Automatic spectroscopic data reduction using BANZAI

Curtis McCully; Matthew Daily; G. Mirek Brandt; Marshall C. Johnson; Mark Bowman; Daniel-Rolf Harbeck

doi:10.1117/12.2630667

29 August 2022 Automatic spectroscopic data reduction using BANZAI

Curtis McCully, Matthew Daily, G. Mirek Brandt, Marshall C. Johnson, Mark Bowman, Daniel-Rolf Harbeck

Proceedings Volume 12189, Software and Cyberinfrastructure for Astronomy VII; 1218914 (2022) https://doi.org/10.1117/12.2630667
Event: SPIE Astronomical Telescopes + Instrumentation, 2022, Montréal, Québec, Canada

Abstract

Time domain astronomy has both increased the data volume and the urgency of data reduction in recent years. Spectra provide key insights into astrophysical phenomena but require complex reductions. Las Cumbres Observatory has six spectrographs - two low-dispersion FLOYDS instruments and four NRES high-resolution echelle spectrographs. We present an extension of the data reduction framework, BANZAI, to process spectra automatically, with no human interaction. We also present interactive tools we have developed for human vetting and improvement of the spectroscopic reduction. Tools like those presented here are essential to maximize the scientific yield from current and future time domain astronomy.

Conference Presentation

Citation Download Citation

Curtis McCully, Matthew Daily, G. Mirek Brandt, Marshall C. Johnson, Mark Bowman, and Daniel-Rolf Harbeck "Automatic spectroscopic data reduction using BANZAI", Proc. SPIE 12189, Software and Cyberinfrastructure for Astronomy VII, 1218914 (29 August 2022); https://doi.org/10.1117/12.2630667

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