JWST/NIRCam calibrations for TEMPLATES-SGAS1723 with extant HST imaging and Bayesian SED Fitting
Abstract
In this talk, we present data quality, calibration products and results from the JWST Early Release Science Program TEMPLATES (PID: 1355). The TEMPLATES program (Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star Formation) targets 4 bright strongly gravitationally lensed arcs with redshifts ranging from z =1 to 4. Since JWST is currently executing its first calibration cycle, reducing TEMPLATES data requires extensive modeling and several iterations across imaging exposures, detectors, filters and point-spread functions. Here, we focus on the reduction process for JWST/NIRCam imaging of SDSS J1723+3411, a strong lensing galaxy cluster at z=1.32, observed in June 2022. With the help of SDSS1723's extensive ancillary datasets, we perform an independent and complementary check on existing reduction pipelines and other community products to reduce NIRCam data. Using HST imaging of SDSS1723, we model the spectral energy distribution (SED) of massive quiescent galaxies in the cluster using Bayesian SED fitting. We utilize our best fit models to predict JWST photometry of the quiescent member galaxies. By comparing these predictions with observed NIRCam flux, we robustly quantify potential corrections (of the order of ~0.1-0.4 AB mags). We also share our results in the context of the current iterations of JWST reduction pipelines, and lessons learnt since JWST commissioning.
- Publication:
-
American Astronomical Society Meeting Abstracts
- Pub Date:
- January 2023
- Bibcode:
- 2023AAS...24143203W