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

Peter M. Weilbacher; Sven Martens; Martin Wendt; Martin M. Roth; Stefan Dreizler; Andreas Kelz; Roland Bacon; Johan Richard

doi:10.1117/12.2630024

29 August 2022 The BlueMUSE data reduction pipeline: lessons learned from MUSE and first design choices

Peter M. Weilbacher, Sven Martens, Martin Wendt, Martin M. Roth, Stefan Dreizler, Andreas Kelz, Roland Bacon, Johan Richard

Author Affiliations +

Proceedings Volume 12189, Software and Cyberinfrastructure for Astronomy VII; 1218912 (2022) https://doi.org/10.1117/12.2630024
Event: SPIE Astronomical Telescopes + Instrumentation, 2022, Montréal, Québec, Canada

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.

Conference Presentation

Citation Download Citation

Peter M. Weilbacher, Sven Martens, Martin Wendt, Martin M. Roth, Stefan Dreizler, Andreas Kelz, Roland Bacon, and Johan Richard "The BlueMUSE data reduction pipeline: lessons learned from MUSE and first design choices", Proc. SPIE 12189, Software and Cyberinfrastructure for Astronomy VII, 1218912 (29 August 2022); https://doi.org/10.1117/12.2630024

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available