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Register a new userExpected performance of the GAW Cherenkov Telescopes Array. Simulation and Analysis
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Added by
Maria Concetta Maccarone
Publication date
2007
fields
Physics
and research's language is
English
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GAW is a path-finder experiment to test the feasibility of a new generation of Imaging Atmospheric Cherenkov telescopes that join high flux sensitivity with large field of view capability using Fresnel lens, stereoscopic observational approach, and single photon counting mode. GAW is an array of three telescopes that will be erected at the Calar Alto Observatory site (Spain, 2150 m a.s.l.). To evaluate the performance of GAW, a consistent data--set has been simulated, including a Crab-like source observation, and a proper image analysis code has been developed, as described in this contribution. The expected performance of GAW are also reported, mainly for what concerns effective area, angular resolution, Cherenkov flux as function of the core distance, ability in the gamma/proton separation, and sensitivity. The first telescope realization, foreseen within the end of this year, will allow to verify if the parameters used in the analysis are in agreement with the real performance of the GAW apparatus.
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The Cherenkov Telescope Array (CTA) will be the next generation very-high-energy gamma-ray observatory. CTA is expected to provide substantial improvement in accuracy and sensitivity with respect to existing instruments thanks to a tenfold increase in the number of telescopes and their state-of-the-art design. Detailed Monte Carlo simulations are used to further optimise the number of telescopes and the array layout, and to estimate the observatory performance using updated models of the selected telescope designs. These studies are presented in this contribution for the two CTA stations located on the island of La Palma (Spain) and near Paranal (Chile) and for different operation and observation conditions.
VERITAS is a system of four imaging Cherenkov telescopes located at the Fred Lawrence Whipple Observatory in southern Arizona. We present here results of detailed Monte Carlo simulations of the array response to extensive air showers. Cherenkov image and shower parameter distributions are calculated and show good agreement with distributions obtained from observations of background cosmic rays and high-energy gamma-rays. Cosmic-ray and gamma-ray rates are accurately predicted by the simulations. The energy threshold of the 3-telescope system is about 150 GeV after gamma-hadron separation cuts; the detection rate after gamma-selection cuts for the Crab Nebula is 7.5 gammas/min. The three-telescope system is able to detect a source with a flux equivalent to 10% of the Crab Nebula flux in 1.2 h of observations (5 sigma detection).
This paper is concerned with the performance optimisation of an stereoscopic array of imaging atmospheric Cherenkov telescopes (IACTs) as a function of their positioning on the ground. In this first work we are concerned primarily with the study of the optimisation method and its test on toy arrays of few (3-6) telescopes. The ideas presented here were developed to investigate alternative ways of studying IACT array geometries. The proposal is an attempt to cover more exhaustively and systematically the parameter space involved in the design of a stereoscopic IACT array, aiming to develop a support tool for directing the computationally expensive Monte Carlo simulations commonly used in the field. The methodology presented here involves a modelling step (in our case a simplified, heuristic IACT array model) and the implementation of an evolutionary algorithm for the geometric optimisation. In this initial work, the heuristic model and the optimisation algorithm are presented, but no detailed Monte Carlo validation is presented yet. The techniques used here may have potential applications in other optimization problems in the field of Gamma Ray Astronomy.
The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. Classically, data analysis in the field maximizes sensitivity by applying quality cuts on the data acquired. These cuts, optimized using Monte Carlo simulations, select higher quality events from the initial dataset. Subsequent steps of the analysis typically use the surviving events to calculate one set of instrument response functions (IRFs). An alternative approach is the use of event types, as implemented in experiments such as the Fermi-LAT. In this approach, events are divided into sub-samples based on their reconstruction quality, and a set of IRFs is calculated for each sub-sample. The sub-samples are then combined in a joint analysis, treating them as independent observations. This leads to an improvement in performance parameters such as sensitivity, angular and energy resolution. Data loss is reduced since lower quality events are included in the analysis as well, rather than discarded. In this study, machine learning methods will be used to classify events according to their expected angular reconstruction quality. We will report the impact on CTA high-level performance when applying such an event-type classification, compared to the classical procedure.
The MICROSCOPE mission aimed to test the Weak Equivalence Principle (WEP) to a precision of $10^{-15}$. The WEP states that two bodies fall at the same rate on a gravitational field independently of their mass or composition. In MICROSCOPE, two masses of different compositions (titanium and platinum alloys) are placed on a quasi-circular trajectory around the Earth. They are the test-masses of a double accelerometer. The measurement of their accelerations is used to extract a potential WEP violation that would occur at a frequency defined by the motion and attitude of the satellite around the Earth. This paper details the major drivers of the mission leading to the specification of the major subsystems (satellite, ground segment, instrument, orbit...). Building upon the measurement equation, we derive the objective of the test in statistical and systematic error allocation and provide the missions expected error budget.
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