Potentiality of automatic parameter tuning suite available in ACTS track reconstruction software framework Article Swipe
YOU?
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· 2024
· Open Access
·
· DOI: https://doi.org/10.1051/epjconf/202429503031
Particle tracking is among the most sophisticated and complex part of the full event reconstruction chain. A number of reconstruction algorithms work in a sequence to build these trajectories from detector hits. Each of these algorithms use many configuration parameters that need to be fine-tuned to properly account for the detector/experimental setup, the available CPU budget and the desired physics performance. Few examples of such parameters include the cut values limiting the search space of the algorithm, the approximations accounting for complex phenomena or the parameters controlling algorithm performance. The most popular method to tune these parameters is hand-tuning using brute-force techniques. These techniques can be inefficient and raise issues for the long-term maintainability of such algorithms. The opensource track reconstruction software framework known as “A Common Tracking Framework (ACTS)” offers an alternative solution to these parameter tuning techniques through the use of automatic parameter optimization algorithms. ACTS come equipped with an auto-tuning suite that provides necessary setup for performing optimization of input parameters belonging to track reconstruction algorithms. The user can choose the tunable parameters in a flexible way and define a cost/benefit function for optimizing the full reconstruction chain. The fast execution speed of ACTS allows the user to run several iterations of optimization within a reasonable time bracket. The performance of these optimizers has been demonstrated on different track reconstruction algorithms such as trajectory seed reconstruction and selection, particle vertex reconstruction and generation of simplified material map, and on different detector geometries such as Generic Detector and Open Data Detector (ODD). We aim to bring this approach to all aspects of trajectory reconstruction by having a more flexible integration of tunable parameters within ACTS.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1051/epjconf/202429503031
- https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_03031.pdf
- OA Status
- diamond
- References
- 6
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396671491
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4396671491Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1051/epjconf/202429503031Digital Object Identifier
- Title
-
Potentiality of automatic parameter tuning suite available in ACTS track reconstruction software frameworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
R. B. Garg, C. Allaire, A. Salzburger, Hadrien Grasland, L. Tompkins, E. HofgardList of authors in order
- Landing page
-
https://doi.org/10.1051/epjconf/202429503031Publisher landing page
- PDF URL
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https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_03031.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_03031.pdfDirect OA link when available
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Suite, Track (disk drive), Software, Software suite, Computer science, Operating system, Geography, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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6Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3173346260, https://openalex.org/W3156538130, https://openalex.org/W6969380257, https://openalex.org/W2949676527, https://openalex.org/W2128158076, https://openalex.org/W2990714382 |
| referenced_works_count | 6 |
| abstract_inverted_index.A | 16 |
| abstract_inverted_index.a | 23, 177, 182, 207, 268 |
| abstract_inverted_index.We | 254 |
| abstract_inverted_index.an | 131, 151 |
| abstract_inverted_index.as | 124, 225, 246 |
| abstract_inverted_index.be | 43, 105 |
| abstract_inverted_index.by | 266 |
| abstract_inverted_index.in | 22, 176 |
| abstract_inverted_index.is | 2, 97 |
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| abstract_inverted_index.on | 219, 241 |
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| abstract_inverted_index.to | 25, 42, 45, 93, 134, 165, 200, 256, 260 |
| abstract_inverted_index.CPU | 54 |
| abstract_inverted_index.Few | 61 |
| abstract_inverted_index.The | 89, 117, 169, 191, 211 |
| abstract_inverted_index.aim | 255 |
| abstract_inverted_index.all | 261 |
| abstract_inverted_index.and | 7, 56, 107, 180, 229, 234, 240, 249 |
| abstract_inverted_index.can | 104, 171 |
| abstract_inverted_index.cut | 68 |
| abstract_inverted_index.for | 48, 80, 110, 158, 185 |
| abstract_inverted_index.has | 216 |
| abstract_inverted_index.run | 201 |
| abstract_inverted_index.the | 4, 11, 49, 52, 57, 67, 71, 75, 77, 84, 111, 140, 173, 187, 198 |
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| abstract_inverted_index.way | 179 |
| abstract_inverted_index.ACTS | 147, 196 |
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| abstract_inverted_index.Open | 250 |
| abstract_inverted_index.been | 217 |
| abstract_inverted_index.come | 148 |
| abstract_inverted_index.fast | 192 |
| abstract_inverted_index.from | 29 |
| abstract_inverted_index.full | 12, 188 |
| abstract_inverted_index.many | 37 |
| abstract_inverted_index.map, | 239 |
| abstract_inverted_index.more | 269 |
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| abstract_inverted_index.part | 9 |
| abstract_inverted_index.seed | 227 |
