Interpolation techniques for reconstructing Galactic Faraday rotation

TL;DR

This paper evaluates various interpolation methods for reconstructing Galactic Faraday rotation maps from RM data, assessing their accuracy, computational cost, and suitability for large sky surveys like POSSUM.

Contribution

It compares multiple interpolation kernels using simulated Galactic RM data to identify the most accurate and efficient techniques for upcoming large-scale surveys.

Findings

BRMS and NNI outperform other methods in accuracy.

IDW is the most computationally expensive technique.

TPS and IM are the least computationally demanding.

Abstract

The line-of-sight structure of the Galactic magnetic field (GMF) can be studied using Faraday rotation measure (RM) grids. We analyze how the choice of interpolation kernel can affect the accuracy and reliability of reconstructed RM maps. We test the following kernels: inverse distance weighting (IDW), natural neighbour interpolation (NNI), inverse multiquadric interpolation (IM), thin-plate spline interpolation (TPS), and a Bayesian rotation measure sky (BRMS); all techniques were tested on two simulated Galactic foreground RMs (one assuming the GMF has patchy structures and the other assuming it has filamentary structures) using magnetohydrodynamic simulations. Both foregrounds were sampled to form RM grids with densities of $\sim$40 sources deg$^{-2}$ and area $\sim$144 deg$^2$. The techniques were tested on data sets with different noise levels and Gaussian random extragalactic RM contributions. The data set that most closely emulates expected data from current surveys, such as the POlarization Sky Survey of the Universe's Magnetism (POSSUM), had extragalactic contributions and a noise standard deviation of $\sim 1.5$ rad m$^{-2}$. For this data set, the accuracy of the techniques for the patchy structures from best to worst was: BRMS, NNI, TPS, IDW and IM; while in the filamentary simulate foreground it was: BRMS, NNI, TPS, and IDW. IDW is the most computationally expensive technique, while TPS and IM are the least expensive. BRMS and NNI have the same, intermediate computational cost. This analysis lays the groundwork for Galactic RM studies with large radio polarization sky surveys, such as POSSUM.