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Title:
Dark matter line searches with the Cherenkov Telescope Array
Authors:
ID
Abe, S.
(Author)
ID
Bhattacharyya, Saptashwa
(Author)
ID
Eckner, Christopher
(Author)
ID
Pérez Romero, Judit
(Author)
ID
Stanič, Samo
(Author)
ID
Vodeb, Veronika
(Author)
ID
Vorobiov, Serguei
(Author)
ID
Zaharijas, Gabrijela
(Author)
ID
Zavrtanik, Danilo
(Author)
ID
Zavrtanik, Marko
(Author)
ID
Živec, Miha
(Author), et al.
Files:
https://iopscience.iop.org/article/10.1088/1475-7516/2024/07/047
Abe_2024_J._Cosmol._Astropart._Phys._2024_047.pdf
(2,04 MB)
MD5: 2F73AB3801D61BA443E529EDB52B9FE8
https://iopscience.iop.org/article/10.1088/1475-7516/2024/07/047
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.
Language:
English
Work type:
Unknown
Typology:
1.01 - Original Scientific Article
Organization:
UNG - University of Nova Gorica
Abstract:
Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g. box-shaped spectra, that would likewise very clearly point to a particle dark matter origin.
Keywords:
dark matter experiments
,
dark matter theory
,
gamma ray experiments
,
Cherenkov Telescope Array Observatory
Publication status:
Published
Publication version:
Version of Record
Publication date:
01.07.2024
Year of publishing:
2024
Number of pages:
str. 1-61
Numbering:
Vol. 2024, no. 7, [article no.] 047
PID:
20.500.12556/RUNG-9344
COBISS.SI-ID:
208755715
UDC:
52
ISSN on article:
1475-7516
eISSN:
1475-7516
DOI:
10.1088/1475-7516/2024/07/047
NUK URN:
URN:SI:UNG:REP:FRYNY3KC
Publication date in RUNG:
24.09.2024
Views:
481
Downloads:
5
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Record is a part of a journal
Title:
Journal of cosmology and astroparticle physics
Publisher:
Institute of Physics Pub.
ISSN:
1475-7516
COBISS.SI-ID:
389627
Document is financed by a project
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P1-0031
Name:
Večglasniška astrofizika
Funder:
ARRS - Slovenian Research Agency
Project number:
P1-0385
Name:
Daljinsko zaznavanje atmosferskih lastnosti
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
I0-0033
Name:
Infrastrukturni program Univerze v Novi Gorici
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
J1-9146
Name:
Novi detektorji in tehnike daljinskega zaznavanja atmosferskih lastnosti za polja Čerenkovih teleskopov
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
J1-1700
Name:
Priprava na iskanje temne snovi z observatorijem Cherenkov Telescope Array z uporabo strojnega ucenja
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
N1-0111
Name:
Identifikacija izvorov kozmičnih žarkov med aktivnimi galaksijami s curki
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:
19.07.2024
License:
Other
Description:
https://iopscience.iop.org/info/page/text-and-data-mining
Licensing start date:
19.07.2024
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