# Study of the performance of an array of Cherenkov telescopes by means of multi-objective evolutionary optimisation

## TL;DR

This study explores the use of multi-objective evolutionary algorithms to optimize the placement of Cherenkov telescopes in an array, aiming to improve design efficiency and support Monte Carlo simulations in gamma-ray astronomy.

## Contribution

It introduces a novel optimization methodology combining heuristic modeling and evolutionary algorithms for Cherenkov telescope array design.

## Key findings

- Developed a simplified heuristic model for IACT array optimization
- Implemented an evolutionary algorithm to explore array configurations
- Demonstrated potential for systematic parameter space coverage

## Abstract

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.