Related papers: Interpretable Faraday Complexity Classification
Generalised Faraday rotation can induce frequency-dependent conversion between the linear and circular polarisation spectra of compact radio sources such as pulsars, fast radio bursts and active galactic nuclei. I devise a simple…
Faraday tomography (or rotation measure synthesis) is a procedure to convert linear polarization spectra into the Faraday dispersion function, which provides us with unique information of magneto-ionic media along the line of sight.…
Being able to interpret, or explain, the predictions made by a machine learning model is of fundamental importance. This is especially true when there is interest in deploying data-driven models to make high-stakes decisions, e.g. in…
Decision-making in complex systems often relies on machine learning models, yet highly accurate models such as XGBoost and neural networks can obscure the reasoning behind their predictions. In operations research applications,…
Faraday rotation measure at radio wavelengths is commonly used to diagnose large-scale magnetic fields. It is argued that the length-scales on which magnetic fields vary in large-scale diffuse astrophysical media can be inferred from…
The magnetic field of the solar wind near the Sun is very difficult to measure directly. Measurements of Faraday rotation of linearly polarized radio sources occulted by the solar wind provide a unique opportunity to estimate this magnetic…
We introduce a new technique for imaging the polarized radio sky using interferometric data. The new approach, which we call Faraday synthesis, combines aperture and rotation measure synthesis imaging and deconvolution into a single…
SHAP explanations are a popular feature-attribution mechanism for explainable AI. They use game-theoretic notions to measure the influence of individual features on the prediction of a machine learning model. Despite a lot of recent…
The overarching goal of Explainable AI is to develop systems that not only exhibit intelligent behaviours, but also are able to explain their rationale and reveal insights. In explainable machine learning, methods that produce a high level…
There is evidence that magnetized material along the line of sight to distant quasars is detectable in the polarization properties of the background sources. The polarization properties appear to be correlated with the presence of…
We introduce the construction of polarized intensity cubes $P$(RA, Dec, $\Phi$) and their visualization as movies, as a powerful technique for interpreting Faraday structure. $P$ is constructed from maps of peak polarized intensity P(RA,…
We define a notion of complexity, which quantifies the nonlinearity of the computation of a neural network, as well as a complementary measure of the effective dimension of feature representations. We investigate these observables both for…
Polarization calibration of interferometric observations is a costly procedure and, in some cases (e.g., a limited coverage of parallactic angle for the calibrator), it may not be possible to be performed. To avoid this worst-case scenario…
We investigate whether the method of wavelet-based Faraday rotation measure (RM) Synthesis can help us to identify structures of regular and turbulent magnetic fields in extended magnetized objects, such as galaxies and galaxy clusters.…
Feature attributions based on the Shapley value are popular for explaining machine learning models; however, their estimation is complex from both a theoretical and computational standpoint. We disentangle this complexity into two factors:…
The new generation of broad-band radio continuum surveys will provide large data sets with polarization information. New algorithms need to be developed to extract reliable catalogs of linearly polarized sources that can be used to…
The detection of filaments in the cosmic web will be crucial to distinguish between the possible magnetogenesis scenarios and future large polarization surveys will be able to shed light on their magnetization level. In this work, we use…
Observations of molecular lines are a key tool to determine the main physical properties of prestellar cores. However, not all the information is retained in the observational process or easily interpretable, especially when a larger number…
The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously unknown classes of objects. To maximise the scientific value…
(abridged) Observations of Faraday rotation for extragalactic sources probe magnetic fields both inside and outside the Milky Way. Building on our earlier estimate of the Galactic contribution, we set out to estimate the extragalactic…