Monte Carlo studies for the optimisation of the Cherenkov Telescope Array layout

Abstract

The Cherenkov Telescope Array (CTA) is the major next-generation observatory for ground-based very-high-energy gamma-ray astronomy. It will improve the sensitivity of current ground-based instruments by a factor of five to twenty, depending on the energy, greatly improving both their angular and energy resolutions over four decades in energy (from 20 GeV to 300 TeV). This achievement will be possible by using tens of imaging Cherenkov telescopes of three successive sizes. They will be arranged into two arrays, one per hemisphere, located on the La Palma island (Spain) and in Paranal (Chile). We present here the optimised and final telescope arrays for both CTA sites, as well as their foreseen performance, resulting from the analysis of three different large-scale Monte Carlo productions.

48 pages, 16 figures, accepted for publication in Astroparticle Physics

References in corpus (2)

• The major upgrade of the MAGIC telescopes, Part II: A performance study using observations of the Crab Nebula
• Monte Carlo Studies of medium-size telescope designs for the Cherenkov Telescope Array

Cited by in corpus (14)

• Demonstration of stellar intensity interferometry with the four VERITAS telescopes
• ASTRI Mini-Array Core Science at the Observatorio del Teide
• Axion-like Particles Implications for High-Energy Astrophysics
• Fundamental physics with blazar spectra: a critical appraisal
• Design and performance of the prototype Schwarzschild-Couder Telescope camera
• Constraining Models of the Pulsar Wind Nebula in SNR G0.9+0.1 via Simulation of its Detection Properties using the Cherenkov Telescope Array
• Probing the evolution of the EBL photon density out to $z\sim 1$ via $\gamma$-ray propagation measurements with Fermi
• Studying deep convolutional neural networks with hexagonal lattices for imaging atmospheric Cherenkov telescope event reconstruction
• Te-REX: a sample of extragalactic TeV-emitting candidates
• An analysis method for data taken by Imaging Air Cherenkov Telescopes at very high energies under the presence of clouds
• Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars
• Testing source confusion and identification capability in Cherenkov Telescope Array data
• CTLearn: Deep Learning for Gamma-ray Astronomy
• Monte Carlo Studies of Combined MAGIC and LST1 Observations