| abstract_inverted_index.such | 64, 115, 224, 245 |
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| abstract_inverted_index.this | 258 |
| abstract_inverted_index.time | 209 |
| abstract_inverted_index.tune | 94 |
| abstract_inverted_index.user | 170, 199 |
| abstract_inverted_index.with | 150 |
| abstract_inverted_index.work | 21 |
| abstract_inverted_index.“A | 125 |
| abstract_inverted_index.ACTS. | 276 |
| abstract_inverted_index.These | 102 |
| abstract_inverted_index.among | 3 |
| abstract_inverted_index.bring | 257 |
| abstract_inverted_index.build | 26 |
| abstract_inverted_index.event | 13 |
| abstract_inverted_index.hits. | 31 |
| abstract_inverted_index.input | 162 |
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| abstract_inverted_index.raise | 108 |
| abstract_inverted_index.setup | 157 |
| abstract_inverted_index.space | 73 |
| abstract_inverted_index.speed | 194 |
| abstract_inverted_index.suite | 153 |
| abstract_inverted_index.these | 27, 34, 95, 135, 214 |
| abstract_inverted_index.track | 119, 166, 221 |
| abstract_inverted_index.using | 99 |
| abstract_inverted_index.(ODD). | 253 |
| abstract_inverted_index.Common | 126 |
| abstract_inverted_index.allows | 197 |
| abstract_inverted_index.budget | 55 |
| abstract_inverted_index.chain. | 15, 190 |
| abstract_inverted_index.choose | 172 |
| abstract_inverted_index.define | 181 |
| abstract_inverted_index.having | 267 |
| abstract_inverted_index.issues | 109 |
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| abstract_inverted_index.offers | 130 |
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| abstract_inverted_index.setup, | 51 |
| abstract_inverted_index.tuning | 137 |
| abstract_inverted_index.values | 69 |
| abstract_inverted_index.vertex | 232 |
| abstract_inverted_index.within | 206, 275 |
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| abstract_inverted_index.account | 47 |
| abstract_inverted_index.aspects | 262 |
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| abstract_inverted_index.include | 66 |
| abstract_inverted_index.physics | 59 |
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| abstract_inverted_index.through | 139 |
| abstract_inverted_index.tunable | 174, 273 |
| abstract_inverted_index.Detector | 248, 252 |
| abstract_inverted_index.Particle | 0 |
| abstract_inverted_index.Tracking | 127 |
| abstract_inverted_index.approach | 259 |
| abstract_inverted_index.bracket. | 210 |
| abstract_inverted_index.detector | 30, 243 |
| abstract_inverted_index.equipped | 149 |
| abstract_inverted_index.examples | 62 |
| abstract_inverted_index.flexible | 178, 270 |
| abstract_inverted_index.function | 184 |
| abstract_inverted_index.limiting | 70 |
| abstract_inverted_index.material | 238 |
| abstract_inverted_index.particle | 231 |
| abstract_inverted_index.properly | 46 |
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| abstract_inverted_index.software | 121 |
| abstract_inverted_index.solution | 133 |
| abstract_inverted_index.tracking | 1 |
| abstract_inverted_index.(ACTS)” | 129 |
| abstract_inverted_index.Framework | 128 |
| abstract_inverted_index.algorithm | 87 |
| abstract_inverted_index.automatic | 143 |
| abstract_inverted_index.available | 53 |
| abstract_inverted_index.belonging | 164 |
| abstract_inverted_index.different | 220, 242 |
| abstract_inverted_index.execution | 193 |
| abstract_inverted_index.framework | 122 |
| abstract_inverted_index.long-term | 112 |
| abstract_inverted_index.necessary | 156 |
| abstract_inverted_index.parameter | 136, 144 |
| abstract_inverted_index.phenomena | 82 |
| abstract_inverted_index.accounting | 79 |
| abstract_inverted_index.algorithm, | 76 |
| abstract_inverted_index.algorithms | 20, 35, 223 |
| abstract_inverted_index.fine-tuned | 44 |
| abstract_inverted_index.generation | 235 |
| abstract_inverted_index.geometries | 244 |
| abstract_inverted_index.iterations | 203 |
| abstract_inverted_index.opensource | 118 |
| abstract_inverted_index.optimizers | 215 |
| abstract_inverted_index.optimizing | 186 |
| abstract_inverted_index.parameters | 39, 65, 85, 96, 163, 175, 274 |
| abstract_inverted_index.performing | 159 |
| abstract_inverted_index.reasonable | 208 |
| abstract_inverted_index.selection, | 230 |
| abstract_inverted_index.simplified | 237 |
| abstract_inverted_index.techniques | 103, 138 |
| abstract_inverted_index.trajectory | 226, 264 |
| abstract_inverted_index.algorithms. | 116, 146, 168 |
| abstract_inverted_index.alternative | 132 |
| abstract_inverted_index.auto-tuning | 152 |
| abstract_inverted_index.brute-force | 100 |
| abstract_inverted_index.controlling | 86 |
| abstract_inverted_index.hand-tuning | 98 |
| abstract_inverted_index.inefficient | 106 |
| abstract_inverted_index.integration | 271 |
| abstract_inverted_index.performance | 212 |
| abstract_inverted_index.techniques. | 101 |
| abstract_inverted_index.cost/benefit | 183 |
| abstract_inverted_index.demonstrated | 218 |
| abstract_inverted_index.optimization | 145, 160, 205 |
| abstract_inverted_index.performance. | 60, 88 |
| abstract_inverted_index.trajectories | 28 |
| abstract_inverted_index.configuration | 38 |
| abstract_inverted_index.sophisticated | 6 |
| abstract_inverted_index.approximations | 78 |
| abstract_inverted_index.reconstruction | 14, 19, 120, 167, 189, 222, 228, 233, 265 |
| abstract_inverted_index.maintainability | 113 |
| abstract_inverted_index.detector/experimental | 50 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.11101995 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |