Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Jimena Rodriguez
Janice Lee
Bradley Whitmore
David Thilker
Daniel Maschmann
Rupali Chandar
Daniel Dale
Diederik Kruijssen
Mederic Boquien
Kathryn Grasha
Elizabeth Watkins
Ashley Barnes
Mattia Sormani
Thomas Williams
Jaeyeon Kim
Gagandeep Anand
Mélanie Chevance
Frank Bigiel
Adam Leroy
Ralf Klessen
Abstract： The earliest stages of star formation occur enshrouded in dust and are not observable in the optical. Here we leverage the extraordinary new high-resolution infrared imaging from JWST to begin the study of dust-embedded star clusters in nearby galaxies throughout the local volume. We present a technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the first galaxy to be observed by the PHANGS-JWST Cycle 1 Treasury Survey. We select sources that have strong 3.3$\mu$m PAH emission based on a $\rm F300M-F335M$ color excess, and identify 67 candidate embedded clusters. Only eight of these are found in the PHANGS-HST optically-selected cluster catalog and all are young (six have SED-fit ages of $\sim1$ Myr). We find that this sample of embedded cluster candidates may significantly increase the census of young clusters in NGC 7496 from the PHANGS-HST catalog -- the number of clusters younger than $\sim$2 Myr could be increased by a factor of two. Candidates are preferentially located in dust lanes, and are coincident with peaks in PHANGS-ALMA CO (2-1) maps. We take a first look at concentration indices, luminosity functions, SEDs spanning from 2700A to 21$\mu$m, and stellar masses (estimated to be between $\sim10^4-10^5 M_{\odot}$). The methods tested here provide a basis for future work to derive accurate constraints on the physical properties of embedded clusters, characterize the completeness of cluster samples, and expand analysis to all 19 galaxies in the PHANGS-JWST sample, which will enable basic unsolved problems in star formation and cluster evolution to be addressed.
Peer Review Status:
Awaiting Review
Subjects: Astronomy >> Astrophysical processes submitted time 2023-02-19
Jiayi Sun
Adam K. Leroy
Eve C. Ostriker
Sharon Meidt
Erik Rosolowsky
Eva Schinnerer
Christine D. Wilson
Dyas Utomo
Francesco Belfiore
Guillermo A. Blanc
Eric Emsellem
Christopher Faesi
Brent Groves
Annie Hughes
Eric W. Koch
Kathryn Kreckel
Daizhong Liu
Hsi-An Pan
Jerome Pety
Miguel Querejeta
Abstract： We measure empirical relationships between the local star formation rate (SFR) and properties of the star-forming molecular gas on 1.5 kpc scales across 80 nearby galaxies. These relationships, commonly referred to as "star formation laws," aim at predicting the local SFR surface density from various combinations of molecular gas surface density, galactic orbital time, molecular cloud free-fall time, and the interstellar medium dynamical equilibrium pressure. Leveraging a multiwavelength database built for the PHANGS survey, we measure these quantities consistently across all galaxies and quantify systematic uncertainties stemming from choices of SFR calibrations and the CO-to-H$_2$ conversion factors. The star formation laws we examine show 0.3-0.4 dex of intrinsic scatter, among which the molecular Kennicutt-Schmidt relation shows a $\sim$10% larger scatter than the other three. The slope of this relation ranges $\beta\approx0.9{-}1.2$, implying that the molecular gas depletion time remains roughly constant across the environments probed in our sample. The other relations have shallower slopes ($\beta\approx0.6{-}1.0$), suggesting that the star formation efficiency (SFE) per orbital time, the SFE per free-fall time, and the pressure-to-SFR surface density ratio (i.e., the feedback yield) may vary systematically with local molecular gas and SFR surface densities. Last but not least, the shapes of the star formation laws depend sensitively on methodological choices. Different choices of SFR calibrations can introduce systematic uncertainties of at least 10-15% in the star formation law slopes and 0.15-0.25 dex in their normalization, while the CO-to-H$_2$ conversion factors can additionally produce uncertainties of 20-25% for the slope and 0.10-0.20 dex for the normalization.
Peer Review Status:Awaiting Review
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