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Measurement of the extragalactic background (EGBR) of diffuse gamma-rays is perhaps one of the most challenging tasks for future gamma-ray observatories, such as GLAST. This is because any determination will depend on accurate subtraction…

Astrophysics · Physics 2007-08-02 A. Sellerholm , J. Conrad , L. Bergstrom , J. Edsjo

Selecting between different dependency structures of hidden Markov random field can be very challenging, due to the intractable normalizing constant in the likelihood. We answer this question with approximate Bayesian computation (ABC)…

Statistics Theory · Mathematics 2019-09-04 Julien Stoehr , Pierre Pudlo , Lionel Cucala

One way to understand the nonthermal history of the universe is by establishing the origins of the unresolved and truly diffuse extragalactic gamma rays. Dim blazars and radio/gamma galaxies certainly make an important contribution to the…

Astrophysics · Physics 2009-06-23 Charles D. Dermer

We present an algorithm capable of detecting diffuse, dim sources of any size in an astronomical image. These sources often defeat traditional methods for source finding, which expand regions around points of high intensity. Extended…

Instrumentation and Methods for Astrophysics · Physics 2016-01-05 T. Butler-Yeoman , M. Frean , C. P. Hollitt , D. W. Hogg , M. Johnston-Hollitt

To reveal natures of the dark matter (DM) particles, a gamma-ray signal produced in annihilation processes of DM into the standard model particles has been one of the major probes. The cross-correlation between highly DM dominated…

Cosmology and Nongalactic Astrophysics · Physics 2022-02-04 Daiki Hashimoto , Atsushi J. Nishizawa , Masahiro Takada

The extragalactic cosmic gamma-ray background (CGB) is an interesting channel to look for signatures of dark matter annihilation. In particular, besides the imprint in the energy spectrum, peculiar anisotropy patterns are expected compared…

We perform a detailed study of the sensitivity to the anisotropies related to Dark Matter (DM) annihilation in the Isotropic Gamma-Ray Background (IGRB) as measured by the Fermi Large Area Telescope (Fermi-LAT). For the first time, we take…

High Energy Astrophysical Phenomena · Physics 2011-09-07 A. Cuoco , A. Sellerholm , J. Conrad , S. Hannestad

We consider the emission of high energy to very high energy $\gamma$-rays in radio-quiet active galactic nuclei (AGN) or the central regions of radio-loud AGN. We use our results to estimate the $\gamma$-ray flux from the central regions of…

Astrophysics · Physics 2011-05-12 P. A. Johnson , A. Mastichiadis , R. J. Protheroe , T. S. Stanev , A. P. Szabo

We calculate the flux of $\gamma$-rays emitted from primordial black holes (PBHs) which are formed by a ``blue'' power-law spectrum of density fluctuations in the early universe. Gamma-ray emission from such PBHs may contribute…

Astrophysics · Physics 2009-10-31 Hee Il Kim , Chul H. Lee , Jane H. MacGibbon

Approximate Bayesian Computation (ABC) is a family of statistical inference techniques, which is increasingly used in biology and other scientific fields. Its main benefit is to be applicable to models for which the computation of the model…

Quantitative Methods · Quantitative Biology 2014-12-25 Franck Jabot , Guillaume Lagarrigues , Benoît Courbaud , Nicolas Dumoulin

In the following article we consider approximate Bayesian computation (ABC) for certain classes of time series models. In particular, we focus upon scenarios where the likelihoods of the observations and parameter are intractable, by which…

Computation · Statistics 2014-01-03 Ajay Jasra

The recent deep X-ray surveys at both soft (0.5--2 keV) and hard (2--10 keV) energies have greatly extended our knowledge of the X-ray source density and spectral shapes at relatively faint fluxes adding further evidence on the fact that…

Astrophysics · Physics 2007-05-23 A. Comastri

Many models of interest in the natural and social sciences have no closed-form likelihood function, which means that they cannot be treated using the usual techniques of statistical inference. In the case where such models can be…

Computation · Statistics 2012-07-19 Simon Barthelmé , Nicolas Chopin

Given the complexity of modern cosmological parameter inference where we are faced with non-Gaussian data and noise, correlated systematics and multi-probe correlated data sets, the Approximate Bayesian Computation (ABC) method is a…

Instrumentation and Methods for Astrophysics · Physics 2017-03-08 Elise Jennings , Maeve Madigan

Various studies firmly establish the fact that gamma-ray observations can act as a unique probe to detect the possible cosmic ray (CR) sources, study the CR density distribution and explore the average properties of interstellar medium…

High Energy Astrophysical Phenomena · Physics 2020-01-08 Sayan Biswas , Nayantara Gupta

Approximate Bayesian computation (ABC) is a class of algorithmic methods in Bayesian inference using statistical summaries and computer simulations. ABC has become popular in evolutionary genetics and in other branches of biology. However…

Computation · Statistics 2011-05-03 Olivier Francois , Guillaume Laval

We have developed a new Bayesian method to correct the flux densities of astronomical sources. The hybrid method combines a simulated likelihood to model survey selection together with an analytic source-count-based prior. The simulated…

Astrophysics of Galaxies · Physics 2020-04-29 Megan B. Gralla , Tobias A. Marriage

Our ability to extract the maximal amount of information from future observations at gigahertz frequencies depends on our ability to separate the underlying cosmic microwave background (CMB) from galactic and extragalactic foregrounds. We…

Astrophysics · Physics 2007-05-23 J. Jewell , C. R. Lawrence , S. Levin

In addition to gamma-rays, dark matter annihilation products can include energetic electrons which inverse Compton scatter with the cosmic microwave background to produce a diffuse extragalactic background of gamma-rays and X-rays. In…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-13 Alexander V. Belikov , Dan Hooper

Approximate Bayesian Computation (ABC) is a powerful method for carrying out Bayesian inference when the likelihood is computationally intractable. However, a drawback of ABC is that it is an approximate method that induces a systematic…

Methodology · Statistics 2015-09-29 Minh Ngoc Tran , Robert Kohn