LEGGOS III: Mapping Star Formation and Dust in Gravitationally Lensed Galaxies with $\textit{SUMAC}$, a UMAP and Clustering Framework

Abstract

Strong gravitational lensing combined with JWST's spatio-spectral resolution enables resolved studies of star-forming regions in $z\sim$ 2-4 galaxies, but identifying and characterizing such regions in lensed integral-field and multi-band data remains a manual, observer-dependent process. We present $\texttt{SUMAC}$ (Software for the Uniform Manifold Approximation of Clumps), an unsupervised learning pipeline that segments JWST imaging and spectroscopy at the "spaxel" level by combining $\texttt{UMAP}$-based manifold embedding with $\texttt{HDBSCAN}$ density clustering applied to spectral energy distributions/spectra. We demonstrate the pipeline on JWST/NIRSpec PRISM IFS observations of the lensed galaxy SGAS111020.0+645950.8 at $z = 2.481$, recovering six physically distinct stellar/nebular populations. The cluster median SEDs separate cleanly on the presence and strength of H$β$+[OIII], H$α$+[NII], $β_{NUV}$ slope, Balmer break strength, and the Balmer decrement, with bluer clusters tracing unobscured star-forming regions and progressively redder clusters tracing dusty star-forming regions.