No abstract

In the context of the development of the Cherenkov Telescope Array, we have conceived and implemented a multi-objective genetic algorithm (GA) code for the optimisation of an array of Imaging Atmospheric Cherenkov Telescopes (IACTs). The algorithm takes as input a series of cost functions (metrics) each describing a different objetive of the optimisation (such as effective area, angular resolution, etc.), all of which are expressed in terms of the relative position of the telescopes in the plane. The output of the algorithm is a family of geometrical arrangements which correspond to the complete set of solutions to the array optimisation problem, and differ from each other according to the relative weight given to each of the (maybe conflicting) objetives of the optimisation. Since the algorithm works with parallel optimisation it admits as many cost functions as desired, and can incorporate constraints such as budget (cost cap) for the array and topological limitations of the terrain, like geographical accidents where telescopes cannot be installed. It also admits different types of telescopes (hybrid arrays) and the number of telescopes of each type can be treated as a parameter to be optimised -constrained, for example, by the cost of each type or the energy range of interest. The purpose of the algorithm, which converges fast to optimised solutions (if compared to the time for a complete Monte Carlo Simulation of a single configuration), is to provide a tool to investigate the full parameter space of possible geometries, and help in designing complex arrays. It does not substitute a detailed Monte Carlo study, but aims to guide it. In the examples of arrays shown here we have used as metrics simple heuristic expressions describing the fundamentals of the IAC technique, but these input functions can be made as detailed or complex as desired for a given experiment. It is important to stress that the individual characteristics of each telescope are taken as fixed, and only the telescope arrangement is being optimised. Preliminary results will be presented in this contribution for the first time.

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.

O objetivo deste trabalho é aplicar um teste que visa determinar se as direções de chegada dos raios cósmicos de energias mais altas (> 10 19 eV) observados pelo Observatório Pierre Auger seguem uma distribuição isotrópica. Sua principal vantagem é dispensar o uso de catálogos de objetos astrofísicos.Igualmente, procura-se uma correlação das direções de chegada com a região conhecida como Plano Supergaláctico. Dá-se ênfase na motivação, interpretação e na visão geral sobre anisotropia de raios cósmicos surgida nos últimos anos.O resultado obtido com os dados atuais neste trabalho é que de fato existe uma anisotropia nas direções de chegada, embora esta ainda seja difícil de caracterizar.

This paper is concerned with the performance optimization of an array of at most six imaging atmospheric Cherenkov telescopes as a function of their positions on the ground. Two types of telescopes were used, with ranges of detection equal to 300 m or 500 m. The ideas presented here were developed around an alternative way that employs a modelling step and the implementation of an evolutionary algorithm. We look for configurations that were not investigated by Monte Carlo simulations yet. We found solutions represented by geometric shapes with 3 to 6 telescopes. This is an initial work and the methods developed here have potential applications in other optimization issues on Gamma Ray Astronomy.