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Register a new userAGILE results on relativistic outflows above 100 MeV
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Carlotta Pittori
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We give an overview of the AGILE gamma-ray satellite scientific highlights. AGILE is an Italian Space Agency (ASI) mission devoted to observations in the 30 MeV - 50 GeV gamma-ray energy range, with simultaneous X-ray imaging in the 18-60 keV band. Launched in April 2007, the AGILE satellite has completed its tenth year of operations in orbit, and it is substantially contributing to improve our knowledge of the high-energy sky. Emission from cosmic sources at energies above 100 MeV is intrinsically non-thermal, and the study of the wide variety of observed Galactic and extragalactic gamma-ray sources provides a unique opportunity to test theories of particle acceleration and radiation processes in extreme conditions.
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Carpet is an air-shower array at Baksan, Russia, equipped with a large-area muon detector, which makes it possible to separate primary photons from hadrons. We report first results of the search for primary photons with energies E>100 TeV. The experiments ongoing upgrade and future sensitivity are also discussed.
We present the first Fermi Large Area Telescope (LAT) low energy catalog (1FLE) of sources detected in the energy range 30 - 100 MeV. The COMPTEL telescope detected sources below 30 MeV, while catalogs released by the Fermi-LAT and EGRET collaborations use energies above 100 MeV. We create a list of sources detected in the energy range between 30 and 100 MeV, which closes a gap of point source analysis between the COMPTEL catalog and the Fermi-LAT catalogs. One of the main challenges in the analysis of point sources is the construction of the background diffuse emission model. In our analysis, we use a background-independent method to search for point-like sources based on a wavelet transform implemented in the PGWave code. The 1FLE contains 198 sources detected above 3 $sigma$ significance with eight years and nine months of the Fermi-LAT data. For 187 sources in the 1FLE catalog we have found an association in the Fermi-LAT 3FGL catalog: 148 are extragalactic, 22 are Galactic, and 17 are unclassified in the 3FGL. The ratio of the number of flat spectrum radio quasars (FSRQ) to BL Lacertae (BL Lacs) in 1FLE is 3 to 1, which can be compared with an approximately 1 to 1 ratio for the 3FGL or a 1 to 6 ratio for 3FHL. The higher ratio of the FSRQs in the 1FLE is expected due to generally softer spectra of FSRQs relative to BL Lacs. Most BL Lacs in 1FLE are of low-synchrotron peaked blazar type (18 out of 31), which have softer spectra and higher redshifts than BL Lacs on average. Correspondingly, we find that the average redshift of the BL Lacs in 1FLE is higher than in 3FGL or 3FHL. There are 11 sources that do not have associations in the 3FGL. Most of the unassociated sources either come from regions of bright diffuse emission or have several known 3FGL sources in the vicinity, which can lead to source confusion. The remaining unassociated sources have significance less than 4 $sigma$.
We give an overview of the SPHERE experiment based on detection of reflected Vavilov-Cherenkov radiation (Cherenkov light) from extensive air showers in the energy region E>10^{15} eV. A brief history of the reflected Cherenkov light technique is given; the observations carried out with the SPHERE-2 detector are summarized; the methods of the experimental datasample analysis are described. The first results on the primary cosmic ray all-nuclei energy spectrum and mass composition are presented. Finally, the prospects of the SPHERE experiment and the reflected Cherenkov light technique are given.
Due to the high energies and long distances involved, astrophysical observations provide a unique opportunity to test possible signatures of Lorentz Invariance Violation (LIV). Superluminal LIV enables the decay of photons at high energy over relatively short distances, giving astrophysical spectra which have a hard cutoff above this energy. The High Altitude Water Cherenkov (HAWC) observatory is the most sensitive currently-operating gamma-ray observatory in the world above 10 TeV. Together with the recent development of an energy-reconstruction algorithm for HAWC using an artificial neural network, HAWC can make detailed measurements of gamma-ray energies above 100 TeV. With these observations, HAWC can limit the LIV energy scale greater than $10^{31}$ eV, over 800 times the Planck energy scale. This limit on LIV is over 60 times more constraining than the best previous value for $rm E_{LIV}^{(1)}$.
The follow-up of external science alerts received from Gamma-Ray Bursts (GRB) and Gravitational Waves (GW) detectors is one of the AGILE Teams current major activities. The AGILE team developed an automated real-time analysis pipeline to analyse AGILE Gamma-Ray Imaging Detector (GRID) data to detect possible counterparts in the energy range 0.1-10 GeV. This work presents a new approach for detecting GRBs using a Convolutional Neural Network (CNN) to classify the AGILE-GRID intensity maps improving the GRBs detection capability over the Li&Ma method, currently used by the AGILE team. The CNN is trained with large simulated datasets of intensity maps. The AGILE complex observing pattern due to the so-called spinning mode is studied to prepare datasets to test and evaluate the CNN. A GRB emission model is defined from the Second Fermi-LAT GRB catalogue and convoluted with the AGILE observing pattern. Different p-value distributions are calculated evaluating with the CNN millions of background-only maps simulated varying the background level. The CNN is then used on real data to analyse the AGILE-GRID data archive, searching for GRB detections using the trigger time and position taken from the Swift-BAT, Fermi-GBM, and Fermi-LAT GRB catalogues. From these catalogues, the CNN detects 21 GRBs with a significance $geq 3 sigma$, while the Li&Ma method detects only two GRBs. The results shown in this work demonstrate that the CNN is more effective in detecting GRBs than the Li&Ma method in this context and can be implemented into the AGILE-GRID real-time analysis pipeline.
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