In preparation to make the most of our own planned James Webb Space Telescope investigations, we take advantage of publicly available calibration and early-science observations to independently derive and test a geometric-distortion solution for NIRCam detectors. Our solution is able to correct the distortion to better than similar to 0.2 mas. Current data indicate that the solution is stable and constant over the investigated filters, temporal coverage, and even over the available filter combinations. We successfully tested our geometric-distortion solution in three cases: (i) field-object decontamination of M 92 field; (ii) estimate of internal proper motions of M 92; and (iii) measurement of the internal proper motions of the Large Magellanic Cloud system. To our knowledge, the here-derived geometric-distortion solution for NIRCam is the best available and we publicly release it, as many other investigations could potentially benefit from it. Along with our geometric-distortion solution, we also release a Python tool to convert the raw-pixels coordinates of each detector into distortion-free positions, and also to put all the ten detectors of NIRCam into a common reference system.

Photometry and astrometry with JWST - II: distortion correction

D. Nardiello;
2023

Abstract

In preparation to make the most of our own planned James Webb Space Telescope investigations, we take advantage of publicly available calibration and early-science observations to independently derive and test a geometric-distortion solution for NIRCam detectors. Our solution is able to correct the distortion to better than similar to 0.2 mas. Current data indicate that the solution is stable and constant over the investigated filters, temporal coverage, and even over the available filter combinations. We successfully tested our geometric-distortion solution in three cases: (i) field-object decontamination of M 92 field; (ii) estimate of internal proper motions of M 92; and (iii) measurement of the internal proper motions of the Large Magellanic Cloud system. To our knowledge, the here-derived geometric-distortion solution for NIRCam is the best available and we publicly release it, as many other investigations could potentially benefit from it. Along with our geometric-distortion solution, we also release a Python tool to convert the raw-pixels coordinates of each detector into distortion-free positions, and also to put all the ten detectors of NIRCam into a common reference system.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3497002
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