Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userFermi-LAT data reprocessed with updated calibration constants
163
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Four years into the mission, the understanding of the performance of the Fermi Large Area Telescope (LAT) and data analysis have increased enormously since launch. Thanks to a careful analysis of flight data, we were able to trace back some of the most significant sources of systematic uncertainties to using non-optimal calibration constants for some of the detectors. In this paper we report on a major effort within the LAT Collaboration to update these constants, to use them to reprocess the first four years of raw data, and to investigate the improvements observed for low- and high-level analysis. The Pass 7 reprocessed data, also known as P7REP data, are still being validated against the original Pass~7 (P7) data by the LAT Collaboration and should be made public, along with the corresponding instrument response functions, in the spring of 2013.
rate research
Read More
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. 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 $chi^2$ test. We propose a method that overcomes these two obstacles by producing and comparing spatially integrated count spectra for data and model at each pixel of the analysed RoI. The comparison is performed following a log-likelihood approach that extends the $chi^2$ test to histograms with low statistics. This method can take into account likelihood weights that are used to account for systematic uncertainties. 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.
We present results of a study of the localization capability of Fermi-LAT, using a large set of blazars with precise radio locations. Since the width of the PSF decreases with energy, the performance is typically dominated by a few high energy photons, so it is important to properly characterize the high-energy PSF. Using such data, we have found a need to modify the pre-launch high-energy (greater than a few GeV) PSF derived from extensive Monte Carlo simulations of particle interactions in the LAT; the resulting data-based PSF is shown
To uniformly determine the properties of supernova remnants (SNRs) at high energies, we have developed the first systematic survey at energies from 1 to 100 GeV using data from the Fermi Large Area Telescope. Based on the spatial overlap of sources detected at GeV energies with SNRs known from radio surveys, we classify 30 sources as likely GeV SNRs. We also report 14 marginal associations and 245 flux upper limits. A mock catalog in which the positions of known remnants are scrambled in Galactic longitude, allows us to determine an upper limit of 22% on the number of GeV candidates falsely identified as SNRs. We have also developed a method to estimate spectral and spatial systematic errors arising from the diffuse interstellar emission model, a key component of all Galactic Fermi LAT analyses. By studying remnants uniformly in aggregate, we measure the GeV properties common to these objects and provide a crucial context for the detailed modeling of individual SNRs. Combining our GeV results with multiwavelength (MW) data, including radio, X-ray, and TeV, demonstrates the need for improvements to previously sufficient, simple models describing the GeV and radio emission from these objects. We model the GeV and MW emission from SNRs in aggregate to constrain their maximal contribution to observed Galactic cosmic rays.
A novel application of machine-learning (ML) based image processing algorithms is proposed to analyze an all-sky map (ASM) obtained using the Fermi Gamma-ray Space Telescope. An attempt was made to simulate a one-year ASM from a short-exposure ASM generated from one-week observation by applying three ML based image processing algorithms: dictionary learning, U-net, and Noise2Noise. Although the inference based on ML is less clear compared to standard likelihood analysis, the quality of the ASM was generally improved. In particular, the complicated diffuse emission associated with the galactic plane was successfully reproduced only from one-week observation data to mimic a ground truth (GT) generated from a one-year observation. Such ML algorithms can be implemented relatively easily to provide sharper images without various assumptions of emission models. In contrast, large deviations between simulated ML maps and GT map were found, which are attributed to the significant temporal variability of blazar-type active galactic nuclei (AGNs) over a year. Thus, the proposed ML methods are viable not only to improve the image quality of an ASM, but also to detect variable sources, such as AGNs, algorithmically, i.e., without human bias. Moreover, we argue that this approach is widely applicable to ASMs obtained by various other missions; thus, it has the potential to examine giant structures and transient events, both of which are rarely found in pointing observations.
Circinus galaxy is a nearby composite starburst/AGN system. In this work we re-analyze the GeV emission from Circinus with 10 years of {it Fermi}-LAT Pass 8 data. In the energy range of 1-500 GeV, the spectrum can be well fitted by a power-law model with a photon index of $Gamma$ = $2.20pm0.14$, and its photon flux is $(5.90pm1.04) times 10^{-10}$ photons cm$^{-2}$ s$^{-1}$. Our 0.1-500 GeV flux is several times lower than that reported in the previous literature, which is roughly in compliance with the empirical relation for star-forming and local group galaxies and might be reproduced by the interaction between cosmic rays and the interstellar medium. The ratio between the $gamma$-ray luminosity and the total infrared luminosity is near the proton calorimetric limit, indicating that Circinus may be a proton calorimeter. However, marginal evidence for variability of the $gamma$-ray emission is found in the timing analysis, which may indicate the activity of AGN jet. More {it Fermi}-LAT data and future observation of CTA are required to fully reveal the origin of its $gamma$-ray emission.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
