The PHANGS-HST Survey: Physics at High Angular resolution in Nearby GalaxieS with the Hubble Space Telescope

TL;DR

The PHANGS-HST survey provides high-resolution UV-optical imaging of 38 nearby spiral galaxies, creating a comprehensive catalog of star-forming regions, star clusters, and associations to study star formation processes across diverse galactic environments.

Contribution

This work introduces the PHANGS-HST survey, combining multi-band imaging with advanced data processing and classification methods to systematically analyze star formation units in nearby galaxies.

Findings

Catalog of tens of thousands of star clusters and associations

New methods for morphological classification using neural networks

Identification of stellar associations across physical scales

Abstract

The PHANGS program is building the first dataset to enable the multi-phase, multi-scale study of star formation across the nearby spiral galaxy population. This effort is enabled by large survey programs with ALMA, VLT/MUSE, and HST, with which we have obtained CO(2-1) imaging, optical spectroscopic mapping, and high resolution UV-optical imaging, respectively. Here, we present PHANGS-HST, which has obtained five band NUV-U-B-V-I imaging of the disks of 38 spiral galaxies at distances of 4-23 Mpc, and parallel V and I band imaging of their halos, to provide a census of tens of thousands of compact star clusters, and multi-scale stellar associations. The combination of HST, ALMA, and VLT/MUSE observations will yield an unprecedented joint catalog of the observed and physical properties of ~100,000 star clusters, associations, HII regions, and molecular clouds. With these basic units of star formation, PHANGS will systematically chart the evolutionary cycling between gas and stars, across a diversity of galactic environments found in nearby galaxies. We discuss the design of the PHANGS-HST survey, and provide an overview of the HST data processing pipeline and first results, highlighting new methods for selecting star cluster candidates, morphological classification of candidates with convolutional neural networks, and identification of stellar associations over a range of physical scales with a watershed algorithm. We describe the cross-observatory imaging, catalogs, and software products to be released. These high-level science products will seed a broad range of investigations, in particular, the study of embedded stellar populations and dust with JWST, for which a PHANGS Cycle 1 Treasury program to obtain eight band 2-21 $\mu$m imaging has been approved.