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Abstract We employ the Feedback In Realistic Environments (FIRE-2) physics model to study how the properties of giant molecular clouds (GMCs) evolve during galaxy mergers. We conduct a pixel-by-pixel analysis of molecular gas properties in both the simulated control galaxies and galaxy major mergers. The simulated GMC pixels in the control galaxies follow a similar trend in a diagram of velocity dispersion (σ_v) versus gas surface density (Σ_mol) to the one observed in local spiral galaxies in the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey. For GMC pixels in simulated mergers, we see a significant increase of a factor of 5–10 in both Σ_molandσ_v, which puts these pixels above the trend of PHANGS galaxies in theσ_vversus Σ_moldiagram. This deviation may indicate that GMCs in the simulated mergers are much less gravitationally bound compared with simulated control galaxies with virial parameters (α_vir) reaching 10–100. Furthermore, we find that the increase inα_virhappens at the same time as the increase in global star formation rate, which suggests that stellar feedback is responsible for dispersing the gas. We also find that the gas depletion time is significantly lower for high-α_virGMCs during a starburst event. This is in contrast to the simple physical picture that low-α_virGMCs are easier to collapse and form stars on shorter depletion times. This might suggest that some other physical mechanisms besides self-gravity are helping the GMCs in starbursting mergers collapse and form stars. 

Abstract The properties of young massive clusters (YMCs) are key to understanding the star formation mechanism in starburst systems, especially mergers. We present Atacama Large Millimeter/submillimeter Array high-resolution (∼10 pc) continuum (100 and 345 GHz) data of YMCs in the overlap region of the Antennae galaxy. We identify six sources in the overlap region, including two sources that lie in the same giant molecular cloud (GMC). These YMCs correspond well with radio sources in lower-resolution continuum (100 and 220 GHz) images at GMC scales (∼60 pc). We find most of these YMCs are bound clusters through virial analysis. We estimate their ages to be ∼1 Myr and that they are either embedded or just beginning to emerge from their parent cloud. We also compare each radio source with a Pa β source, and find they have consistent total ionizing photon numbers, which indicates they are tracing the same physical source. By comparing the free–free emission at ∼10 pc scale and ∼60 pc scale, we find that ∼50% of the free–free emission in GMCs actually comes from these YMCs. This indicates that roughly half of the stars in massive GMCs are formed in bound clusters. We further explore the mass correlation between YMCs and GMCs in the Antennae and find it generally agrees with the predictions of the star cluster simulations. The most massive YMC has a stellar mass that is 1%–5% of its host GMC mass. 

Abstract We use 0.1″ observations from the Atacama Large Millimeter Array (ALMA), Hubble Space Telescope (HST), and JWST to study young massive clusters (YMCs) in their embedded “infant” phase across the central starburst ring in NGC 3351. Our new ALMA data reveal 18 bright and compact (sub-)millimeter continuum sources, of which 8 have counterparts in JWST images and only 6 have counterparts in HST images. Based on the ALMA continuum and molecular line data, as well as ancillary measurements for the HST and JWST counterparts, we identify 14 sources as infant star clusters with high stellar and/or gas masses (∼10⁵M_⊙), small radii (≲ 5 pc), large escape velocities (6–10 km s⁻¹), and short freefall times (0.5–1 Myr). Their multiwavelength properties motivate us to divide them into four categories, likely corresponding to four evolutionary stages from starless clumps to exposed Hiiregion–cluster complexes. Leveraging age estimates for HST-identified clusters in the same region, we infer an evolutionary timeline, ranging from ∼1–2 Myr before cluster formation as starless clumps, to ∼4–6 Myr after as exposed Hiiregion–cluster complexes. Finally, we show that the YMCs make up a substantial fraction of recent star formation across the ring, exhibit a nonuniform azimuthal distribution without a very coherent evolutionary trend along the ring, and are capable of driving large-scale gas outflows. 

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 Physics at High Angular Resolution in Nearby Galaxies (PHANGS) survey, we measure these quantities consistently across all galaxies and quantify systematic uncertainties stemming from choices of SFR calibrations and the CO-to-H₂conversion 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 ∼10% larger scatter than the other three. The slope of this relation rangesβ≈ 0.9–1.2, implying that the molecular gas depletion time remains roughly constant across the environments probed in our sample. The other relations have shallower slopes (β≈ 0.6–1.0), suggesting that the star formation efficiency per orbital time, the star formation efficiency per free fall time, and the pressure-to-SFR surface density ratio (i.e., the feedback yield) 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-H₂conversion factors can additionally produce uncertainties of 20%–25% for the slope and 0.10–0.20 dex for the normalization.