Abstract
Abstract
The deployment of several large scale arrays is envisioned
to study astroparticles at ultra-high energies. In order to
circumvent the heavy computational costs of exploring and optimizing
their layouts, we have developed a pruning method. It consists in
i) running a set of microscopic simulations and interpolate them
over a dense, regularly spaced array of detection units, and
ii) pruning the unnecessary units out of the layout, in order to
obtain the shower footprint on a newly shaped layout. This method
offers flexibility to test various layout parameters, instrumental
constraints, and physical inputs, with a drastic reduction in the
required CPU time. The method can be universally applied to optimize
arrays of any size, and using any detection techniques.
For demonstration, we apply the pruning tool to radio antenna
layouts, which allows us to discuss the interplay between the energy
and inclination of air-showers on the size of the radio footprint
and the intensity of the signal on the ground. Some rule-of-thumb
conclusions that can be drawn for this specific case are: i) a
hexagonal geometry is more efficient than a triangular geometry,
ii) the detection efficiency of the array is stable to changes in
the spacing between radio antennas around 1000 m step size,
iii) for a given number of antennas, adding a granular infill on top
of a coarse hexagonal array is more efficient than instrumenting the
full array with a less dense spacing.