-ex↗

arXiv2021

Event vertex and time reconstruction in large volume liquid scintillator detector

Large-volume liquid scintillator detectors with ultra-low background levels have been widely used to study neutrino physics and search for dark matter. Event vertex and event time are not only useful for event selection but also essential for the reconstruction of event energy. In this study, four event vertex and event time reconstruction algorithms using charge and time information collected by photomultiplier tubes were analyzed comprehensively. The effects of photomultiplier tube properties were also investigated. The results indicate that the transit time spread is the main effect degrading the vertex reconstruction, while the effect of dark noise is limited. In addition, when the event is close to the detector boundary, the charge information provides better performance for vertex reconstruction than the time information.

physics.ins-det↗

arXiv2021

Improving the energy uniformity for large liquid scintillator detectors

It is challenging to achieve high precision energy resolution for large liquid scintillator detectors. Energy non-uniformity is one of the main obstacles. To surmount it, a calibration-data driven method was developed previously to reconstruct event energy in the JUNO experiment. In this paper, we investigated the choice of calibration sources thoroughly, optimized the calibration positions and corrected the residual detector azimuthal asymmetry. All these efforts lead to a reduction of the energy non-uniformity near the detector boundary, from about 0.64% to 0.38%. And within the fiducial volume of the detector it is improved from 0.3% to 0.17%. As a result the energy resolution could be further improved.

physics.ins-det↗

arXiv2017

Parallelized JUNO simulation software based on SNiPER

The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment to determine neutrino mass hierarchy. It has a central detector used for neutrino detection, which consists of a spherical acrylic vessel containing 20 kt LS and about 18,000 20-inch PMTs to collect light from LS. Around the CD, there is a water pool to shield radioactivities. The WP is equipped with about 2000 PMTs to measure cosmic ray muons by detecting Cherenkov light. As one of the important parts in JUNO offline software, the serial simulation framework is developed based on SNiPER. It is in charge of physics generator, detector simulation, event mixing and digitization. However Geant4 based detector simulation of such a large detector is time-consuming and challenging. It is necessary to take full advantages of parallel computing to speedup simulation. Starting from version 10, Geant4 supports event-level parallelism. Even though based on pthread, it could be extended with other libraries such as Intel TBB. Therefore it is possible to parallelize JUNO simulation framework via integrating Geant4 and SNiPER. In this paper, our progress in developing parallelized simulation software are presented. The SNiPER framework can run in sequential mode, Intel TBB mode or other modes. The SNiPER task component is in charge of event loop, which is like a simplified application manager. Two types of tasks are introduced in the simulation framework, one is global task and another is worker task. The global task will run only once to initialize detector geometry and physics processes. The worker tasks will be spawned after global task is done. In each worker task, a Geant4 run manager is invoked to do the real simulation. Therefore the simulation framework and the underlying TBB have been decoupled. Finally, the software performance of parallelized JUNO simulation software is also presented.

physics.ins-det↗

arXiv2017

The Application of SNiPER to the JUNO Simulation

JUNO is a multipurpose neutrino experiment which is designed to determine neutrino mass hierarchy and precisely measure oscillation parameters. As one of the important systems, the JUNO offline software is being developed using the SNiPER software. In this proceeding, we focus on the requirements of JUNO simulation and present the working solution based on the SNiPER. The JUNO simulation framework is in charge of managing event data, detector geometries and materials, physics processes, simulation truth information etc. It glues physics generator, detector simulation and electronics simulation modules together to achieve a full simulation chain. In the implementation of the framework, many attractive characteristics of the SNiPER have been used, such as dynamic loading, flexible flow control, multiple event management and Python binding. Furthermore, additional efforts have been made to make both detector and electronics simulation flexible enough to accommodate and optimize different detector designs. For the Geant4-based detector simulation, each sub-detector component is implemented as a SNiPER tool which is a dynamically loadable and configurable plugin. So it is possible to select the detector configuration at runtime. The framework provides the event loop to drive the detector simulation and interacts with the Geant4 which is implemented as a passive service. All levels of user actions are wrapped into different customizable tools, so that user functions can be easily extended by just adding new tools. The electronics simulation has been implemented by following an event driven scheme. The SNiPER task component is used to simulate data processing steps in the electronics modules. The electronics and trigger are synchronized by triggered events containing possible physics signals.

physics.ins-det↗