ترغب بنشر مسار تعليمي؟ اضغط هنا

A fast simulation package for STCF detector

47   0   0.0 ( 0 )
 نشر من قبل Xiaodong Shi
 تاريخ النشر 2020
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

A Super Tau Charm Facility (STCF) is one of the major options for the accelerator-based high energy project in China in the post-BEPCII era, and its R&D program is underway. The proposed STCF will span center of mass energies ($sqrt{s}$) ranging from 2 to 7 GeV with a peaking luminosity above $0.5times 10^{35}$ cm$^{-2}$s$^{-1}$ at $sqrt{s}=4.0$ GeV, and will provide a unique platform for tau-charm physics and hadron physics. In order to evaluate the physical potential capabilities and optimize the detector design, a fast simulation package has been developed. This package takes as inputs the response of physical objects in each sub-system of the detector including resolution, efficiency as well as related variables for the kinematic fit and the secondary vertex reconstruction algorithm. It can flexibly adjust the responses of each sub-detector system and is a critical tool for the STCF R&D program.



قيم البحث

اقرأ أيضاً

We are developing the vertex detector with a fine pixel CCD (FPCCD) for the international linear collider (ILC), whose pixel size is $5 times 5$ $mu$m$^{2}$. To evaluate the performance of the FPCCD vertex detector and optimize its design, developmen t of the software dedicated for the FPCCD is necessary. We, therefore, started to develop the software for FPCCD. In this article, the status of the study is reported.
97 - A. Annovi 2009
The Fast Tracker (FTK) is a proposed upgrade to the ATLAS trigger system that will operate at full Level-1 output rates and provide high quality tracks reconstructed over the entire detector by the start of processing in Level-2. FTK solves the combi natorial challenge inherent to tracking by exploiting the massive parallelism of Associative Memories (AM) that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and leveraging fast DSPs in modern commercial FPGAs. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in approximately one millisecond. By employing a pipelined architecture, FTK is able to continuously operate at Level-1 rates without deadtime. The system design is defined and studied using ATLAS full simulation. Reconstruction quality is evaluated for single muon events with zero pileup, as well as WH events at the LHC design luminosity. FTK results are compared with the tracking capability of an offline algorithm.
89 - Tao Lin , Ziyan Deng , Weidong Li 2016
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 17,000 phot omultiplier 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.
266 - Tao Yang , Kewei Wu , Mei Zhao 2021
We report a precise TCAD simulation for low gain avalanche detector (LGAD) with calibration by secondary ion mass spectroscopy (SIMS). The radiation model - LGAD Radiation Damage Model (LRDM) combines local acceptor degeneration with global deep ener gy levels is proposed. The LRDM could predict the leakage current level and the behavior of capacitance for irradiated LGAD sensor at -30 $^{circ}$C after irradiation fluence $rm Phi_{eq}=2.5 times 10^{15} ~n_{eq}/cm^{2}$.
We present the 3DGAN for the simulation of a future high granularity calorimeter output as three-dimensional images. We prove the efficacy of Generative Adversarial Networks (GANs) for generating scientific data while retaining a high level of accura cy for diverse metrics across a large range of input variables. We demonstrate a successful application of the transfer learning concept: we train the network to simulate showers for electrons from a reduced range of primary energies, we then train further for a five times larger range (the model could not train for the larger range directly). The same concept is extended to generate showers for other particles (photons and neutral pions) depositing most of their energies in electromagnetic interactions. In addition, the generation of charged pion showers is also explored, a more accurate effort would require additional data from other detectors not included in the scope of the current work. Our further contribution is a demonstration of using GAN-generated data for a practical application. We train a third-party network using GAN-generated data and prove that the response is similar to a network trained with data from the Monte Carlo simulation. The showers generated by GAN present accuracy within $10%$ of Monte Carlo for a diverse range of physics features, with three orders of magnitude speedup. The speedup for both the training and inference can be further enhanced by distributed training.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا