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haiyun teng (Institute of High Energy Physics, CAS)11/07/2024, 08:45
介绍散裂中子源的数据获取特点和需求，其虽然在数据量上没有高能物理实验的海量规模，但各种先进的实验方法要求数据获取与控制提供双向链路和实时性等重要支持特性，数据获取也因而在这些特性方向上有了独特的发展。结合CSNS上的谱仪数据获取发展状况，报告进而介绍目前中子谱仪的基于数据流平台的数据获取框架及关键技术，进一步探讨未来中子谱仪的数据获取如何利用人工智能和大数据的优势，实现更加高效智能的数据处理。
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Jingyan Shi (IHEP)11/07/2024, 09:30
The HEP computing platform at IHEP is designed to support data processing for the HEP experiments in which IHEP is involved. The platform operates large-scale HTC and HPC clusters, along with WLCG grid sites, providing petabyte-level storage. Studies on optimizing job scheduling and enhancing I/O performance aim to improve resource utilization. Operational maintenance is managed through...
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Dr 新华 林 (上海交通大学)11/07/2024, 10:35
本报告基于上海交大校级超算平台的实践经验，介绍国产鲲鹏超算平台的部署、优化、应用案例，展示鲲鹏生态在复杂计算任务中的卓越表现，以及2024年与华为成立鲲鹏昇腾科教创新卓越中心后，致力于人才培养与生态推广的愿景。
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朝义 渠 (山东高等技术研究院)11/07/2024, 13:45
The High Energy cosmic-Radiation Detection (HERD) facility is scheduled to operate on Chinese Space Station (CSS) since 2027 for about 10 years. With the high accuracy silicon charge detector (SCD) and silicon tungsten detector (STK) forming a compact 5 side sensitive detection, HERD is capable to provide trajectory measurement of cosmic-rays. A cellular based track reconstruction algorithm is...
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Rui Zhang (University of Wisconsin-Madison)11/07/2024, 14:30
Machine learning (ML) has become a transformative tool in high energy physics. In this talk, I will demonstrate how high energy physics problems can be reframed as ML tasks, and highlight the application of ML techniques to enhance particle reconstruction and identification, particularly at the Large Hadron Collider (LHC). Additionally, I will discuss unsupervised ML methods for calorimeter...
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Da Yu Tou (Tsinghua University)11/07/2024, 15:15
The current Upgrade I data-taking of the LHCb experiment uses a fully software trigger to perform a real-time analysis of LHCb detector data at an input rate of 5TB/s which corresponds to an event rate of 30MHz. This trigger is implemented in two stages. The High Level Trigger 1 (HLT1) performs a partial but high throughput reconstruction on GPUs to inclusively select events. The HLT2 then...
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Hongyue Duyang (Shandong University)11/07/2024, 16:10
The Jiangmen Underground Neutrino Observatory (JUNO) is a next-generation neutrino experiment currently under construction in southern China. It is designed with a 20 kton liquid scintillator detector and 78% photomultiplier tube (PMT) coverage. The primary physics goal of JUNO is to determine the neutrino mass ordering and measure oscillation parameters with unprecedented precision. JUNO’s...
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Zejia Lu (SJTU)11/07/2024, 16:55
DarkSHINE is an electron-on-target experiment proposed to search for light dark matter. In this talk, we present the application of Graph Neural Networks (GNN) for the tracking and vertex reconstruction in the proposed DarkSHINE experiment with full simulation samples. Compared to the traditional Kalman Filter method, GNN method doubles the signal efficiency while significantly reducing the...
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Siyuan Song11/07/2024, 17:20
Particle Identification (PID) plays a central role in associating the energy depositions in calorimeter cells with the type of primary particle in a particle flow oriented detector system. In this talk, we hope to demonstrate novel PID methods based on the Residual Network (ResNet) architecture to classify experiment data collected at CERN in 2022 and 2023 for the CEPC AHCAL prototype Beam...
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逸昇 傅 (IHEP)12/07/2024, 09:00
A Python-based software tool is developed for the performance evaluation of cylindrical tracking system. Incorporating fast simulation techniques, the tool facilitates the assessment of spatial resolution and the effects of multiple scattering, offering both analytical calculations and Kalman filter reconstruction. Additionally, a user-friendly graphical user interface (GUI) has been provided...
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Tao Li (Sun Yat-sen University)12/07/2024, 09:45
PandaX is an experiment that aims to search for dark matter, neutrinoless double beta decay, and other rare processes using a liquid xenon time projection chamber. A good understanding of the energy deposition processes in the detector holds great importance to the experiment. To address this, BambooMC, a Geant4-based Monte Carlo simulation program, has been developed. In this presentation,...
