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Featured researches published by Guofu Cao.


Journal of Physics: Conference Series | 2015

SNiPER: an offline software framework for non-collider physics experiments

Jiaheng Zou; X. T. Huang; Weidong Li; Tao Lin; T. Li; K. Zhang; Ziyan Deng; Guofu Cao

SNiPER (Software for Non-collider Physics ExpeRiments) has been developed based on common requirements from both nuclear reactor neutrino and cosmic ray experiments. The design and implementation of SNiPER is described in this proceeding. Compared to the existing offline software frameworks in the high energy physics domain, the design of SNiPER is more focused on execution efficiency and flexibility. SNiPER has an open structure. User applications are executed as plug-ins based on it. The framework contains a compact kernel for software components management, event execution control, job configuration, common services, etc. Some specific features are attractive to non-collider physics experiments.


Journal of Physics: Conference Series | 2017

The Application of SNiPER to the JUNO Simulation

Tao Lin; Jiaheng Zou; Weidong Li; Ziyan Deng; Xiao Fang; Guofu Cao; Xing-Tao Huang; Zhengyun You

The JUNO (Jiangmen Underground Neutrino Observatory) 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. The JUNO simulation software has been released and is being used by the JUNO collaboration to do detector design optimization, event reconstruction algorithm development and physics sensitivity studies.


arXiv: Instrumentation and Detectors | 2018

Parallelized JUNO simulation software based on SNiPER

Tao Lin; Jiaheng Zou; Weidong Li; Ziyan Deng; Guofu Cao; Xing-Tao Huang; Zhengyun You

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. nAs 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. nIn 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.


Proceedings of 38th International Conference on High Energy Physics — PoS(ICHEP2016) | 2017

Offline Data Processing Software for the JUNO Experiment

Xing-Tao Huang; Teng Li; Jiaheng Zou; Tao Lin; Weidong Li; Ziyan Deng; Guofu Cao

JUNO is a multi-purpose neutrino experiment designed to determine the neutrino mass hierarchy and precisely measure oscillation parameters. The offline data processing of JUNO is based on the newly designed and developed SNiPER framework which provides flexible event management buffer, efficient event execution controlling, user-friendly interfaces and so on. The event data model of JUNO is based on the ROOT TObject. A new type of smart pointer, SmartRef, is designed to meet the special multi-event correlation requirements of neutrino experiments. SmartRef uses the Universally Unique Identifier to handle the references of event data objects, both in memory and in ROOT files. The Input/Output system supports the lazy-loading of event objects when reading data from ROOT files. So far, JUNO offline data processing software has been successfully used for the optimization of detector performance as well as study of reconstruction and physics performance.


Chinese Physics C | 2016

Fast muon simulation in the JUNO central detector

Tao Lin; Ziyan Deng; Weidong Li; Guofu Cao; Zhengyun You; Xinying Li

The Jiangmen Underground Neutrino Observatory(JUNO) is a multi-purpose neutrino experiment designed to measure the neutrino mass hierarchy using a central detector(CD),which contains 20 kton liquid scintillator(LS) surrounded by about 17000 photonuiltiplier tubes(PMTs).Due to the large fiducial volume and huge number of PMTs,the simulation of a muon particle passing through the CD with the Geant4 toolkit becomes an extremely computation-intensive task.This paper presents a fast simulation implementation using a so-called voxel method:for scintillation photons generated in a certain LS voxel,the PMT’s response is produced beforehand with Geant4 and then introduced into the simulation at runtime.This pararneterisation method successfully speeds up the most CPU consuming process,the optical photon’s propagation in the LS,by a factor of 50.In the paper,the comparison of physics performance between fast and full simulation is also given.The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment designed to measure the neutrino mass hierarchy using a central detector (CD), which contains 20 kton liquid scintillator (LS) surrounded by about 17000 photomultiplier tubes (PMTs). Due to the large fiducial volume and huge number of PMTs, the simulation of a muon particle passing through the CD with the Geant4 toolkit becomes an extremely computation-intensive task. This paper presents a fast simulation implementation using a so-called voxel method: for scintillation photons generated in a certain LS voxel, the PMTs response is produced beforehand with Geant4 and then introduced into the simulation at runtime. This parameterisation method successfully speeds up the most CPU consuming process, the optical photons propagation in the LS, by a factor of 50. In the paper, the comparison of physics performance between fast and full simulation is also given.


