Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728

0583671 - ASÚ 2025 RIV US eng J - Článek v odborném periodiku
Leist, M. T. - Packham, C. - Rosario, D. J. - Boorman, Peter G. … celkem 35 autorů
Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728.
Astronomical Journal. Roč. 167, č. 3 (2024), č. článku 96. ISSN 0004-6256. E-ISSN 1538-3881
Institucionální podpora: RVO:67985815
Klíčová slova: deconvolution * James Webb Space Telescope * active galactic nuclei
Obor OECD: Astronomy (including astrophysics,space science)
Impakt faktor: 5.3, rok: 2022
Způsob publikování: Open access

We present an assessment of several deconvolution approaches to improve image quality and mitigate the effects of the complex JWST point-spread function (PSF). The optimal deconvolution method is determined by using WebbPSF to simulate JWST's complex PSF and MIRISim to simulate multiband JWST/Mid-Infrared Imager Module (MIRIM) observations of a toy model of an active galactic nucleus (AGN). Five different deconvolution algorithms are tested: (1) Kraken deconvolution, (2) Richardson-Lucy, (3) the adaptive imaging deconvolution algorithm, (4) sparse regularization with the Condat-Vu algorithm, and (5) iterative Wiener filtering and thresholding. We find that Kraken affords the greatest FWHM reduction of the nuclear source of our MIRISim observations for the toy AGN model while retaining good photometric integrity across all simulated wave bands. Applying Kraken to Galactic Activity, Torus, and Outflow Survey (GATOS) multiband JWST/MIRIM observations of the Seyfert 2 galaxy NGC 5728, we find that the algorithm reduces the FWHM of the nuclear source by a factor of 1.6-2.2 across all five filters. Kraken images facilitate detection of extended nuclear emission similar to 2.'' 5 (similar to 470 pc, position angle similar or equal to 115 degrees) in the SE-NW direction, especially at the longest wavelengths. We demonstrate that Kraken is a powerful tool to enhance faint features otherwise hidden in the complex JWST PSF.
Trvalý link: https://hdl.handle.net/11104/0353288