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February 28, 2026Monthly Notices of the Royal Astronomical Society0 citationsOpen Access

A Robust Analysis of QU-fitting Behavior for 800-1088 MHz and 1296-1440 MHz

LOLindsey OberhelmanCECameron L. Van EckNMN M McClure-Griffiths

Key Points

  • To investigate the effectiveness and limitations of QU-fitting for interpreting spectro-polarimetric data from the ASKAP POSSUM survey.
  • Simulated polarization sources including Faraday simple, Burn slab, and turbulence models.
  • Assessed fit accuracies and observational degeneracies within specified frequency ranges.
  • Compared performance of Bayes factor against traditional metrics like BIC and AIC for model selection.
  • Evaluated QU-fitting's parameter recovery accuracy and uncertainty assessment in Faraday depth space.
  • Bayes factor provides superior model selection compared to BIC, AIC, and χ2.
  • Identified regions where model parameter determination is ambiguous or unreliable.
  • Established empirical relationships for distinguishing model fitting capabilities in observational data.

Abstract

Abstract QU-fitting is a powerful tool for interpreting spectro-polarimetric radio continuum observations by linking them to physical models, enabling estimates of the magnetic fields in, for example, the Milky Way, galaxy clusters, and radio jets. We present a comprehensive investigation into the effectiveness and limitations of QU-fitting within the ASKAP POSSUM survey frequency ranges (800–1088 MHz and 1296–1440 MHz) with projections to other spectro-polarimetric radio observations. We simulate different physical polarization sources: Faraday simple, Burn slab, internal turbulence, external turbulence, and two-component models in the POSSUM frequencies, and assess their observational degeneracies and fit accuracies. Our results highlight the model-dependent nature of reliable fitting and identify specific regions of parameter space where model selection, and therefore characterization of the physical medium, becomes ambiguous. For QU-fitting we find the Bayes factor, computed using the marginal likelihood, outperforms more traditionally used goodness-of-fit metrics such as Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC), and χ2 for model selection. We provide empirical relationships to delineate the boundaries where model distinguishability is impossible. Finally, we evaluate how accurately QU-fitting recovers model parameters and their associated uncertainties, thereby assessing its ability to correctly characterize the Faraday-rotating medium in both point and extended sources in Faraday depth space.

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Cite This Study

Oberhelman et al. (2026) studied this question.

synapsesocial.com/papers/69a286490a974eb0d3c01275https://doi.org/10.1093/mnras/stag394
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