Issue |
A&A
Volume 680, December 2023
|
|
---|---|---|
Article Number | A34 | |
Number of page(s) | 8 | |
Section | Astronomical instrumentation | |
DOI | https://doi.org/10.1051/0004-6361/202346984 | |
Published online | 05 December 2023 |
Empirical contrast model for high-contrast imaging A VLT/SPHERE case study
1
European Southern Observatory,
Alonso de Córdova 3107, Vitacura, Casilla
19001,
Santiago, Chile
e-mail: bcourtne@eso.org
2
Research School of Astronomy and Astrophysics, Australian National University,
Canberra, ACT
2611, Australia
3
Institute of Astronomy and National Astronomical Observatory, Bulgarian Academy of Sciences,
72 Tsarigradsko Shose Blvd.,
Sofia
1784, Bulgaria
4
Université Grenoble Alpes, CNRS, IPAG,
38000
Grenoble, France
Received:
24
May
2023
Accepted:
26
September
2023
Context. The ability to accurately predict the contrast achieved with high-contrast imagers is important for efficient scheduling and quality control measures in modern observatories.
Aims. We aim to consistently predict and measure the raw contrast achieved by SPHERE/IRDIS on a frame-by-frame basis in order to improve the efficiency of SPHERE at the Very Large Telescope (VLT) and maximise scientific yield.
Methods. Contrast curves were calculated for over 5 yr of archival data obtained using the most common SPHERE/IRDIS corona-graphic mode in the H2/H3 dual-band filter. These data consist of approximately 80 000 individual frames, which were merged and interpolated with atmospheric data to create a large database of contrast curves with associated features. An empirical power-law model for contrast – motivated by physical considerations – was then trained and finally tested on an out-of-sample test dataset.
Results. At an angular separation of 300 mas, the contrast model achieved a mean (out-of-sample) test error of 0.13 magnitude with the 5th and 95th percentiles of the residuals equal to −0.23 and 0.64 magnitude respectively. The models test-set root mean square error (RMSE) between 250 and 600 mas was between 0.31 and 0.40 magnitude, which is equivalent to that of other state-of-the-art contrast models presented in the literature. In general, the model performed best for targets of between 5 and 9 G-band magnitude, with degraded performance for targets outside this range. This model is currently being incorporated into the Paranal SCUBA software for first-level quality control and real-time scheduling support.
Key words: methods: data analysis / methods: statistical / instrumentation: adaptive optics / atmospheric effects
© The Authors 2023
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.
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