The Booster Neutrino Experiment (MiniBooNE) searches for muon neutrino to electron neutrino oscillations using the ~1 GeV neutrino beam produced by the FNAL Booster synchrotron. The array of photomultiplier tubes (PMTs) lining the MiniBooNE detector records Cherenkov and scintillation photons from the charged particles produced in neutrino interactions. We describe a maximum likelihood fitting algorithm used to reconstruct the basic properties (position, direction, energy) of these particles from the charges and times measured by the PMTs. The likelihoods returned from fitting an event to different particle hypotheses are used to categorize it as a signal electron neutrino event or as one of the background muon neutrino processes, in particular charged current quasi-elastic scattering and neutral current $π^0$ production. The reconstruction and event selection techniques described here can be applied to current and future neutrino experiments using similar Cherenkov-based detection.
We study the impact of the effect of multinucleon interactions in the reconstruction of the neutrino energy on the fit of the MiniBooNE data in terms of neutrino oscillations. We obtain some improvement of the fit of the MiniBooNE low-energy excess in the framework of two-neutrino oscillations and a shift of the allowed region in the $\sin^2 2\vartheta$--$Δ{m}^2$ plane towards smaller values of $\sin^2 2\vartheta$ and larger values of $Δ{m}^2$. However this effect is not enough to solve the problem of the appearance-disappearance tension in the global fit of short-baseline neutrino oscillation…
An efficient and precise reconstruction of charged-particle tracks is crucial for the overall performance of the CMS experiment. During Run 2 of LHC, significant upgrades were made to the track reconstruction algorithms in order to accommodate for the high pileup environment and the installation of an upgraded pixel detector in 2017. This paper provides an overview of the iterative track reconstruction algorithm used in CMS during Run 2 and of the performance measured both with simulated and collision data. Developments are ongoing to further improve track reconstruction in Run 3, especially f…
The Muon Ionization Cooling Experiment (MICE) will demonstrate the principle of muon beam phase-space reduction via ionization cooling. Muon beam cooling will be required for the proposed Neutrino Factory or Muon Collider. The phase-space before and after the cooling cell must be measured precisely. This is achieved using two scintillating-fibre trackers, each placed in a solenoidal magnetic field. This paper describes the software reconstruction for the fibre trackers: the GEANT4 based simulation; the implementation of the geometry; digitisation; space-point reconstruction; pattern recognitio…
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.
MicroBooNE (the Micro Booster Neutrino Experiment) is a short-baseline neutrino experiment based on the technology of a liquid-argon time-projection chamber (LArTPC), and has recently completed its first year of data-taking in the Fermilab Booster Neutrino Beam. It aims to address the anomalous excess of events with an electromagnetic final state in MiniBooNE, to measure neutrino-argon interaction cross sections, and to provide relevant R\&D for the future LArTPC experiments, such as DUNE. In these proceedings, we present the first reconstructed energy spectrum of Michel electrons from cosmic …
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。
The PANDA (anti-Proton ANnihilation at DArmstadt) experiment at the Facility for Anti-proton and Ion Research is going to study strong interactions at the scale at which quarks are confined to form hadrons. A continuous beam of antiproton, provided by the High Energy Storage Ring (HESR), will impinge on a fixed hydrogen target. The antiproton beam momentum spans from 1.5 GeV {Natural units, c=1} to 15 GeV \cite{physics2009report}, will create optimal conditions for studying many different aspects of hadron physics, including hyperon physics. Precision physics studies require a highly efficient…
Considering the aging effects of existing Inner Drift Chamber (IDC) of BES\uppercase\expandafter{\romannumeral3}, a GEM based inner tracker is proposed to be designed and constructed as an upgrade candidate for IDC. This paper introduces a full simulation package of CGEM-IT with a simplified digitization model, describes the development of the softwares for cluster reconstruction and track fitting algorithm based on Kalman filter method for CGEM-IT. Preliminary results from the reconstruction algorithms are obtained using a Monte Carlo sample of single muon events in CGEM-IT.
ALICE is the dedicated heavy-ion experiment at the CERN Large Hadron Collider (LHC). Its main tracking and particle-identification detector is a large volume Time Projection Chamber (TPC). The TPC has been designed to perform well in the high-track density environment created in high-energy heavy-ion collisions. In this proceeding, we describe the track reconstruction procedure in ALICE. In particular, we focus on the two main challenges that were faced during the Run 2 data-taking period (2015--2018) of the LHC, which were the baseline fluctuations and the local space charge distortions in th…
We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of $40\,\rm MHz$. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.
