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Gamma rays from clusters and groups of galaxies: Cosmic rays versus dark matter

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PHYSICAL REVIEW D
卷 80, 期 2, 页码 -

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AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.80.023005

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Clusters of galaxies have not yet been detected at gamma-ray frequencies; however, the recently launched Fermi Gamma-ray Space Telescope, formerly known as GLAST, could provide the first detections in the near future. Clusters are expected to emit gamma rays as a result of (1) a population of high-energy cosmic rays fueled by accretion, merger shocks, active galactic nuclei, and supernovae, and (2) particle dark-matter annihilation. In this paper, we ask the question of whether the Fermi telescope will be able to discriminate between the two emission processes. We present data-driven predictions for the gamma-ray emission from cosmic rays and dark matter for a large x-ray-flux-limited sample of galaxy clusters and groups. We point out that the gamma-ray signals from cosmic rays and dark matter can be comparable. In particular, we find that poor clusters and groups are the systems predicted to have the highest dark-matter to cosmic-ray emission ratio at gamma-ray energies. Based on detailed Fermi simulations, we study observational handles that might enable us to distinguish the two emission mechanisms, including the gamma-ray spectra, the spatial distribution of the signal, and the associated multiwavelength emissions. We also propose optimal hardness ratios, which will help us to understand the nature of the gamma-ray emission. Our study indicates that gamma rays from dark-matter annihilation with a high particle mass can be distinguished from a cosmic-ray spectrum even for fairly faint sources. Discriminating a cosmic-ray spectrum from a light dark-matter particle will be, instead, much more difficult, and will require long observations and/or a bright source. While the gamma-ray emission from our simulated clusters is extended, determining the spatial distribution with Fermi will be a challenging task requiring an optimal control of the backgrounds.

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