The BlueMUSE data reduction pipeline: lessons learned from MUSE and first design choices

TL;DR

This paper reviews lessons from the MUSE pipeline to inform the design of BlueMUSE's data reduction software, highlighting key differences, new features, and simulation strategies for this upcoming blue optical spectrograph.

Contribution

It introduces the initial design choices for BlueMUSE's data reduction pipeline, based on lessons learned from MUSE and tailored for the blue wavelength range.

Findings

Identified key differences between MUSE and BlueMUSE

Proposed improvements in data covariance handling and wavelength calibration

Outlined simulation approaches for BlueMUSE datacubes

Abstract

BlueMUSE is an integral field spectrograph in an early development stage for the ESO VLT. For our design of the data reduction software for this instrument, we are first reviewing capabilities and issues of the pipeline of the existing MUSE instrument. MUSE has been in operation at the VLT since 2014 and led to discoveries published in more than 600 refereed scientific papers. While BlueMUSE and MUSE have many common properties we briefly point out a few key differences between both instruments. We outline a first version of the flowchart for the science reduction, and discuss the necessary changes due to the blue wavelength range covered by BlueMUSE. We also detail specific new features, for example, how the pipeline and subsequent analysis will benefit from improved handling of the data covariance, and a more integrated approach to the line-spread function, as well as improvements regarding the wavelength calibration which is of extra importance in the blue optical range. We finally discuss how simulations of BlueMUSE datacubes are being implemented and how they will be used to prepare the science of the instrument.