J-UBIK:JAX 加速通用贝叶斯成像工具包

Vincent Eberle, Matteo Guardiani, Margret Westerkamp, Philipp Frank, Julian Rüstig, Julia Stadler, Torsten A. Enßlin
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引用次数: 0

摘要

天文学和天体物理学的许多进步都源于多波长天空发射的精确图像。这通常需要重建从多个仪器探测到的空间和光谱相关信号。为了便于对这些信号进行高保真成像,我们引入了通用贝叶斯成像工具包(UBIK)。具体来说,我们介绍了 J-UBIK,它是一种灵活的模块化实现,利用 JAX 加速的 NIFTy.re 软件作为其后端。J-UBIK 简化了关键贝叶斯推理组件的实现,提供了贝叶斯成像管道的所有必要步骤。首先,它为不同的天空实景提供了可调整的先验模型。其次,它还包括为特定仪器量身定制的似然模型。到目前为止,该软件包包括三种仪器:钱德拉和用于 X 射线观测的 eROSITA,以及用于近红外和中红外观测的詹姆斯-韦伯空间望远镜(JWST)。我们的目标是在未来扩大这套模型。第三,这些模型可以与各种推理和优化方案相结合,如最大后验估计和变量推理。明确的演示展示了如何将各个模块集成到完整的分析管道中。总之,J-UBIK 可以通过贝叶斯管道高效生成高保真图像,并可根据具体研究目标进行定制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
J-UBIK: The JAX-accelerated Universal Bayesian Imaging Kit
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.
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