  With their high angular resolutions of 30--100 mas, large fields of view, and
complex optical systems, imagers on next-generation optical/near-infrared space
observatories, such as the Near-Infrared Camera (NIRCam) on the James Webb
Space Telescope (JWST), present both new opportunities for science and also new
challenges for empirical point spread function (PSF) characterization. In this
context, we introduce ShOpt, a new PSF fitting tool developed in Julia and
designed to bridge the advanced features of PIFF (PSFs in the Full Field of
View) with the computational efficiency of PSFEx (PSF Extractor). Along with
ShOpt, we propose a suite of non-parametric statistics suitable for evaluating
PSF fit quality in space-based imaging. Our study benchmarks ShOpt against the
established PSF fitters PSFEx and PIFF using real and simulated COSMOS-Web
Survey imaging. We assess their respective PSF model fidelity with our proposed
diagnostic statistics and investigate their computational efficiencies,
focusing on their processing speed relative to the complexity and size of the
PSF models. We find that ShOpt can already achieve PSF model fidelity
comparable to PSFEx and PIFF while maintaining competitive processing speeds,
constructing PSF models for large NIRCam mosaics within minutes.
