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Register a new userCalibration of AGILE-GRID with In-Flight Data and Monte Carlo Simulations
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Context: AGILE is a gamma-ray astrophysics mission which has been in orbit since 23 April 2007 and continues to operate reliably. The gamma-ray detector, AGILE-GRID, has observed Galactic and extragalactic sources, many of which were collected in the first AGILE Catalog. Aims: We present the calibration of the AGILE-GRID using in-flight data and Monte Carlo simulations, producing Instrument Response Functions (IRFs) for the effective area A_eff), Energy Dispersion Probability (EDP), and Point Spread Function (PSF), each as a function of incident direction in instrument coordinates and energy. Methods: We performed Monte Carlo simulations at different gamma-ray energies and incident angles, including background rejection filters and Kalman filter-based gamma-ray reconstruction. Long integrations of in-flight observations of the Vela, Crab and Geminga sources in broad and narrow energy bands were used to validate and improve the accuracy of the instrument response functions. Results: The weighted average PSFs as a function of spectra correspond well to the data for all sources and energy bands. Conclusions: Changes in the interpolation of the PSF from Monte Carlo data and in the procedure for construction of the energy-weighted effective areas have improved the correspondence between predicted and observed fluxes and spectra of celestial calibration sources, reducing false positives and obviating the need for post-hoc energy-dependent scaling factors. The new IRFs have been publicly available from the Agile Science Data Centre since November 25, 2011, while the changes in the analysis software will be distributed in an upcoming release.
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AGILE is a mission of the Italian Space Agency (ASI) Scientific Program dedicated to gamma-ray astrophysics, operating in a low Earth orbit since April 23, 2007. It is designed to be a very light and compact instrument, capable of simultaneously detecting and imaging photons in the 18 keV to 60 keV X-ray energy band and in the 30 MeV{50 GeV gamma-ray energy with a good angular resolution (< 1 deg at 1 GeV). The core of the instrument is the Silicon Tracker complemented with a CsI calorimeter and a AntiCoincidence system forming the Gamma Ray Imaging Detector (GRID). Before launch, the GRID needed on-ground calibration with a tagged gamma-ray beam to estimate its performance and validate the Monte Carlo simulation. The GRID was calibrated using a tagged gamma-ray beam with energy up to 500 MeV at the Beam Test Facilities at the INFN Laboratori Nazionali di Frascati. These data are used to validate a GEANT3 based simulation by comparing the data and the Monte Carlo simulation by measuring the angular and energy resolutions. The GRID angular and energy resolutions obtained using the beam agree well with the Monte Carlo simulation. Therefore the simulation can be used to simulate the same performance on-light with high reliability.
The upcoming Cherenkov Telescope Array (CTA) ground-based gamma-ray observatory will open up our view of the very high energy Universe, offering an improvement in sensitivity of 5-10 times that of previous experiments. NectarCAM is one of the proposed cameras for the Medium-Sized Telescopes (MST) which have been designed to cover the core energy range of CTA, from 100 GeV to 10 TeV. The final camera will be capable of GHz sampling and provide a field of view of 8 degrees with its 265 modules of 7 photomultiplier each (for a total of 1855 pixels). In order to validate the performance of NectarCAM, a partially-equipped prototype has been constructed consisting of only the inner 61-modules. It has so far undergone testing at the integration test-bench facility in CEA Paris-Saclay (France) and on a prototype of the MST structure in Adlershof (Germany). To characterize the performance of the prototype, Monte Carlo simulations were conducted using a detailed model of the 61 module camera in the CORSIKA/sim_telarray framework. This contribution provides an overview of this work including the comparison of trigger and readout performance on test-bench data and trigger and image parameterization performance during on-sky measurements.
The accuracy of Monte Carlo simulations in reproducing the scientific performance of space telescopes (e.g. angular resolution) is mandatory for a correct design of the mission. A brand-new Monte Carlo simulator of the Astrorivelatore Gamma ad Immagini LEggero (AGILE)/Gamma-Ray Imaging Detector (GRID) space telescope, AGILESim, is built using the customizable Bologna Geant4 Multi-Mission Simulator (BoGEMMS) architecture and the latest Geant4 library to reproduce the instrument performance of the AGILE/GRID instrument. The Monte Carlo simulation output is digitized in the BoGEMMS postprocessing pipeline, according to the instrument electronic read-out logic, then converted into the onboard data handling format, and finally analyzed by the standard mission on-ground reconstruction pipeline, including the Kalman filter, as a real observation in space. In this paper we focus on the scientific validation of AGILESim, performed by reproducing (i) the conversion efficiency of the tracker planes, (ii) the tracker charge readout distribution measured by the on-ground assembly, integration, and verification activity, and (iii) the point-spread function of in-flight observations of the Vela pulsar in the 100 MeV - 1 GeV energy range. We measure an in-flight angular resolution (FWHM) for Vela-like point sources of $2.0^{+0.2}_{-0.3}$ and $0.8^{+0.1}_{-0.1}$ degrees in the 100 - 300 and 300 - 1000 MeV energy bands, respectively. The successful cross-comparison of the simulation results with the AGILE on-ground and in-space performance validates the BoGEMMS framework for its application to future gamma-ray trackers (e.g. e-ASTROGAM and AMEGO).
The NASA/ASI Imaging X-ray Polarimetry Explorer, which will be launched in 2021, will be the first instrument to perform spatially resolved X-ray polarimetry on several astronomical sources in the 2-8 keV energy band. These measurements are made possible owing to the use of a gas pixel detector (GPD) at the focus of three X-ray telescopes. The GPD allows simultaneous measurements of the interaction point, energy, arrival time, and polarization angle of detected X-ray photons. The increase in sensitivity, achieved 40 years ago, for imaging and spectroscopy with the Einstein satellite will thus be extended to X-ray polarimetry for the first time. The characteristics of gas multiplication detectors are subject to changes over time. Because the GPD is a novel instrument, it is particularly important to verify its performance and stability during its mission lifetime. For this purpose, the spacecraft hosts a filter and calibration set (FCS), which includes both polarized and unpolarized calibration sources for performing in-flight calibration of the instruments. In this study, we present the design of the flight models of the FCS and the first measurements obtained using silicon drift detectors and CCD cameras, as well as those obtained in thermal vacuum with the flight units of the GPD. We show that the calibration sources successfully assess and verify the functionality of the GPD and validate its scientific results in orbit; this improves our knowledge of the behavior of these detectors in X-ray polarimetry.
A crucial aspect of 3D Monte Carlo radiative transfer is the choice of the spatial grid used to partition the dusty medium. We critically investigate the use of octree grids in Monte Carlo dust radiative transfer, with two different octree construction algorithms (regular and barycentric subdivision) and three different octree traversal algorithms (top-down, neighbour list, and the bookkeeping method). In general, regular octree grids need higher levels of subdivision compared to the barycentric grids for a fixed maximum cell mass threshold criterion. The total number of grid cells, however, depends on the geometry of the model. Surprisingly, regular octree grid simulations turn out to be 10 to 20% more efficient in run time than the barycentric grid simulations, even for those cases where the latter contain fewer grid cells than the former. Furthermore, we find that storing neighbour lists for each cell in an octree, ordered according to decreasing overlap area, is worth the additional memory and implementation overhead: using neighbour lists can cut down the grid traversal by 20% compared to the traditional top-down method. In conclusion, the combination of a regular node subdivision and the neighbour list method results in the most efficient octree structure for Monte Carlo radiative transfer simulations.
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