JWST Advanced Deep Extragalactic Survey (JADES) Data Release 5: Wisp Subtraction with the Non-negative Matrix Factorization Algorithm

TL;DR

This paper presents a novel non-negative matrix factorization method to effectively model and subtract wisps in JWST/NIRCam images, improving data quality for faint-source photometry in extragalactic surveys.

Contribution

The authors develop a multi-component, template-based NMF approach for wisp subtraction, enhancing artifact removal over previous methods and providing publicly available templates for future use.

Findings

Lower residuals in wisp-affected regions.

Reduced photometric bias and scatter.

Templates are applicable to other datasets.

Abstract

Wisps are among the most prominent scattered light artifacts in JWST/NIRCam imaging. They often appear in certain regions of the detectors and contaminate observations at surface-brightness levels relevant for faint-source photometry. We introduce a new subtraction method that uses the non-negative matrix factorization (NMF) algorithm to model and remove wisps. Using deep NIRCam observations from the JWST Advanced Deep Extragalactic Survey (JADES) and other programs, we construct multi-component, filter- and detector-specific wisp templates that capture the wisp structures and their exposure-to-exposure morphological variations. Wisps in individual exposures are represented as non-negative linear combinations of these templates, consistent with their additive nature and reducing degeneracies relative to single-template scaling. Compared to existing approaches, our method delivers lower residual root mean square in wisp-affected regions and reduces photometric bias and scatter to levels consistent with clean detector areas. The NMF wisp templates are readily applicable to other datasets and are publicly released to support future NIRCam extragalactic surveys.