scholarly journals Ariadne: PyTorch library for particle track reconstruction using deep learning

2021 ◽  
Author(s):  
Pavel Goncharov ◽  
Egor Schavelev ◽  
Anastasia Nikolskaya ◽  
Gennady Ososkov
Keyword(s):  
Deep Learning ◽  
Particle Track ◽  
Track Reconstruction

scholarly journals Speeding up particle track reconstruction using a parallel Kalman filter algorithm

2020 ◽  
Vol 15 (09) ◽  
pp. P09030-P09030
Author(s):  
S. Lantz ◽  
K. McDermott ◽  
M. Reid ◽  
D. Riley ◽  
P. Wittich ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Particle Track ◽  
Track Reconstruction ◽  
Kalman Filter Algorithm

scholarly journals Graph neural network application to the particle track reconstruction for data from the GEM detector

2019 ◽  
Author(s):  
Dmitriy Baranov ◽  
Pavel Goncharov ◽  
Gennady Ososkov ◽  
Egor Shchavelev
Keyword(s):  
Neural Network ◽  
Particle Track ◽  
Track Reconstruction ◽  
Network Application ◽  
Gem Detector

scholarly journals Medical Applications of the GEMPix

2021 ◽  
Vol 11 (1) ◽  
pp. 440
Author(s):  
Johannes Leidner ◽  
Fabrizio Murtas ◽  
Marco Silari
Keyword(s):  
Radiation Therapy ◽  
Field Size ◽  
Photon Radiation ◽  
Medical Applications ◽  
Drift Region ◽  
Particle Track ◽  
Track Reconstruction ◽  
Tissue Equivalent ◽  
Gafchromic Films ◽  
Time Projection

The GEMPix is a small gaseous detector with a highly pixelated readout, consisting of a drift region, three Gas Electron Multipliers (GEMs) for signal amplification, and four Timepix ASICs with 55 µm pixel pitch and a total of 262,144 pixels. A continuous flow of a gas mixture such as Ar:CO2:CF4, Ar:CO2 or propane-based tissue equivalent gas is supplied externally at a rate of 5 L/h. This article reviews the medical applications of the GEMPix. These include relative dose measurements in conventional photon radiation therapy and in carbon ion beams, by which on-line 2D dose images provided a similar or better performance compared to gafchromic films. Depth scans in a water phantom with 12C ions allowed measuring the 3D energy deposition and reconstructing the Bragg curve of a pencil beam. Microdosimetric measurements performed in neutron and photon fields allowed comparing dose spectra with those from Tissue Equivalent Proportional Counters and, additionally, to obtain particle track images. Some preliminary measurements performed to check the capabilities as the detector in proton tomography are also illustrated. The most important on-going developments are: (1) a new, larger area readout to cover the typical maximum field size in radiation therapy of 20 × 20 cm2; (2) a sealed and low-pressure version to facilitate measurements and to increase the equivalent spatial resolution for microdosimetry; (3) 3D particle track reconstruction when operating the GEMPix as a Time Projection Chamber.

scholarly journals DyTER – Dynamic Track and Event Reconstruction

2019 ◽  
Vol 214 ◽  
pp. 02026
Author(s):  
Michael Papenbrock
Keyword(s):  
Pattern Matching ◽  
Particle Track ◽  
Track Reconstruction ◽  
Proton Collisions ◽  
Panda Experiment ◽  
Event Reconstruction ◽  
Wide Range ◽  
Future Challenges ◽  
Event Rates ◽  
Specific Particle

The future PANDA experiment at FAIR experiment aims to cover a wide range of processes in antiproton-proton collisions at event rates of up to 20 MHz. Such event rates make reconstruction a challenging task for the purely software-based event filter. Investigating complex event topologies with displaced vertices increases the difficulty even further. Here we present two attempts to meet these future challenges: an algorithm for track reconstruction based on pattern matching with pre-determined look-up tables, and as a continuation of this approach a system of neural networks for identifying specific particle track candidates and predicting their momentum.

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