Richard D. P. Grumitt

The 21 cm line from neutral hydrogen captures rich cosmological information. However, the 21 cm signals are highly contaminated by foreground emission, making accurate component separation vital for cosmological analyses. Gaussian processes (GPs) have been utilized for component separation in 21 cm data analyses, exploiting the distinct spectral behavior of the cosmological and foreground signals, which are modeled through the GP covariance kernel. Previous approaches have employed a global GP kernel along all lines of sight (LoS). In this work, we study Bayesian approaches that allow for spatial variations in foreground kernel parameters, testing them against simulated H i intensity mapping observations, which measures the total H i intensity in large voxels. We consider a no-pooling (NP) model, treating each LoS independently by fitting for separate covariance kernels, and a hierarchical Gaussian process (HGP) model, allowing for variation in kernel parameters between different LoS, regularized through a global hyperprior. We find that including spatial variations in the GP kernel parameters results in a significant improvement in cosmological signal recovery, achieving up to a 30% reduction in the standard deviation of the residual distribution. Allowing for spatial variations also improves the recovery of the H i power spectra and wavelet scattering transform coefficients. While the NP model achieves superior recovery as measured by the residual distribution, it is computationally demanding, faces convergence challenges, and is prone to overfitting. The HGP model strikes a balance between accuracy and robustness. Further improvements to the HGP model will require more physically-motivated modeling of foreground spatial variations. Our code can be found in the following repository: https://github.com/dkn16/H21F.

We introduce synax (https://github.com/dkn16/Synax), a novel library for automatically differentiable simulation of Galactic synchrotron emission. Built on the JAX framework, synax leverages JAX’s capabilities, including batch acceleration, just-in-time compilation, and hardware-specific optimizations (CPU, GPU, TPU). Crucially, synax uses JAX’s automatic differentiation (AD) mechanism, enabling precise computation of analytical derivatives with respect to any model parameters. This facilitates powerful inference algorithms, such as Hamiltonian Monte Carlo (HMC) and gradient-based optimization, which enables inference over models that would otherwise be computationally prohibitive. In its initial release, synax supports synchrotron intensity and polarization calculations down to GHz frequencies, alongside several models of the Galactic magnetic field (GMF), cosmic-ray spectra, and thermal electron density fields. When running synax on the CPU we obtain identical performance to hammurabi, a state-of-the-art synchrotron simulation package, while on the GPU synax brings a 20-fold enhancement in efficiency. We further demonstrate the potential of AD in enabling full posterior inference using gradient-based inference algorithms. Using synax with HMC to perform inference over a four-parameter test model, we attain a twofold improvement compared to standard random walk Metropolis–Hastings (RWMH). When applied to a more complex 16-parameter model, HMC is still able to obtain accurate posterior expectations, while RWMH fails to converge. We also showcase the application of synax to optimizing the GMF based on the Haslam 408 MHz map, achieving residuals with a standard deviation below 1 K.

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. In this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

Bent radio active galactic nucleus (AGN) morphology depends on the density of the surrounding gas. However, bent sources are found inside and outside clusters, raising the question of how environment impacts bent AGN morphology. We analyze new LOw-Frequency Array the LOFAR Two-metre Sky Survey (LoTSS) Data Release II observations of 20 bent AGNs in clusters and 15 not in clusters from the high-z Clusters Occupied by Bent Radio AGN (COBRA) survey (0.35 < z < 2.35). We measure the impact of environment on size, lobe symmetry, and radio luminosity. We find that the most asymmetric radio lobes lie outside of clusters, and we uncover a tentative anticorrelation between the total projected physical area and cluster overdensity. Additionally, we, for the first time, present spectral index measurements of a large sample of high-z bent sources using LoTSS and Very Large Array Faint Images of the Radio Sky at Twenty-centimeters (VLA FIRST) observations. We find that the median spectral index for the cluster sample is −0.76 ± 0.01, while the median spectral index for the noncluster sample is −0.81 ± 0.02. Furthermore, 13 of 20 cluster bent AGNs have flat cores (α ≥ −0.6) compared to 4 of 15 of noncluster bent AGNs, indicating a key environmental signature. Beyond core spectral index, bent AGNs inside and outside clusters are remarkably similar. We conclude that the noncluster sample may be more representative of bent AGNs at large offsets from the cluster center (> 1.2 Mpc) or bent AGNs in weaker groups rather than the field.

The Andromeda galaxy (M 31) is our closest neighbouring spiral galaxy, making it an ideal target for studying the physics of the interstellar medium in a galaxy very similar to our own. Using new observations of M 31 at 4.76 GHz by the C-Band All-Sky Survey (C-BASS), and all available radio data at 1^○ resolution, we produce the integrated spectrum and put new constraints on the synchrotron spectral index and anomalous microwave emission (AME) from M 31. We use aperture photometry and spectral modelling to fit for the integrated spectrum of M 31, and subtract a comprehensive model of nearby background radio sources. The AME in M 31 is detected at 3σ significance with a peak near 30 GHz and flux density 0.27 ± 0.09Jy. The synchrotron spectral index of M 31 is flatter than our own Galaxy at α =−0.66 ± 0.03with no strong evidence of spectral curvature. The emissivity of AME, averaged over the total emission from M 31 is lower than typical AME sources in our Galaxy, implying that AME is not uniformly distributed throughout M 31 and instead is likely confined to sub-regions—this will need to be confirmed using future higher resolution observations around 20–30 GHz.

The C-Band All-Sky Survey (C-BASS) has observed the Galaxy at 4.76 GHz with an angular resolution of 0${_{.}^{\circ}}$73 full-width half-maximum, and detected Galactic synchrotron emission with high signal-to-noise ratio over the entire northern sky (δ > −15○). We present the results of a spatial correlation analysis of Galactic foregrounds at mid-to-high (b > 10○) Galactic latitudes using a preliminary version of the C-BASS intensity map. We jointly fit for synchrotron, dust, and free–free components between 20 and 1000 GHz and look for differences in the Galactic synchrotron spectrum, and the emissivity of anomalous microwave emission (AME) when using either the C-BASS map or the 408-MHz all-sky map to trace synchrotron emission. We find marginal evidence for a steepening (<Δβ> = −0.06 ± 0.02) of the Galactic synchrotron spectrum at high frequencies resulting in a mean spectral index of <β> = −3.10 ± 0.02 over 4.76–22.8 GHz. Further, we find that the synchrotron emission can be well modelled by a single power law up to a few tens of GHz. Due to this, we find that the AME emissivity is not sensitive to changing the synchrotron tracer from the 408-MHz map to the 4.76-GHz map. We interpret this as strong evidence for the origin of AME being spinning dust emission.