Automated SpectroPhotometric Image REDuction (ASPIRED

Marco C. Lam, Robert J. Smith, Iair Arcavi, Iain A. Steele, Josh Veitch-Michaelis, Lukasz Wyrzykowski

Research output: Contribution to journalArticlepeer-review

Abstract

We provide a suite of public open-source spectral data-reduction software to rapidly obtain scientific products from all forms of long-slit-like spectroscopic observations. Automated SpectroPhotometric REDuction (ASPIRED) is a Python-based spectral data-reduction toolkit. It is designed to be a general toolkit with high flexibility for users to refine and optimize their data-reduction routines for the individual characteristics of their instruments. The default configuration is suitable for low-resolution long-slit spectrometers and provides a quick-look quality output. However, for repeatable science-ready reduced spectral data, some moderate one-time effort is necessary to modify the configuration. Fine-tuning and additional (pre)processing may be required to extend the reduction to systems with more complex setups. It is important to emphasize that although only a few parameters need updating, ensuring their correctness and suitability for generalization to the instrument can take time due to factors such as instrument stability. We compare some example spectra reduced with ASPIRED to published data processed with iraf-based and STARLINK-based pipelines, and find no loss in the quality of the final product. The Python-based, iraf-free ASPIRED can significantly ease the effort of an astronomer in constructing their own data-reduction workflow, enabling simpler solutions to data-reduction automation. This availability of near-real-time, science-ready data will allow adaptive observing strategies, particularly important in, but not limited to, time-domain astronomy.

Original languageEnglish
Article number13
JournalAstronomical Journal
Volume166
Issue number1
DOIs
StatePublished - 1 Jul 2023

Funding

FundersFunder number
Israeli Council for Higher Education Alon Fellowship
National Science Foundation
Horizon 2020 Framework Programme730890, 852097
National Research Council
Science and Technology Facilities Council
European Research Council
Australian Research Council
United States-Israel Binational Science Foundation
Comisión Nacional de Investigación Científica y Tecnológica
Israel Science Foundation2752/19
Liverpool John Moores University
Narodowe Centrum Nauki2017/27/L/ST9/03221
Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires
Ministério da Ciência e Tecnologia
Instituto de Astrofísica de Canarias

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