Issue |
A&A
Volume 668, December 2022
|
|
---|---|---|
Article Number | A84 | |
Number of page(s) | 16 | |
Section | Planets and planetary systems | |
DOI | https://doi.org/10.1051/0004-6361/202244587 | |
Published online | 12 December 2022 |
Spectral cube extraction for the VLT/SPHERE IFS
Open-source pipeline with full forward modeling and improved sensitivity★
1
Max-Planck-Institut für Astronomie,
Königstuhl 17,
69117
Heidelberg, Germany
e-mail: samland@mpia.de
2
Department of Physics, University of California,
Santa Barbara, CA
93106, USA
3
Univ. Grenoble Alpes, CNRS, IPAG,
38000
Grenoble, France
4
Aix-Marseille Univ., CNRS, CNES, LAM,
Marseille, France
Received:
24
July
2022
Accepted:
16
September
2022
We present a new open-source data-reduction pipeline to reconstruct spectral data cubes from raw SPHERE integral-field spectrograph (IFS) data. The pipeline is written in Python and based on the pipeline that was developed for the CHARIS IFS. It introduces several improvements to SPHERE data analysis that ultimately produce significant improvements in postprocessing sensitivity. We first used new data to measure SPHERE lenslet point spread functions (PSFs) at the four laser calibration wavelengths. These lenslet PSFs enabled us to forward-model SPHERE data, to extract spectra using a least-squares fit, and to remove spectral crosstalk using the measured lenslet PSFs. Our approach also reduces the number of required interpolations, both spectral and spatial, and can preserve the original hexagonal lenslet geometry in the SPHERE IFS. In the case of least-squares extraction, no interpolation of the data is performed. We demonstrate this new pipeline on the directly imaged exoplanet 51 Eri b and on observations of the hot white dwarf companion to HD 2133. The extracted spectrum of HD 2133B matches theoretical models, demonstrating spectrophotometric calibration that is good to a few percent. Postprocessing on two 51 Eri b data sets demonstrates a median improvement in sensitivity of 80 and 30% for the 2015 and 2017 data, respectively, compared to the use of cubes reconstructed by the SPHERE Data Center. The largest improvements are seen for poorer observing conditions. The new SPHERE pipeline takes less than three minutes to produce a data cube on a modern laptop, making it practical to reprocess all SPHERE IFS data.
Key words: planets and satellites: detection / methods: data analysis / techniques: imaging spectroscopy / techniques: high angular resolution
The pipeline and documentation are publicly available at https://github.com/PrincetonUniversity/charis-dep
© M. Samland et al. 2022
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article is published in open access under the Subscribe-to-Open model.
Open Access funding provided by Max Planck Society.
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