arXiv: High Energy Physics - Experiment | 2018

Measurement of the phase between strong and electromagnetic amplitudes of

Medina Ablikim; Mikhail N Achasov; S. Ahmed; M. Albrecht; Antonio Amoroso; Fenfen An; Q. An; Y. Bai; O. Bakina; R. Baldini Ferroli; Yong Ban; Dan Bennett; Jake Bennett; Niklaus Berger; Monica Bertani; D. Bettoni; J. M. Bian; Fabrizio Bianchi; Evgeny Boger; Igor Boyko; R. A. Briere; Hao Cai; Xiao Cai; O. Cakir; Alessandro Calcaterra; Guofu Cao; Serkant Ali Cetin; Junying Chai; Jinfan Chang; Georgy Chelkov


Chinese Physics C | 2010

J/\psi

Naum K. Berger; Kai Zhu; Zhen-An Liu; D. P. Jin; Hao Xu; W. X. Gong; Ke Wang; Guofu Cao


Chinese Physics C | 2010

decays.

Lu-Kui Jia; Ze-Pu Mao; Weidong Li; Guofu Cao; Xue-Xiang Cao; Ziyan Deng; Kang-Lin He; Chun-yan Liu; Huai-Min Liu; Qiu-Guang Liu; Qiumei Ma; Xiang Ma; Jin-Fa Qiu; Hao-Lai Tian; Ji-Ke Wang; L. H. Wu; Ye Yuan; Shi-Lei Zang; Chang-Chun Zhang; Lei Zhang; Yao Zhang; Kai Zhu; Jiaheng Zou


Chinese Physics C | 2009

PARTICLES AND FIELDS Trigger efficiencies at BESIII

Yu-Tie Liang; Kun Liu; Zheng-Yun You; Yajun Mao; Weidong Li; Jian-Ming Bian; Guofu Cao; Xue-Xiang Cao; Shenjian Chen; Ziyan Deng; Cheng-Dong Fu; Yuanning Gao; Lei Han; S. Q. Han; Kanglin He; Miao He; J. F. Hu; X. W. Hu; Bin Huang; Xing-Tao Huang; Lu-Kui Jia; X. B. Ji; Haibo Li; B. Liu; C. L. Liu; Huai-Min Liu; Ying D. Liu; Yong Liu; Tao Luo; Q. W. Lu


Chinese Physics C | 2009

DETECTORS AND EXPERIMENTAL METHODS Study of low momentum track reconstruction for the BESIII main drift chamber

Ji-Ke Wang; Zepu Mao; Jian-Ming Bian; Guofu Cao; Xue-Xiang Cao; Shenjian Chen; Ziyan Deng; Cheng-Dong Fu; Yuanning Gao; Kanglin He; Miao He; Chun-Fei Hua; Bin Huang; Xing-Tao Huang; X. B. Ji; Fei Li; Haibo Li; Weidong Li; Yu-Tie Liang; C. L. Liu; Huai-Min Liu; Suo Liu; Yingjie Liu; Q. M. Ma; Xiang Ma; Yajun Mao; Xiaohu Mo; Ming-Hua Pan; Cai-Ying Pang; R. G. Ping

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Weidong Li

Chinese Academy of Sciences

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Huai-Min Liu

Chinese Academy of Sciences

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Xue-Xiang Cao

Chinese Academy of Sciences

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Bin Huang

Chinese Academy of Sciences

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Jian-Ming Bian

Chinese Academy of Sciences

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Miao He

Chinese Academy of Sciences

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