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Xuliang Zhu (Tsung-Dao Lee Institute, Shanghai Jiao Tong Univ. (CN))12/07/2024, 10:40
This talk introduces the Dark SHINE Simulation software. Dark SHINE is a fixed-target dark photon search experiment based at Shanghai SHINE facility. The Dark SHINE Simulation software integrates generator, simulation, digitization, reconstruction, and analysis chain. There are three main parts, DSimu, DAna, and DDis. DSimu is a simulation software based on Geant4 and ROOT, characterized by...
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泰霖 吴 (西湖大学)12/07/2024, 11:05
In science and engineering, fundamental problems include the forward problem of simulating the evolution of complex physical systems, and the inverse design/inverse problem of optimizing/inferring the system's high-dimensional parameters. Traditional numerical simulation and optimization methods often require extensive computation due to complex physical dynamics. In this talk, I will...
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Zhengde ZHANG (IHEP, CAS)12/07/2024, 13:30
The BESIII experiment has collected the world's largest sample of charm hadron data, yielding a wealth of physical results. Large AI models, with their comprehensive data and god's-eye view, have the potential to significantly enhance the efficiency of human scientific discovery. The Computing Center and Experimental Physics Center at IHEP have collaborated to develop Dr. Sai, an AI agent for...
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Congqiao Li (Peking University)12/07/2024, 14:15
The search for heavy resonances beyond the Standard Model (BSM) is a key objective at the LHC. While the recent use of advanced deep neural networks for boosted-jet tagging significantly enhances the sensitivity of dedicated searches, it is limited to specific final states, leaving vast potential BSM phase space underexplored. In this talk, we introduce a novel experimental method,...
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Jianqin Xu12/07/2024, 15:00
Generative Adversarial Networks (GANs), as a powerful framework in deep learning, have been widely applied in various fields. This study aims to develop a rapid data generator by training GAN networks on the data collected from the Pandax-II Run11 AmBe experiment. The data generated by the GAN network not only preserves the individual physical characteristics but also maintains the...
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Qitian Wu (Shanghai Jiao Tong University)12/07/2024, 15:55
Graphs are a popular mathematical abstraction for systems of relations and interactions that can be applied in various domains such as physics, biology, social sciences, etc. Towards unleashing the power of machine learning models for graphs, one fundamental challenge is how to obtain high-quality representations for graph-structured data with diverse scales and properties. We will talk about...
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Huilin Qu (CERN)12/07/2024, 16:40
Machine learning has revolutionized the analysis of large-scale data samples in high energy physics (HEP) and greatly increased the discovery potential for new fundamental laws of nature. Specifically, graph neural networks (GNNs), thanks to their high flexibility and expressiveness, have demonstrated superior performance over classical deep learning approaches in tackling data analysis...
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Bingzhi Li (Zhejiang Lab 之江实验室)12/07/2024, 17:25口头报告
In the Muon g-2 experiment, the tracking reconstruction is a key component of the data reconstruction and analysis, it provides essential beam dynamics parameters and muon weighting parameters and determines the precision of muon EDM measurements. This presentation introduces the GNN-based tracking reconstruction method. Leveraging message-passing mechanisms and the Louvain algorithm, the GNN...
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Manqi RUAN (Institute of High Energy Physics, Beijing, China)13/07/2024, 09:00
To enhance the scientific discovery power of high-energy collider experiments, we propose and realize the concept of jet-origin identification that categorizes jets into five quark species (b; c; s; u; d), five corresponding antiquarks, and the gluon.
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Using state-of-the-art algorithms and simulated ν¯νH, H → jj
events at 240 GeV center-of-mass energy at the electron-positron Higgs factory,... -
Kun Wang (University of Shanghai for Science and Technology)13/07/2024, 09:45
We propose a new jet tagging method based on Transformer architecture called More Interaction Particle Transformer (miParT). This method improves upon the ParT algorithm by modifying the attention mechanism and increasing the embedding dimension of the pairwise particle interaction input, all while reducing the total number of parameters and computational complexity. We tested miParT on two...
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Yunxuan Song (EPFL - Ecole Polytechnique Federale Lausanne (CH))13/07/2024, 10:30
The reconstruction of neutral hadrons, particularly (anti-)neutrons, presents a significant challenge in high-energy physics experiments, notably at BESIII, which lacks a dedicated hadronic calorimeter. This talk will cover the innovative techniques applied in the identification of neutrons, in the first observation of the $\Lambda_c^+\to ne^+ \nu$ process. Furthermore, it will discuss the...
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Weiyan Zhang (Hebei Normal University)
The classification of cosmic-ray components in ground-based air shower experiments such as LHAASO is a challenging task. ParticleNet is a DGCNN-based model designed for particle physics applications. In this presentation, we use ParticleNet to identify the proton and light components from background cosmic-ray events in the simulation data of LHAASO-KM2A. The results show enhanced...
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