matvis: A matrix-based visibility simulator for fast forward modelling of many-element 21 cm arrays

TL;DR

This paper introduces 'matvis', a fast, matrix-based simulation tool for large-scale radio interferometric arrays, enabling efficient modeling of 21 cm cosmology observations with high fidelity.

Contribution

The paper presents a novel, computationally efficient matrix-based method for simulating radio interferometric data, validated against high-precision simulations.

Findings

Achieves significant speedup over traditional methods

Maintains high accuracy in visibility simulations

Scales efficiently with array size and frequency channels

Abstract

Detection of the faint 21 cm line emission from the Cosmic Dawn and Epoch of Reionisation will require not only exquisite control over instrumental calibration and systematics to achieve the necessary dynamic range of observations but also validation of analysis techniques to demonstrate their statistical properties and signal loss characteristics. A key ingredient in achieving this is the ability to perform high-fidelity simulations of the kinds of data that are produced by the large, many-element, radio interferometric arrays that have been purpose-built for these studies. The large scale of these arrays presents a computational challenge, as one must simulate a detailed sky and instrumental model across many hundreds of frequency channels, thousands of time samples, and tens of thousands of baselines for arrays with hundreds of antennas. In this paper, we present a fast matrix-based method for simulating radio interferometric measurements (visibilities) at the necessary scale. We achieve this through judicious use of primary beam interpolation, fast approximations for coordinate transforms, and a vectorised outer product to expand per-antenna quantities to per-baseline visibilities, coupled with standard parallelisation techniques. We validate the results of this method, implemented in the publicly-available matvis code, against a high-precision reference simulator, and explore its computational scaling on a variety of problems.