Journal Article PUBDB-2022-03543

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Calomplification — the power of generative calorimeter models

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2022
Inst. of Physics London

Journal of Instrumentation 17(09), P09028 () [10.1088/1748-0221/17/09/P09028]
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Report No.: DESY-22-111; arXiv:2202.07352

Abstract: Motivated by the high computational costs of classical simulations, machine-learned generative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distribution, such that a generated sample outperforms a training sample of limited size. This kind of GANplification has been observed for simple Gaussian models. We show the same effect for a physics simulation, specifically photon showers in an electromagnetic calorimeter.

Keyword(s): photon: showers ; calorimeter: electromagnetic ; costs ; Detector modelling and simulations I (interaction of radiation with matter ; interaction of photons with matter ; interaction of hadrons with matter ; etc) ; Simulation methods and programs ; Analysis and statistical methods ; Calorimeter methods

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Note: 17 pages, 10 figures

Contributing Institute(s):
  1. Technol. zukünft. Teilchenph. Experim. (FTX)
Research Program(s):
  1. 611 - Fundamental Particles and Forces (POF4-611) (POF4-611)
  2. HIDSS-0002 - DASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter (2019_IVF-HIDSS-0002) (2019_IVF-HIDSS-0002)
  3. DFG project 396021762 - TRR 257: Phänomenologische Elementarteilchenphysik nach der Higgs-Entdeckung (396021762) (396021762)
  4. DFG project 390900948 - EXC 2181: STRUKTUREN: Emergenz in Natur, Mathematik und komplexen Daten (390900948) (390900948)
  5. DFG project 390833306 - EXC 2121: Quantum Universe (390833306) (390833306)
Experiment(s):
  1. No specific instrument

Appears in the scientific report 2022
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Medline ; Creative Commons Attribution CC BY 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Essential Science Indicators ; IF < 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Calomplification - The Power of Generative Calorimeter Models
[10.3204/PUBDB-2022-00968]  GO OpenAccess  Download fulltext Files  Download fulltextFulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS


 Record created 2022-07-05, last modified 2025-07-15


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JINST_011P_0722 - Download fulltext PDF Download fulltext PDF (PDFA)
Bieringer_2022_J._Inst._17_P09028 - Download fulltext PDF Download fulltext PDF (PDFA)
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