000 | 03730nam a22006015i 4500 | ||
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001 | 978-3-030-65771-0 | ||
003 | DE-He213 | ||
005 | 20220530131631.0 | ||
007 | cr nn 008mamaa | ||
008 | 210226s2021 sz | s |||| 0|eng d | ||
020 |
_a9783030657710 _9978-3-030-65771-0 |
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024 | 7 |
_a10.1007/978-3-030-65771-0 _2doi |
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072 | 7 |
_aPHP _2bicssc |
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072 | 7 |
_aSCI051000 _2bisacsh |
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072 | 7 |
_aPHP _2thema |
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082 | 0 | 4 |
_a539.73 _223 |
100 | 1 |
_aFrühwirth, Rudolf. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aPattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors _h[electronic resource] / _cby Rudolf Frühwirth, Are Strandlie. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
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300 |
_aXVII, 203 páginas86 ilustraciones, 39 ilustraciones in color. _bonline resource. |
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336 |
_atexto _btxt _2rdacontent |
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337 |
_acomputadora _bc _2rdamedia |
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338 |
_arecurso en línea _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aParticle Acceleration and Detection, _x2365-0877 |
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505 | 0 | _aPart 1. Introduction -- Chapter 1. Tracking Detectors -- Chapter 2. Event Reconstruction -- Chapter 3. Statistics and Numerical Methods -- Part 2. Track Reconstruction -- Chapter 4. Track Models -- Chapter 5. Track Finding -- Chapter 6. Track Fitting -- Part 3. Vertex Reconstruction -- Chapter 7. Vertex Finding -- Chapter 8. Vertex Fitting -- Chapter 9. Secondary Vertex Reconstruction -- Part 4. Case Studies -- Chapter 10. LHC Experiments. | |
506 | 0 | _aOpen Access | |
520 | _aThis open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments. . | ||
650 | 0 | _aParticle accelerators. | |
650 | 0 | _aMeasurement. | |
650 | 0 | _aMeasuring instruments. | |
650 | 0 | _aPattern recognition systems. | |
650 | 0 | _aMathematical physics. | |
650 | 1 | 4 | _aAccelerator Physics. |
650 | 2 | 4 | _aMeasurement Science and Instrumentation. |
650 | 2 | 4 | _aAutomated Pattern Recognition. |
650 | 2 | 4 | _aTheoretical, Mathematical and Computational Physics. |
700 | 1 |
_aStrandlie, Are. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030657703 |
776 | 0 | 8 |
_iPrinted edition: _z9783030657727 |
776 | 0 | 8 |
_iPrinted edition: _z9783030657734 |
830 | 0 |
_aParticle Acceleration and Detection, _x2365-0877 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-65771-0 |
912 | _aZDB-2-PHA | ||
912 | _aZDB-2-SXP | ||
912 | _aZDB-2-SOB | ||
999 |
_c153096 _d153096 |