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AIROPA II: modeling instrumental aberrations for off-axis point spread functions in adaptive optics

Ciurlo, Anna and Turri, Paolo and Witzel, Gunther and Lu, Jessica R. and Do, Tuan and Sitarski, Breann N. and Fitzgerald, Michael P. and Ghez, Andrea M. and Alvarez, Carlos and Terry, Sean K. and Doppmann, Greg and Lyke, James E. and Ragland, Sam and Campbell, Randall and Matthews, Keith (2022) AIROPA II: modeling instrumental aberrations for off-axis point spread functions in adaptive optics. Journal of Astronomical Telescopes, Instruments, and Systems, 8 (3). Art. No. 8.3.038007. ISSN 2329-4124. doi:10.1117/1.jatis.8.3.038007. https://resolver.caltech.edu/CaltechAUTHORS:20221024-125854800.23

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Abstract

Images obtained with single-conjugate adaptive optics (AO) show spatial variation of the point spread function (PSF) due to both atmospheric anisoplanatism and instrumental aberrations. The poor knowledge of the PSF across the field of view strongly impacts the ability to take full advantage of AO capabilities. The AIROPA project aims to model these PSF variations for the NIRC2 imager at the Keck Observatory. Here, we present the characterization of the instrumental phase aberrations over the entire NIRC2 field of view and we present a metric for quantifying the quality of the calibration, the fraction of variance unexplained (FVU). We used phase diversity measurements obtained on an artificial light source to characterize the variation of the aberrations across the field of view and their evolution with time. We find that there is a daily variation of the wavefront error (RMS of the residuals is 94 nm) common to the whole detector, but the differential aberrations across the field of view are very stable (RMS of the residuals between different epochs is 59 nm). This means that instrumental calibrations need to be monitored often only at the center of the detector, and the much more time-consuming variations across the field of view can be characterized less frequently (most likely when hardware upgrades happen). Furthermore, we tested AIROPA’s instrumental model through real data of the fiber images on the detector. We find that modeling the PSF variations across the field of view improves the FVU metric by 60% and reduces the detection of fake sources by 70%.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1117/1.JATIS.8.3.038007DOIArticle
ORCID:
AuthorORCID
Ciurlo, Anna0000-0001-5800-3093
Witzel, Gunther0000-0003-2618-797X
Lu, Jessica R.0000-0001-9611-0009
Do, Tuan0000-0001-9554-6062
Fitzgerald, Michael P.0000-0002-0176-8973
Ghez, Andrea M.0000-0003-3230-5055
Terry, Sean K.0000-0002-5029-3257
Lyke, James E.0000-0001-7809-7867
Ragland, Sam0000-0002-0696-1780
Additional Information:We acknowledge the support provided by NSF (grant nos. AST-1412615 and AST-1518273), Jim and Lori Keir, the Gordon and Betty Moore Foundation, the Heising–Simons Foundation, the W. M. Keck Foundation, Howard and Astrid Preston. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain.
Funders:
Funding AgencyGrant Number
NSFAST-1412615
NSFAST-1518273
Jim and Lori KeirUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Heising-Simons FoundationUNSPECIFIED
W. M. Keck FoundationUNSPECIFIED
Issue or Number:3
DOI:10.1117/1.jatis.8.3.038007
Record Number:CaltechAUTHORS:20221024-125854800.23
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20221024-125854800.23
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:117553
Collection:CaltechAUTHORS
Deposited By: Research Services Depository
Deposited On:01 Nov 2022 20:45
Last Modified:01 Nov 2022 20:45

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