Preprint

PUBDB-2022-00968

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Calomplification - The Power of Generative Calorimeter Models

Bieringer, S. G. (Corresponding author)Extern* ; Anja Butter ; Diefenbacher, S. D.Extern* ; Eren, E.DESY* ; Gaede, F.DESY* ; Hundhausen, D. C.Extern* ; Kasieczka, G.Extern* ; Nachman, B.Extern* ; Plehn, T. ; Mathias Trabs, K.

2022

This record in other databases:  

Please use a persistent id in citations: doi:10.3204/PUBDB-2022-00968

Report No.: DESY-22-031; arXiv:2202.07352

Abstract: Motivated by the high computational costs of classical simulations, machine-learned gen- erative models can be extremely useful in particle physics and elsewhere. They become especially attractive when surrogate models can efficiently learn the underlying distri- bution, 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 a highly-granular electromagnetic calorimeter.

Keyword(s): photon, showers ; calorimeter, electromagnetic ; costs

Note: 17 pages, 10 figures

---

Contributing Institute(s):

1. Technol. zukünft. Teilchenph. Experim. (FTX)

Research Program(s):

1. 623 - Data Management and Analysis (POF4-623) (POF4-623)

Experiment(s):

1. No specific instrument

Appears in the scientific report 2022

---

Database coverage:
; Published

---

---

Linked articles:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article Bieringer, S.Extern* ; Butter, A.Extern* ; Diefenbacher, S.Extern* ; Eren, E. (Corresponding author)DESY* ; Gaede, F.DESY* ; Hundhausen, D.Extern* ; Kasieczka, G.Extern* ; Nachman, B.Extern* ; Plehn, T. ; Trabs, M.
Calomplification — the power of generative calorimeter models
Journal of Instrumentation 17(09), P09028 (2022) [10.1088/1748-0221/17/09/P09028]2022     Files  Fulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS

---