J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917777057513472 |
|---|---|
| author | Eberle, Vincent Guardiani, Matteo Westerkamp, Margret Frank, Philipp Rüstig, Julian Stadler, Julia Enßlin, Torsten A. |
| author_facet | Eberle, Vincent Guardiani, Matteo Westerkamp, Margret Frank, Philipp Rüstig, Julian Stadler, Julia Enßlin, Torsten A. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_10381 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit Eberle, Vincent Guardiani, Matteo Westerkamp, Margret Frank, Philipp Rüstig, Julian Stadler, Julia Enßlin, Torsten A. Instrumentation and Methods for Astrophysics Computational Physics Data Analysis, Statistics and Probability Instrumentation and Detectors 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. |
| title | J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit |
| topic | Instrumentation and Methods for Astrophysics Computational Physics Data Analysis, Statistics and Probability Instrumentation and Detectors |
| url | https://arxiv.org/abs/2409.10381 |