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Indirect searches for dark matter using dwarf spheroidal galaxies are limited by systematic uncertainties in modeling diffuse gamma-ray backgrounds. We present a likelihood-based comparison of locally constructed empirical background models…

High Energy Astrophysical Phenomena · Physics 2026-03-06 Chance Hoskinson , Jason Kumar , Pearl Sandick

Recent advances in gamma-ray cosmic ray, infrared and radio astronomy have allowed us to develop a significantly better understanding of the galactic medium properties in the last few years. In this work using the DRAGON code, that…

High Energy Astrophysical Phenomena · Physics 2014-03-05 Maryam Tavakoli , Ilias Cholis , Carmelo Evoli , Piero Ullio

Composite likelihood provides approximate inference when the full likelihood is intractable and sub-likelihood functions of marginal events can be evaluated relatively easily. It has been successfully applied for many complex models.…

Methodology · Statistics 2024-09-05 Wentao Li , Rosabeth White , Dennis Prangle

We perform a detailed examination of current constraints on annihilating and decaying dark matter models from both prompt and inverse-Compton emission photons, including both model-dependent and model-independent bounds. We also show that…

High Energy Physics - Phenomenology · Physics 2012-02-13 Kevork N. Abazajian , Steve Blanchet , J. Patrick Harding

Observations of diffuse Galactic gamma ray emission (DGE) by the Fermi Large Area Telescope (LAT) allow a detailed study of cosmic rays and the interstellar medium. However, diffuse emission models of the inner Galaxy underpredict the…

Cosmology and Nongalactic Astrophysics · Physics 2014-04-03 Lin F. Yang , Joseph Silk , Alexander S. Szalay , Rosemary F. G. Wyse , Brandon Bozek , Piero Madau

Our present understanding of the extragalactic source counts and background radiation at infrared and sub-mm wavelengths is reviewed. Available count data are used to constrain evolutionary models of galaxies and Active Nuclei. The CIRB, on…

For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations…

Computation · Statistics 2011-07-04 Chris Barnes , Sarah Filippi , Michael P. H. Stumpf , Thomas Thorne

The global contribution of unresolved gamma-ray point sources to the extragalactic gamma-ray background has been recently measured down to gamma-ray fluxes lower than those reached with standard source detection techniques, and by employing…

High Energy Astrophysical Phenomena · Physics 2020-05-27 Silvia Manconi , Michael Korsmeier , Fiorenza Donato , Nicolao Fornengo , Marco Regis , Hannes Zechlin

The flux of the diffuse gamma-ray background radiation (GBR) does not confirm that the excess in the flux of cosmic ray electrons between 300-800 GeV, which was measured locally with the ATIC instrument in balloon flights over Antartica, is…

High Energy Astrophysical Phenomena · Physics 2011-09-28 Shlomo Dado , Arnon Dar

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract this information (at least partially) but they require sophisticated statistical techniques that have been made…

Approximate Bayesian computation (ABC) using a sequential Monte Carlo method provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in differential equations. However, this method, like other…

Machine Learning · Statistics 2015-07-21 Sanmitra Ghosh , Srinandan Dasmahapatra , Koushik Maharatna

Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bayesian Computation (ABC) is devoted to these complex…

Populations and Evolution · Quantitative Biology 2011-06-15 Katalin Csilléry , Olivier François , Michael GB Blum

The ability to efficiently infer system parameters is essential in any signal-processing task that requires fast operation. Dealing with quantum systems, a serious challenge arises due to substantial growth of the underlying Hilbert space…

Quantum Physics · Physics 2025-04-23 Lewis A. Clark , Jan Kolodynski

Approximate Bayesian Computation (ABC) can be viewed as an analytic approximation of an intractable likelihood coupled with an elementary simulation step. Such a view, combined with a suitable instrumental prior distribution permits…

Methodology · Statistics 2013-01-04 F. J. Rubio , Adam M. Johansen

The isotropic diffuse $\gamma$-ray background (IGRB) has been detected by various experiments and recently the Fermi-LAT Collaboration has precisely measured its spectrum in a wide energy range. The origin of the IGRB is still unclear and…

High Energy Astrophysical Phenomena · Physics 2016-06-22 Mattia Di Mauro

Annihilation of dark matter particles in cosmological halos (including a halo of the Milky Way) contributes to the diffuse gamma-ray background (DGRB). As this contribution will appear anisotropic in the sky, one can use the angular power…

Cosmology and Nongalactic Astrophysics · Physics 2013-07-31 Shin'ichiro Ando , Eiichiro Komatsu

If dark matter is composed of neutralinos, the gamma-ray radiation produced in their annihilation offers an attractive possibility for dark matter detection. This process may contribute significantly to the extragalactic gamma-ray…

Cosmology and Nongalactic Astrophysics · Physics 2010-01-20 Jesus Zavala , Volker Springel , Michael Boylan-Kolchin

The origin of the extragalactic $\gamma$-ray background (EGB) has been debated for some time. { The EGB comprises the $\gamma$-ray emission from resolved and unresolved extragalactic sources, such as blazars, star-forming galaxies and radio…

(Abridged) The extragalactic background light (EBL) observed at multiple wavelengths is a promising tool to probe the nature of dark matter since it might contain a significant contribution from gamma-rays produced promptly by dark matter…

Cosmology and Nongalactic Astrophysics · Physics 2011-06-30 Jesus Zavala , Mark Vogelsberger , Tracy R. Slatyer , Abraham Loeb , Volker Springel

Approximate Bayesian Computation (ABC) is a statistical learning technique to calibrate and select models by comparing observed data to simulated data. This technique bypasses the use of the likelihood and requires only the ability to…

Computation · Statistics 2021-05-04 Pierre-Olivier Goffard , Patrick J. Laub