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Low-noise, position-sensitive Silicon Drift Detectors (SDDs) are particularly useful for experiments in which a good energy resolution combined with a large sensitive area is required, as in the case of X-ray astronomy space missions and medical appl ications. This paper presents the experimental characterization of VEGA, a custom Application Specific Integrated Circuit (ASIC) used as the front-end electronics for XDXL-2, a large-area (30.5 cm^2) SDD prototype. The ASICs were integrated on a specifically developed PCB hosting also the detector. Results on the ASIC noise performances, both stand-alone and bonded to the large area SDD, are presented and discussed.
The Large Observatory For X-ray Timing (LOFT), currently in an assessment phase in the framework the ESA M3 Cosmic Vision programme, is an innovative medium-class mission specifically designed to answer fundamental questions about the behaviour of ma tter, in the very strong gravitational and magnetic fields around compact objects and in supranuclear density conditions. Having an effective area of ~10 m^2 at 8 keV, LOFT will be able to measure with high sensitivity very fast variability in the X-ray fluxes and spectra. A good knowledge of the in-orbit background environment is essential to assess the scientific performance of the mission and optimize the design of its main instrument, the Large Area Detector (LAD). In this paper the results of an extensive Geant-4 simulation of the instrument will be discussed, showing the main contributions to the background and the design solutions for its reduction and control. Our results show that the current LOFT/LAD design is expected to meet its scientific requirement of a background rate equivalent to 10 mCrab in 2-30 keV, achieving about 5 mCrab in the most important 2-10 keV energy band. Moreover, simulations show an anticipated modulation of the background rate as small as 10% over the orbital timescale. The intrinsic photonic origin of the largest background component also allows for an efficient modelling, supported by an in-flight active monitoring, allowing to predict systematic residuals significantly better than the requirement of 1%, and actually meeting the 0.25% science goal.
108 - R. Campana , T. Mineo , A. De Rosa 2008
PSR B0540-69 is a young pulsar in the Large Magellanic Cloud that has similar properties with respect to the Crab Pulsar, and is embedded in a Pulsar Wind Nebula. We have analyzed the complete archival RXTE dataset of observations of this source, tog ether with new Swift-XRT and INTEGRAL-IBIS data. Accurate lightcurves are produced in various energy bands between 2 and 60 keV, showing no significant energy variations of the pulse shape. The spectral analysis shows that the pulsed spectrum is curved, and is best fitted up to 100 keV by a log-parabolic model: this strengthens the similarities with the Crab pulsar, and is discussed in the light of a phenomenologic multicomponent model. The total emission from this source is studied, the relative contributions of the pulsar and the PWN emission are derived, and discussed in the context of other INTEGRAL detected pulsar/PWN systems.
We developed a source detection algorithm based on the Minimal Spanning Tree (MST), that is a graph-theoretical method useful for finding clusters in a given set of points. This algorithm is applied to gamma-ray bidimensional images where the points correspond to the arrival direction of photons, and the possible sources are associated with the regions where they clusterize. Some filters to select these clusters and to reduce the spurious detections are introduced. An empirical study of the statistical properties of MST on random fields is carried in order to derive some criteria to estimate the best filter values. We introduce also two parameters useful to verify the goodness of candidate sources. To show how the MST algorithm works in the practice, we present an application to an EGRET observation of the Virgo field, at high galactic latitude and with a low and rather uniform background, in which several sources are detected.
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