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Cited by 308

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Limits to dark matter annihilation cross-section from a combined analysis of MAGIC and Fermi-LAT observations of dwarf satellite galaxies

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MAGIC collaboration·2016·Journal of Cosmology and Astroparticle Physics

Abstract

We present the first joint analysis of gamma-ray data from the MAGIC Cherenkov telescopes and the Fermi Large Area Telescope (LAT) to search for gamma-ray signals from dark matter annihilation in dwarf satellite galaxies. We combine 158 hours of Segue 1 observations with MAGIC with 6-year observations of 15 dwarf satellite galaxies by the Fermi-LAT. We obtain limits on the annihilation cross-section for dark matter particle masses between 10 GeV and 100 TeV—the widest mass range ever explored by a single gamma-ray analysis. These limits improve on previously published Fermi-LAT and MAGIC results by up to a factor of two at certain masses. Our new inclusive analysis approach is completely generic and can be used to perform a global, sensitivity-optimized dark matter search by combining data from present and future gamma-ray and neutrino detectors.

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Crossref · 10.1088/1475-7516/2016/02/039

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Metadata

Authors
MAGIC collaboration
Venue
Journal of Cosmology and Astroparticle Physics
Published
2016-02-01
Volume
2016
Issue
02
Pages
039-039
ISSN
  • 1475-7508 (ISSN-L)
  • 1475-7516
OpenAlex
W2257873680
Cited by
308
References
46
FWCI
14.69
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Limits to dark matter annihilation cross-section from a combined analysis of MAGIC and Fermi-LAT observations of dwarf satellite galaxies. https://app.cochat.ai/papers/10.1088/1475-7516/2016/02/039
The paper
MAGIC collaboration. (2016). Limits to dark matter annihilation cross-section from a combined analysis of MAGIC and Fermi-LAT observations of dwarf satellite galaxies. Journal of Cosmology and Astroparticle Physics. https://doi.org/10.1088/1475-7516/2016/02/039

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.