Toward the End-To-End Optimization of the SWGO Array Layout

TL;DR

This paper presents a novel end-to-end optimization pipeline using stochastic gradient descent to determine the optimal layout of water Cherenkov detectors for the SWGO gamma-ray observatory, improving design efficiency.

Contribution

It introduces a continuous model of atmospheric shower particles and an optimization pipeline that effectively finds the global maximum in high-dimensional detector layout space.

Findings

Pipeline successfully identifies promising detector configurations.

Demonstrates the ability to find global maxima in complex parameter spaces.

Discusses performance and limitations of the optimization method.

Abstract

In this document we consider the problem of finding the optimal layout for the array of water Cherenkov detectors proposed by the SWGO collaboration to study very-high-energy gamma rays in the southern hemisphere. We develop a continuous model of the secondary particles produced by atmospheric showers initiated by high-energy gamma rays and protons, and build an optimization pipeline capable of identifying the most promising configuration of the detector elements. The pipeline employs stochastic gradient descent to maximize a utility function aligned with the scientific goals of the experiment. We demonstrate how the software is capable of finding the global maximum in the high-dimensional parameter space, and discuss its performance and limitations.