Very fast stochastic gravitational wave background map making using folded data

TL;DR

This paper introduces a highly efficient algorithm and software package that significantly accelerates the process of creating sky maps of the stochastic gravitational-wave background, enabling rapid analysis on standard computers.

Contribution

The authors developed a new algorithm and open-source software, PyStoch, that makes SGWB sky map making hundreds to thousands of times faster using folded data and matrix operations.

Findings

Analysis speed increased by a factor of a few thousand.

All-sky maps can be generated in minutes on a laptop.

The software produces frequency-binned skymaps as intermediate products.

Abstract

A stochastic gravitational-wave background (SGWB) is expected from the superposition of a wide variety of independent and unresolved astrophysical and cosmological sources from different stages in the evolution of the Universe. Radiometric techniques are used to make sky maps of anisotropies in the SGWB by cross-correlating data from pairs of detectors. The conventional searches can be made hundreds of times faster through the folding mechanism introduced recently. Here we present a newly developed algorithm to perform the SGWB searches in a highly efficient way. Taking advantage of the compactness of the folded data we replaced the loops in the pipeline with matrix multiplications. We also incorporated well-known HEALPix pixelization tools for further standardization and optimization. Our Python-based implementation of the algorithm is available as an open source package ${\tt PyStoch}$. Folding and ${\tt PyStoch}$ together has made the radiometer analysis $\textit{a few thousand times}$ faster; it is now possible to make all-sky maps of a stochastic background in just a few minutes on an ordinary laptop. Moreover, ${\tt PyStoch}$ generates a skymap at every frequency bin as an intermediate data product. These techniques have turned SGWB searches very convenient and will make computationally challenging analyses like blind all-sky narrowband search feasible.