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At least 73 records · Page 4

Quantum pattern recognition algorithms for charged particle tracking

High-energy physics is facing a daunting computing challenge with the large datasets expected from the upcoming High-Luminosity Large Hadron Collider in the next decade and even more so at future colliders. A key challenge in the reconstruction of events of simulated data and collision data is the pattern recognition algorithms used to determine the trajectories of charged particles. The field of quantum computing shows promise for transformative capabilities and is going through a cycle of rapid development and hence might provide a solution to this challenge. This article reviews current studies of quantum computers for charged particle pattern recognition in high-energy physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Charged particle track reconstruction with SπRIT Time Projection Chamber

In this work, we present a software framework, SπRITROOT, which is capable of track reconstruction and analysis of heavy-ion collision events recorded with the SRIT time projection chamber. The track-fitting toolkit GENFIT and the vertex reconstruction toolkit RAVE are applied to a box-type detector system. A pattern recognition algorithm which performs helix track finding and handles overlapping pulses is described. The performance of the software is investigated using experimental data obtained at the Radioactive Isotope Beam Facility (RIBF) at RIKEN. This work focuses on data from 132 Sn + 124 Sn collision events with beam energy of 270 AMeV. Particle identification is established using < dE/dx >and magnetic rigidity, with pions, hydrogen isotopes, and helium isotopes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Symplectic Particle Tracking in a Thick Nonlinear McMillan Lens for the Fermilab Integrable Optics Test Accelerator (IOTA)

The McMillan system is a novel method to increase the tune spread of a beam without decreasing its dynamic aperture due to the systems integrability. While the ideal system is based on an infinitely thin kick, the physical design requires a thick electron lens, including a solenoid. Particle transport through the lens is difficult to simulate due to the nature of the force on the circulating beam. This paper demonstrates accurate simulation of a thick McMillan lens in a solenoid using symplectic integrators derived from Yoshidas method.

43 PARTICLE ACCELERATORS↗

Charged particle tracking with quantum annealing optimization

Abstract At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

97 MATHEMATICS AND COMPUTING↗

Particle-Tracking Proton Computed Tomography—Data Acquisition, Preprocessing, and Preconditioning

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

42 ENGINEERING↗

Verification and Performance Impact of the New Parallel MCNP6.3 Particle Track Output Capability for Subcritical Multiplication Simulations [Slides]

A separate MCNP6.3 V&V document reports on all the default calculations for all test suites. This report does not include the subcritical multiplication benchmark suite. After some additional clean-up and finalizing the post-processing and documentation steps, the subcritical multiplication benchmark suite will be released in the next version of our vnvstats repository. We tested the new HDF5 PTRAC feature in MCNP6.3 and found encouraging outcomes. Identical results coming out of the simulation with respect to the legacy PTRAC results. The overall runtime for all simulations is reduced by ~20% with the new HDF5 PTRAC capability. We consider giving the new HDF5 PTRAC features a try and using it for all subcritical multiplication and any other relevant (PTRAC) calculations.

97 MATHEMATICS AND COMPUTING↗

Combining Particle Tracking with Electromagnetic Radiation Showers: Merging GPT and Geant4 with Visualization

Field emitted electrons can seriously affect the operation of high-field, high-duty factor electron accelerators. Accelerated field emission can result in high average power beams which can radiation damage beamline components. In addition, localized losses generate thermal hot spots whose outgassing degrades the ultra-high vacuum required in photoinjectors and cryomodules. However, despite their importance, the effects of field emission are rarely included in the design and engineering of electron injectors. This work attempts to remedy this situation by combining two well-known and well-documented programs, GPT and Geant4, to track electrons and their losses in an injector beamline. This paper describes a system of programs which simulates electron paths and losses along the beamline. In addition, the tracking results can be zoomed and panned along and about the beampipe envelope using an open-source 3D CAD program. The scattering albedo calculations of the combined program, GPT-Geant4, are shown to be in good agreement with the literature albedos. The paper concludes with a dark current simulation for the LCLS-II injector from the cathode to the collimator at 1.5 m from the cathode.

Dowell, David H.↗