Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning
Autor(en):
Zusammenfassung
Intensity interferometry is part of optical interferometry, which provides a sub-milliarcsecond resolution of astronomical objects. In intensity interferometry one correlates intensities of optical fluxes rather than amplitudes of waves. For a successful measurement one needs a large light collecting area for several telescopes separated by hundreds of meters and good time resolution of the intensity flux. Air Cherenkov telescopes, e.g., H.E.S.S. are a natural candidate for performing such a measurement. One of the important tasks is to determine the rate of photons hitting the PMTs to calculate expectations on the signal-to-noise ratio. For low rates, the individual pulses can be resolved and counted, but for high rates, relevant for the IACTs, the pulses from the photons overlap. We use different neural network algorithms in order to determine the rate of photons hitting the PMT, including the high rates.
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- BibTeX
Bhanderi, Ji., Funk, St., Malyshev, Dm., Vogel, Na. & Zmija, An.,
(2022).
Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning.
In:
Demmler, D., Krupka, D. & Federrath, H.
(Hrsg.),
INFORMATIK 2022.
Gesellschaft für Informatik, Bonn.
(S. 507-516).
DOI: 10.18420/inf2022_42
@inproceedings{mci/Bhanderi2022,
author = {Bhanderi,Jigar AND Funk,Stefan AND Malyshev,Dmitry AND Vogel,Naomi AND Zmija,Andreas},
title = {Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 507-516 } ,
doi = { 10.18420/inf2022_42 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Bhanderi,Jigar AND Funk,Stefan AND Malyshev,Dmitry AND Vogel,Naomi AND Zmija,Andreas},
title = {Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 507-516 } ,
doi = { 10.18420/inf2022_42 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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Mehr Information
DOI: 10.18420/inf2022_42
ISBN: 978-3-88579-720-3
ISSN: 1617-5468
Datum: 2022
Sprache:
(en)
(en)