A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For ttbar events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of pt > 0.9 GeV…
Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogen…
Finding tracks downstream of the magnet at the earliest LHCb trigger level is not part of the baseline plan of the upgrade trigger, on account of the significant CPU time required to execute the search. Many long-lived particles, such as $K^0_S$ and strange baryons, decay after the vertex track detector, so that their reconstruction efficiency is limited. We present a study of the performance of a future innovative real-time tracking system based on FPGAs, developed within a R\&D effort in the context of the LHCb Upgrade Ib (LHC Run~4), dedicated to the reconstruction of the particles downstre…
The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented conditions will create a combinatorial complexity for charged-particle track reconstruction that demands a computational cost that is expected to surpass the projected computing budget using conventional CPUs. Motivated by this and taking into account the prevalence of heterogeneous computing in cutting-edge High Performance Computing centers, we propose an efficient, fast and highly parallelizable bottom-up approach to t…
The spherical proportional counter is a versatile gaseous detector with physics applications ranging from rare event searches to fast neutron spectroscopy. In its simplest form, the detector operates with a single channel read-out, and uses pulse-shape information to reconstruct the interaction radius, which is used for background discrimination and target volume definition. Recent developments in the read-out instrumentation have enabled the use of a multi-anode read-out structure, ACHINOS. The multiple anodes provide information about the interaction position which, coupled with the radial i…
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…
We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at $40\,\rm MHz$, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking de…
Fast 4$π$ track reconstruction in nuclear emulsion detectors based on GPU technology
快速4 $π$立体角粒子径迹识别一直是粒子物理领域的一个挑战，特别是在核乳胶探测器上。计算技术的最新进展为实现这一目标开辟了道路。介绍了一种基于GPU技术结合多线程编程的快速4 $π$立体角粒子轨迹重建方法，并对GPU编程和CPU编程进行了详细比较。通过具有优异跟踪性能的GPU，3D乳胶检测器数据的处理速度提高了60倍，相当于每小时扫描15 cm $^2$乳胶表面。
LUXE (Laser Und XFEL Experiment) is a proposed experiment at DESY which will study Quantum Electrodynamics (QED) in the strong-field regime, where QED becomes non-perturbative. Measuring the rate of created electron-positron pairs using a silicon pixel tracking detector is an essential ingredient to study this regime. Precision tracking of positrons traversing the four layers of the tracking detector becomes very challenging at high laser intensities due to the high rates, which can be computationally expensive for classical computers. In this work, we update our previous study of the potentia…
From Hits to Tracks: A BERT-based Tracking Model for Track Reconstruction in Drift Chambers
Institute of High Energy Physics, Chinese Academy of Sciences（中国科学院高能物理研究所）；University of Chinese Academy of Sciences（中国科学院大学）；China Academy of Space Technology（中国空间技术研究院）
sPHENIX is a high energy nuclear physics experiment under construction at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory (BNL). The primary physics goals of sPHENIX are to study the quark-gluon-plasma, as well as the partonic structure of protons and nuclei, by measuring jets, their substructure, and heavy flavor hadrons in $p$$+$$p$, $p$+Au, and Au+Au collisions. sPHENIX will collect approximately 300 PB of data over three run periods, to be analyzed using available computing resources at BNL; thus, performing track reconstruction in a timely manner is a challenge due t…
sPHENIX is a new experiment that is being constructed at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The primary physics goals of sPHENIX are to measure jets, their substructure, and the upsilon resonances in $p$$+$$p$, $p$+Au and Au+Au collisions. To realize these goals, a tracking system composed of a time projection chamber and several silicon detectors will be used to identify tracks that correspond to jets and upsilon decays. However, the sPHENIX experiment will collect approximately 200 PB of data utilizing a finite-sized computing center; thus, performing trac…
Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational challenge of track finding and fitting requires novel solutions. The current track reconstruction algorithms used at the LHC are based on Kalman filter methods that achieve good physics performance. By adapting the Kalman filter techniques for use on many-core SIMD architectures such as the Intel Xeon and Intel Xeon Phi and (to a limited degree) NVIDIA GPUs, we…
The physics reach of the HL-LHC will be limited by how efficiently the experiments can use the available computing resources, i.e. affordable software and computing are essential. The development of novel methods for charged particle reconstruction at the HL-LHC incorporating machine learning techniques or based entirely on machine learning is a vibrant area of research. In the past two years, algorithms for track pattern recognition based on graph neural networks (GNNs) have emerged as a particularly promising approach. Previous work mainly aimed at establishing proof of principle. In the pre…
