The Universal Bayesian Imaging Kit

TL;DR

Problem: imaging across diverse instruments is ill-posed due to instrument effects and incomplete sky information. Approach: UBIK unifies Bayesian imaging within Information Field Theory using a probabilistic forward model with a latent Gaussian field $\xi$ mapped to sky signals $s=f(\xi)$ and a data likelihood $\mathcal{P}(d|s)$; the posterior $\mathcal{P}(s|d)$ is inferred via variational schemes MGVI and geoVI, enabling tractable, high-dimensional inference. Key contributions: a modular, open-source platform with instrument descriptions for Chandra, eROSITA, JWST, and ALMA, capable of multi-instrument imaging, joint calibration, and separation of diffuse, point-like, and extended emission; synthetic-data generation for validation and uncertainty quantification. Significance: this framework facilitates cross-calibration and robust, uncertainty-aware sky reconstructions across wavelengths, with broad applicability to complex astrophysical datasets.

Abstract

Bayesian imaging of astrophysical measurement data shares universal properties across the electromagnetic spectrum: it requires probabilistic descriptions of possible images and spectra, and instrument responses. To unify Bayesian imaging, we present the Universal Bayesian Imaging Kit (UBIK). Currently, UBIK images data from Chandra, eROSITA, JWST, and ALMA. UBIK is based on information field theory (IFT), the mathematical theory of field inference, and on NIFTy, a package for numerical IFT. UBIK provides sky models that are instrument independent and instrument interfaces that share common parts of their response representations. It is open source, can provide spatio-spectral image cubes, jointly analyses data from several instruments, and separates diffuse emission, point sources, and extended emission regions.

Figures (1)

• Figure 1: Graphical representation of a typical generative model used in astronomical imaging with UBIK.