The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Dark matter and pulsar model constraints from Galactic Center Fermi-LAT gamma-ray observations
Open accessAbstract
Employing Fermi-LAT gamma-ray observations, several independent groups have found excess extended gamma-ray emission at the Galactic Center (GC). Both annihilating dark matter (DM) or a population of $\ensuremath{\sim}{10}^{3}$ unresolved millisecond pulsars (MSPs) are regarded as well-motivated possible explanations. However, there are significant uncertainties in the diffuse galactic background at the GC. We have performed a revaluation of these two models for the extended gamma-ray source at the GC by accounting for the systematic uncertainties of the Galactic diffuse emission model. We also marginalize over point-source and diffuse background parameters in the region of interest. We show that the excess emission is significantly more extended than a point source. We find that the DM (or pulsar-population) signal is larger than the systematic errors and therefore proceed to determine the sectors of parameter space that provide an acceptable fit to the data. We find that a population of 1000--2000 MSPs with parameters consistent with the average spectral shape of Fermi-LAT measured MSPs is able to fit the GC excess emission. For DM, we find that a pure ${\ensuremath{\tau}}^{+}{\ensuremath{\tau}}^{\ensuremath{-}}$ annihilation channel is not a good fit to the data. But a mixture of ${\ensuremath{\tau}}^{+}{\ensuremath{\tau}}^{\ensuremath{-}}$ and $b\overline{b}$ with a $⟨\ensuremath{\sigma}v⟩$ of order the thermal relic value and a DM mass of around 20 to 60 GeV provides an adequate fit.
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Metadata
- Authors
- Gordon, C., & Macías, O.
- Venue
- Physical Review D
- Publisher
- American Physical Society (APS)
- Published
- 2013-10-21
- Volume
- 88
- Issue
- 8
- ISSN
- 0556-2821 (ISSN-L)
- 1550-7998
- 1550-2368
- OpenAlex
- W2071587586
- Cited by
- 440
- References
- 49
- FWCI
- 36.36
- Type
- journal article
- Language
- en
- Open access
- green
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