Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Mánek, Petr | |
dc.contributor.author | Bergmann, Benedikt | |
dc.contributor.author | Burian, Petr | |
dc.contributor.author | Garvey, Declan | |
dc.contributor.author | Meduna, Lukáš | |
dc.contributor.author | Pospíšil, Stanislav | |
dc.contributor.author | Smolyanskiy, Petr | |
dc.contributor.author | White, E. | |
dc.date.accessioned | 2023-02-06T11:00:22Z | - |
dc.date.available | 2023-02-06T11:00:22Z | - |
dc.date.issued | 2022 | |
dc.identifier.citation | MÁNEK, P. BERGMANN, B. BURIAN, P. GARVEY, D. MEDUNA, L. POSPÍŠIL, S. SMOLYANSKIY, P. WHITE, E. Improved algorithms for determination of particle directions with Timepix3 . Journal of Instrumentation, 2022, roč. 17, č. 1, s. nestránkováno. ISSN: 1748-0221 | cs |
dc.identifier.issn | 1748-0221 | |
dc.identifier.uri | 2-s2.0-85125544942 | |
dc.identifier.uri | http://hdl.handle.net/11025/51325 | |
dc.description.abstract | Timepix3 pixel detectors have demonstrated great potential for tracking applications. With 256 × 256 pixels, 55 μm pitch and improved resolution in time (1.56 ns) and energy (2 keV at 60 keV), they have become powerful instruments for characterization of unknown radiation fields. A crucial pre-processing step for such analysis is the determination of particle trajectories in 3D space from individual tracks. This study presents a comprehensive comparison of regression methods that tackle this task under the assumption of track linearity. The proposed methods were first evaluated on a simulation and assessed by their accuracy and computational time. Selected methods were then validated with a real-world dataset, which was measured in a well-known radiation field. Finally, the presented methods were applied to experimental data from the Large Hadron Collider. The best-performing methods achieved a mean absolute error of 1.99° and 3.90° in incidence angle θ and azimuth φ, respectively. The fastest presented method required a mean computational time of 0.02 ps per track. For all experimental applications, we present angular maps and stopping power spectra. | de |
dc.format | 11 s. | cs |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | IOP Publishing | en |
dc.relation.ispartofseries | Journal of Instrumentation | en |
dc.rights | Plný text není přístupný. | cs |
dc.rights | © IOP Publishing Ltd and Sissa Medialab | en |
dc.title | Improved algorithms for determination of particle directions with Timepix3 | en |
dc.type | článek | cs |
dc.type | article | en |
dc.rights.access | closedAccess | en |
dc.type.version | publishedVersion | en |
dc.description.abstract-translated | Timepix3 pixel detectors have demonstrated great potential for tracking applications. With 256 × 256 pixels, 55 μm pitch and improved resolution in time (1.56 ns) and energy (2 keV at 60 keV), they have become powerful instruments for characterization of unknown radiation fields. A crucial pre-processing step for such analysis is the determination of particle trajectories in 3D space from individual tracks. This study presents a comprehensive comparison of regression methods that tackle this task under the assumption of track linearity. The proposed methods were first evaluated on a simulation and assessed by their accuracy and computational time. Selected methods were then validated with a real-world dataset, which was measured in a well-known radiation field. Finally, the presented methods were applied to experimental data from the Large Hadron Collider. The best-performing methods achieved a mean absolute error of 1.99° and 3.90° in incidence angle θ and azimuth φ, respectively. The fastest presented method required a mean computational time of 0.02 ps per track. For all experimental applications, we present angular maps and stopping power spectra. | en |
dc.subject.translated | analysis and statistical methods | en |
dc.subject.translated | data processing methods | en |
dc.subject.translated | data reduction methods | en |
dc.subject.translated | dattern recognition, cluster finding, calibration and fitting methods | en |
dc.identifier.doi | 10.1088/1748-0221/17/01/C01062 | |
dc.type.status | Peer-reviewed | en |
dc.identifier.document-number | 766150700003 | |
dc.identifier.obd | 43938085 | |
Appears in Collections: | Články / Articles (KEI) OBD |
Files in This Item:
File | Size | Format | |
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Mánek_2022_J._Inst._17_C01062.pdf | 1,42 MB | Adobe PDF | View/Open Request a copy |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/51325
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