Related papers: GPU-based track-finding for the J-PARC muon g-2/ED…
This paper discusses a parallelized event reconstruction of the COMET Phase-I experiment. The experiment aims to discover charged lepton flavor violation by observing 104.97 MeV electrons from neutrinoless muon-to-electron conversion in…
A high-intensity pulsed muon beam is becoming available at the at the Japan Proton Accelerator Research Complex (J-PARC). Many experiments to study fundamental physics using this high-intensity muon beam are proposed. An experiment to…
We report on the development of a front-end ASIC for silicon-strip detectors of the J-PARC Muon g-2/EDM experiment. This experiment aims to measure the muon anomalous magnetic moment and electric dipole moment precisely to explore new…
The GPU-accelerated track finding method is investigated to track electrons from neutrinoless muon decay in the COMET Phase-I experiment. Inside the cylindrical drift chamber, one third of the signal electron trajectories are composed of…
Fast 4$\pi$ solid angle particle track recognition has been a challenge in particle physics for a long time, especially in using nuclear emulsion detectors. The recent advances in computing technology opened the way for its realization. A…
We present a GPU-accelerated method for muon transport based on histogram sampling that delivers orders of magnitude faster performance than CPU-based Geant4 simulation. Our method employs precomputed histograms of momentum loss and…
The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for…
Graphical Processing Units (GPUs) have recently become a valuable computing tool for the acquisition of data at high rates and for a relatively low cost. The devices work by parallelizing the code into thousands of threads, each executing a…
We present a fast GPU implementation of the image reconstruction routine, for a novel two strip PET detector that relies solely on the time of flight measurements.
The J-PARC muon $g - 2$/EDM experiment aims to measure the muon magnetic moment anomaly $a_{\mu} = (g -2) / 2 ~ $ and the muon electric dipole moment (EDM) $d_{\mu}$. The target sensitivity for $a_{\mu}$ is a statistical uncertainty of $450…
The prediction of a dielectric breakdown in a high-voltage device is based on criteria that evaluate the electric field along field lines. Therefore it is necessary to efficiently compute the electric field at arbitrary points in space. A…
For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as GPGPU, ARM and Intel…
High-energy physics experiments require fast and efficient methods for reconstructing the tracks of charged particles. The commonly used algorithms are sequential, and the required CPU power increases rapidly with the number of tracks.…
The Muon g-2/EDM Experiment at J-PARC will employ a novel way to measure the muon magnetic anomaly, a_mu = (g-2)_mu/2, by using a low-emittance beam of positive muons stored in a compact muon storage magnet. The experimental method includes…
Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the…
The J-PARC muon g-2/EDM experiment aims to measure the muon magnetic moment anomaly $a_{\mu} = (g -2 ) / 2 ~ $. The target sensitivity for $a_{\mu}$ is a statistical uncertainty of $450 \times 10^{-9}$, and $a_{\mu}$ can be extracted by…
Particle tracking simulations with space charge effects are very important for high-intensity proton rings. Since they include not only Hamilton mechanics of a single particle but constructing charge densities and solving Poisson equations…
Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core…
Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting…
In high-energy physics, the increasing luminosity and detector granularity at the Large Hadron Collider are driving the need for more efficient data processing solutions. Machine Learning has emerged as a promising tool for reconstructing…