Over the past two decades, both X-ray and gamma-ray astronomy have experienced great progress. However, the region of the electromagnetic spectrum around ∼1 MeV is not so thoroughly explored. Future medium-sized gamma-ray telescopes will fill this gap in observations. As the timescale for the development and launch of a medium-class mission is ∼10 years, with substantial costs, we propose a different approach for the immediate future. In this paper, we evaluate the viability of a much smaller and cheaper detector: a nano-satellite Compton telescope, based on the CubeSat architecture. The scientific performance of this telescope would be well below that of the instrument expected for the future larger missions; however, via simulations, we estimate that such a compact telescope will achieve a performance similar to that of COMPTEL.
Abstract. This paper presents the RBF4AERO benchmark technology platform, developed in the framework of the EU-funded RBF4AERO project. The platform enables the so-called Benchmark Management System (BMS) used for benchmark submission and results reporting. The BMS is deployed using three modules, namely the Graphical User Interface (GUI), the Workflow Manager (WM) and the Benchmarking Database System (BDS) which cooperate during the whole optimization benchmark life-cycle. The GUI is the only component which interacts with the end-user. It enables the optimization benchmark submission, along with the progress, results and computational platform resources monitoring. The configuration of the Optimization (OT) and the Morpher Tool (MT) is a pre-requisite for the optimization benchmark submission. In an optimization scenario the WM, which is practically the controller of the system, queries the OT in order to get a table of samples and gives back the results of the simulator (for instance a CFD tool). The evaluated individuals serve as training patterns of a Response Surface Model (RSM) which is, then, used for an Evolutionary Algorithms based optimization. The resulting 'optimal' solution(s) are delivered back to the WM for re-evaluation on the CFD tool. For each evaluation on the CFD tool, when a new geometrical shape is required, the computational grid is morphed using the MT based on radial basis functions.
4156Massimo Bernaschi et al.
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