Ultra-high-energy (UHE) photons are an important tool for studying the high-energy Universe. A plausible source of photons with exa-eV (EeV) energy is provided by UHE cosmic rays (UHECRs) undergoing the Greisen–Zatsepin–Kuzmin process (Greisen 1966; Zatsepin & Kuzmin 1966) or pair production process (Blumenthal 1970) on a cosmic background radiation. In this context, the EeV photons can be a probe of both UHECR mass composition and the distribution of their sources (Gelmini, Kalashev & Semikoz 2008; Hooper, Taylor & Sarkar 2011). At the same time, the possible flux of photons produced by UHE protons in the vicinity of their sources by pion photoproduction or inelastic nuclear collisions would be noticeable only for relatively near sources, as the attenuation length of UHE photons is smaller than that of UHE protons; see, for example, Bhattacharjee & Sigl (2000) for a review. There also exists a class of so-called top-down models of UHECR generation that efficiently produce the UHE photons, for instance by the decay of heavy dark-matter particles (Berezinsky, Kachelriess & Vilenkin 1997; Kuzmin & Rubakov 1998) or by the radiation from cosmic strings (Berezinsky, Blasi & Vilenkin 1998). The search for the UHE photons was shown to be the most sensitive methodmore »
Approximate Bayesian Computation applied to the Diffuse Gamma-Ray Sky
Many sources contribute to the diffuse gamma-ray background (DGRB), including star forming galaxies, active galactic nuclei, and cosmic ray interactions in the Milky Way. Exotic sources, such as dark matter annihilation, may also make some contribution. The photon counts-in-pixels distribution is a powerful tool for analysing the DGRB and determining the relative contributions of different sources. However, including photon energy information in a likelihood analysis of the counts-in-pixels distribution quickly becomes computationally intractable as the number of source types and energy bins increase. Here, we apply the likelihood-free method of approximate Bayesian computation (ABC) to the problem. We consider a mock analysis that includes contributions from dark matter annihilation in Galactic subhaloes as well as astrophysical backgrounds. We show that our results using ABC are consistent with the exact likelihood when energy information is discarded, and that significantly tighter parameter constraints can be obtained with ABC when energy information is included. ABC presents a powerful tool for analysing the DGRB and understanding its varied origins.
- Publication Date:
- NSF-PAR ID:
- 10370801
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 516
- Issue:
- 2
- Page Range or eLocation-ID:
- p. 2326-2336
- ISSN:
- 0035-8711
- Publisher:
- Oxford University Press
- Sponsoring Org:
- National Science Foundation
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