An imaging system for measuring the spatial distribtion of charged particle tracks in a low-pressure gas is presented. The method is based on an optically read out time projection chamber. Results of experiments with fast heavy ions are shown.
In this report we discuss appropriate strategies for the tracking of charged particles in the limit of zero curvature. The suggested approach avoids special treatments and precision issues that frequently arise in that limit. We provide explicit expressions for transport, refitting and vertexing in regions where magnetic field inhomogeneities or detector interaction effects can be approximately ignored.
The determination of charged particle trajectories (tracking) in collisions at the CERN Large Hadron Collider (LHC) is one of the most important aspects for event reconstruction at hadron colliders. This is especially true in the high conditions expected during the future high-luminosity phase of the LHC (HL-LHC) where the number of interactions per beam crossing will increase by a factor of five. Deep learning algorithms have been successfully applied to this task for offline applications. However, their study in hardware-based trigger applications has been limited . In this paper, we study d…
The design of gaseous detectors for accelerator, particle and nuclear physics requires simulations relying on multi-physics aspects. In fact, these simulations deal with the dynamics of a large number of charged particles interacting in a gaseous medium immersed in the electric field generated by a more or less complex assembly of electrodes and dielectric materials. We report here on a homemade software, called OUROBOROSBEM, able to tackle the different features involved in such simulations. After solving the electrostatic problem for which a solver based on the boundary element method (BEM) …
A prototype of the CMOS pixel sensor named SUPIX-1 has been fabricated and tested in order to investigate the feasibility of a pixelated tracker for a proposed Higgs factory, namely, the Circular Electron-Positron Collider (CEPC). The sensor, taped out with a 180 nm CMOS Image Sensor (CIS) process, consists of nine different pixel arrays varying in pixel pitches, diode sizes and geometries in order to study the particle detection performance of enlarged pixels. The test was carried out with a Fe-55 radioactive source. Two soft X-ray peaks observed were used to calibrate the charge to voltage f…
Charged particle tracking without magnetic field: optimal measurement of track momentum by a Bayesian analysis of the multiple measurements of deflections due to multiple scattering
NuMI离轴现象(英语:NuMI Off-Axis v Appearance,缩写:NOvA)实验是一个长基线中微子振荡实验,使用的是费米实验室的NuMI光束线产生的中微子源。该实验将使用两个功能相同的塑料液体闪烁体填充探测器研究μ子中微子到电子中微子的振荡,该探测器放置在离轴14毫弧度的NuMI光束上。带电中微子相互作用将被用来观察中微子味从识别的最终状态轻子。μ子带电粒子径迹的重建在探测器对准和校准的短期目标以及通过识别μ子带电电流事件的长期振荡分析中起着重要作用。提出了一种基于卡尔曼滤波的μ子径迹识别和径迹拟合的初步方法。
University of Pennsylvania(宾夕法尼亚大学);University of California San Diego(加州大学圣地亚哥分校);National Yang Ming Chiao Tung University(国立阳明交通大学);University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校);Princeton University(普林斯顿大学);University of Washington(华盛顿大学)
The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a type of geometric deep learning algorithm that has successfully been applied to this task by embedding tracker data as a graph -- nodes represent hits, while edges represent possible track segments -- and classifying the edges as true or fake track segments. However, their study in hardware- or…
We describe the Hybrid seeding, a standalone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing.
The design of a detector system comprised of four silicon sensors bump-bonded to Timepix4 ASICs is described together with its data acquisition system, operational infrastructure, and dedicated software. The spatial and temporal performance of the system are assessed with a 180 GeV/c mixed hadron beam at the CERN SPS and reported in detail. Particle tracks are reconstructed using time-space measurements from the four detector planes. The spatial hit resolution is assessed to be $(15.5\pm 0.5)$ $μ$m and $(4.5\pm0.3)$ $μ$m for 100 and 300 $μ$m thick sensors, respectively. The timestamps from the…
Impact of Cold Noise on the tracking performance of ATLAS ITk short strip barrel modules using a charged particle beam
Santa Cruz Institute for Particle Physics, University of California Santa Cruz(加州大学圣克鲁兹分校圣克鲁兹粒子物理研究所);Deutsches Elektronen-Synchrotron DESY(德国电子同步加速器中心);Lunds universitet(隆德大学);University of Birmingham(伯明翰大学);Charles University(查理大学);Rutherford Appleton Laboratory(卢瑟福阿普尔顿实验室);University of British Columbia(不列颠哥伦比亚大学);TRIUMF(特里姆夫实验室)
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant…
University of California San Diego(加州大学圣地亚哥分校);Princeton University(普林斯顿大学);University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校);Fermi National Accelerator Laboratory(费米国家加速器实验室);Massachusetts Institute of Technology(麻省理工学院);Institute of Physics Belgrade(贝尔格莱德物理研究所);European Organization for Nuclear Research (CERN)(欧洲核子研究组织(CERN));California Institute of Technology(加州理工学院);Purdue University(普渡大学);HawkEye360;University of Illinois at Chicago(伊利诺伊大学芝加哥分校)
We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a framework for writing programs that execute across heterogeneous platforms, and hls4ml, a high-level-synthesis-based compiler for neural network to firmware conversion. We evaluate and compare the resource usage, latency, and tracking performance of our implementations based on a benchmark dataset. We find a considerable speedup over CPU-based execution is possible, potentially enabling such algorithms to be used effecti…
Event-by-event track imaging of charged particles with an ultrafast plenoptic camera
ETH Zürich(苏黎世联邦理工学院);Università degli Studi Roma Tre(罗马第三大学);Istituto Nazionale di Ottica - CNR(意大利国家光学研究所-国家研究委员会);INFN Sezione di Roma Tre(罗马第三大学意大利国家核物理研究所分部);Politecnico di Bari(巴里理工大学);INFN Sezione di Bari(巴里意大利国家核物理研究所分部);École polytechnique fédérale de Lausanne (EPFL)(洛桑联邦理工学院)
A CMOS pixel sensor, named Supix-1, is developed for a pixelated silicon tracker for the Circular Electron-Positron Collider (CEPC) project. The sensor, consisted of nine sectors varying in pixel sizes, diode sizes and geometries, is fabricated with a 180 nm CMOS Image Sensor (CIS) process to study the particle detection performance of enlarged pixels. In this work, the radiation-induced effects on the charge collection of the sensor under the fluence of 1 $\times$ 10^13 1 MeV neq/cm^2 are studied by the measurements with the radioactive source of Fe-55 and the Technology Computer Aided Design…
On-chip probabilistic inference for charged-particle tracking at the sensor edge
Cornell University(康奈尔大学);Fermi National Accelerator Laboratory(费米国家加速器实验室);Johns Hopkins University(约翰斯·霍普金斯大学);Northeastern University(东北大学);Purdue University(普渡大学);University of Chicago(芝加哥大学);University of Colorado Boulder(科罗拉多大学博尔德分校);University of Illinois Chicago(伊利诺伊大学芝加哥分校);University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)
Physics Informed Neural Networks for design optimisation of diamond particle detectors for charged particle fast-tracking at high luminosity hadron colliders
Istituto Nazionale di Fisica Nucleare, Sezione di Firenze(意大利佛罗伦萨核物理研究所);ICSC - Centro Nazionale di Ricerca in High Performance Computing, Big Data & Quantum Computing(高性能计算、大数据与量子计算国家研究中心)