J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit

TL;DR

J-UBIK is a flexible, modular software toolkit built on JAX that streamlines Bayesian imaging for multi-instrument astronomical data, enabling high-fidelity sky image reconstruction.

Contribution

It introduces a versatile Bayesian imaging toolkit with adaptable models and inference schemes, specifically tailored for multi-instrument astronomical observations.

Findings

Supports multiple instruments including Chandra, eROSITA, and JWST.

Provides adaptable prior and likelihood models for different sky signals.

Enables efficient high-fidelity image reconstruction through Bayesian pipelines.

Abstract

Many advances in astronomy and astrophysics originate from accurate images of the sky emission across multiple wavelengths. This often requires reconstructing spatially and spectrally correlated signals detected from multiple instruments. To facilitate the high-fidelity imaging of these signals, we introduce the universal Bayesian imaging kit (UBIK). Specifically, we present J-UBIK, a flexible and modular implementation leveraging the JAX-accelerated NIFTy.re software as its backend. J-UBIK streamlines the implementation of the key Bayesian inference components, providing for all the necessary steps of Bayesian imaging pipelines. First, it provides adaptable prior models for different sky realizations. Second, it includes likelihood models tailored to specific instruments. So far, the package includes three instruments: Chandra and eROSITA for X-ray observations, and the James Webb Space Telescope (JWST) for the near- and mid-infrared. The aim is to expand this set in the future. Third, these models can be integrated with various inference and optimization schemes, such as maximum a posteriori estimation and variational inference. Explicit demos show how to integrate the individual modules into a full analysis pipeline. Overall, J-UBIK enables efficient generation of high-fidelity images via Bayesian pipelines that can be tailored to specific research objectives.