Abstract
Context. The analysis of Fermi-Large Area Telescope (LAT) gamma-ray data in a given Region of Interest (RoI) usually consists of performing a binned log-likelihood fit in order to determine the sky model that after convolution with the instrument response best accounts for the distribution of observed counts. Aims. While tools are available to perform such a fit, it is not easy to check the goodness-of-fit. The difficulty of the assessment of the data-model agreement is twofold. First of all, the observed and predicted counts are binned in three dimensions (two spatial dimensions and one energy dimension) and comparing two 3D maps is not straightforward. Secondly, gamma-ray source spectra generally decrease with energy as the inverse of the energy square. As a consequence, the number of counts above several GeV generally falls into the Poisson regime, which precludes performing a simple χ2 test. Methods. We propose a method that overcomes these two obstacles by producing and comparing, at each pixel of the analyzed RoI, spatially integrated count spectra for data and model. The comparison follows a log-likelihood approach that extends the χ2 test to histograms with low statistics. This method can take into account likelihood weights that are used to account for systematic uncertainties. Results. We optimize the new method so that it provides a fast and reliable tool to assess the goodness-of-fit of Fermi-LAT data and we use it to check the latest gamma-ray source catalog on 10 years of data.
Highlights
Since its launch in June 2008, the Fermi Large Area Telescope (LAT, Atwood et al 2009) has been continuously observing the gamma-ray sky in the energy range between 30 MeV and 2 TeV
Fermi-LAT analyses are generally based on a binned loglikelihood fit of a 3D count map but there is no fast, reliable and sensitive tool available to check the goodness-of-fit
In order to overcome the lack of such a tool, we have developed a new method that allows Fermi
Summary
Since its launch in June 2008, the Fermi Large Area Telescope (LAT, Atwood et al 2009) has been continuously observing the gamma-ray sky in the energy range between 30 MeV and 2 TeV. The usual way to analyze LAT data in a given Region of Interest (RoI) is to bin the data in a 3D map (two spatial dimensions and one energy dimension 2) and search for the sky model that best predicts the number of gamma rays observed in this RoI. The Fermitools provide a method to quantify the datamodel agreement which is frequently used It consists of computing a test statistic (TS) map: at each pixel, the presence of an additional source is tested by computing twice the difference in log-likelihood obtained with and without the source. A TS = 25 corresponds to ∼ 4σ significance (Mattox et al 1996) The drawbacks of this method are twofold: it is computationally intensive and, above all, it is not sensitive to negative deviations (data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
