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Abstract Star formation occurs within dense regions of giant molecular clouds (GMCs); however, exactly how gas collects and evolves to form individual stars and what role dense cores play remains unclear. We use the Lagrangian cell information in the STARFORGE simulation suite to track star-forming gas in three GMCs with varying magnetic field strengths. We find that once a protostar forms, the lifetime of the unaccreted gas correlates with the final stellar mass, where low-mass stars (M_* < 0.5M_⊙) accrete for 0.5–0.6 Myr from a relatively local reservoir of gas and high-mass stars (M_* > 2M_⊙) accrete over 3.3–4.7 Myr from a much larger volume. Although the protostellar accretion time increases weakly with magnetic field strength, the accreting gas radii, velocity dispersions, virial parameters, and magnetic energy ratios are largely insensitive to the global cloud properties. At the time of protostar formation, the unaccreted gas exhibits linewidth-size and mass-size relations characteristic of turbulently regulated, isothermal dense cores, followingσ_v ∝ R^1.0−1.1andM ∝ R^0.47−0.55, respectively. Low- and intermediate-mass stars undergo relatively continuous accretion, and their accretion histories are well-fit by isothermal sphere, turbulent core, or competitive accretion models, where no one model fits all masses. However, many high-mass stars experience intermittent accretion, and their accretion histories are not well-fit by any of these models. While the distribution of accreting gas is more extended than typically defined dense cores, the physical properties and structure of the star-forming gas resemble those of observed cores and are largely regulated by turbulence and feedback. 

Abstract Artificial intelligence is rapidly being integrated into a variety of tasks in astronomical research, from model fitting to anomaly detection. While AI offers huge potential to accelerate discoveries about the universe, its current capabilities and trustworthiness fall short. I discuss the road to full AI integration into astronomical workflows: why the field of astronomy is a particularly fertile ground for AI development, the potential revolutionary gains possible for scientific analysis and discovery, how AI developments within astronomy can accelerate AI advancements more broadly, and the current roadblocks to fully AI-integrated astronomy. 

Abstract We present a population study of Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 6 observations of the 100 most gravitationally unstable dense cores in Aquila using a simple mass versus size analysis. We identify 66 continuum sources from ALMA 12 m observations at 106 GHz and through comparisons with known protostellar catalogs; two of these detected dense cores appear to be completely starless, without any accompanying/nearby protostar detections. Additionally, we find nine other starless ALMA 12 m detections within protostellar cores that have fragmented into a mixture of starless and protostellar substructures. We test the turbulent core collapse model by conducting synthetic observations of turbulent magnetohydrodynamical simulations of collapsing starless cores in order to predict how many starless cores should be detected given their central density and density profile. The simulations predict at least one (1.19) detection, consistent with our two detections of ALMA 12 m emission within completely starless cores. We also use a combination of ALMA Compact Array Cycle 4 observations and the Herschel Gould Belt Survey data to analyze how mass is distributed on three distinct spatial scales, in order to understand how turbulence shapes the evolution of substructure development as dense cores collapse to form new star systems. We find an increase in multiplicity at the smallest scales when the parent larger-scale structure also has a higher degree of fragmentation. 

Abstract We present the first systematic study of explosive dispersal outflows (EDOs) as potential sources of high-energy emission in the Milky Way. EDOs are energetic outflows produced during dynamical interactions in young, massive star-forming regions, and their physical conditions make them promising environments for cosmic-ray acceleration. Using 16 yr of 0.2–500 GeV Fermi-Large Area Telescope observations, we study theγ-ray properties of seven EDOs. Three EDOs, DR21, G34.26+0.15, and G5.89−0.39, show spatially coincident GeV emission, while the remaining systems yield nondetections. Among the sample, DR21 stands out as the brightest candidate, with a detection significance ≥40σ. Its spectrum is well described by a power law with an exponential cutoff, and the integrated luminosity in the 0.1–500 GeV band isL_γ ≃ 2 × 10³⁵erg s⁻¹. When compared with the outflow’s estimated kinetic energy, the inferred cosmic-ray acceleration efficiency is ≤15%, consistent with values for shocks in dense molecular environments. The energetics and morphology support an association between the DR21 molecular outflow and the observedγ-rays. Our results demonstrate that EDOs span a wide range ofγ-ray luminosities and efficiencies, suggesting they may contribute to the Galactic cosmic-ray budget. This motivates searches for additional EDOs and improved multiwavelength characterization of their environments. 

Neural Operators (NOs) are a leading method for surrogate modeling of partial differential equations. Unlike traditional neural networks, which approximate individual functions, NOs learn the mappings between function spaces. While NOs have been predominantly tested on simplified 1D and 2D problems, such as those explored in prior works, these studies fail to address the complexities of more realistic, high-dimensional, and high-dynamic range systems. Moreover, many real-world applications involve incomplete or noisy data, which has not been adequately explored in current NO literature. In this work, we present a novel application of NOs to astrophysical data, which involves high-dynamic range projections into an observational space. We train Fourier NO (FNO) models to predict the evolution of incomplete observational proxies with density variations spanning four orders of magnitude. We demonstrate that FNOs can predict the effects of unobserved dynamical variables. Our work lays the groundwork for future studies that forecast direct astronomical observables. 

Abstract Most stars form in multiple systems, with profound implications in numerous astronomical phenomena intrinsically linked to multiplicity. However, our knowledge about the process of how multiple stellar systems form is incomplete and biased toward nearby molecular clouds forming only low-mass stars, which are unrepresentative of the stellar population in the Galaxy. Most stars form within dense cores in clusters alongside high-mass stars (>8M_⊙), as the Sun likely did. Here we report deep Atacama Large Millimeter/submillimeter Array (ALMA) 1.33 mm dust continuum observations at ∼160 au spatial resolution, revealing 72 low-mass multiple systems embedded in 23 high-mass cluster-forming regions, as part of the Digging into the Interior of Hot Cores with ALMA survey. We find that the companion separation distribution presents a distinct peak at ∼1200 au, in contrast to the one at ∼4000 au observed in nearby low-mass regions. The shorter fragmentation scale can be explained by considering the higher pressure exerted by the surrounding medium, which is higher than the one in low-mass regions, due to the larger turbulence and densities involved. Because the peak of the companion separation distribution occurs at much larger scales than the expected disk sizes, we argue that the observed fragmentation is produced by turbulent core fragmentation. Contrary to predictions, the multiplicity fraction remains constant as the stellar density increases. We propose that in the extremely dense environments where high-mass stars form, dynamical interactions play an important role in disrupting weakly bound systems. 

Abstract We explore the relation between stellar surface density and gas surface density (the star–gas, or S-G, correlation) in a 20,000M_⊙simulation from the STAR FORmation in Gaseous Environments (starforge) project. We create synthetic observations based on the Spitzer and Herschel telescopes by modeling contamination by active galactic nuclei, smoothing based on angular resolution, cropping the field of view, and removing close neighbors and low-mass sources. We extract S-G properties such as the dense gas-mass fraction, the Class II:I ratio, and the S-G correlation (Σ_YSO/Σ_gas) from the simulation and compare them to observations of giant molecular clouds, young clusters, and star-forming regions, as well as to analytical models. We find that the simulation reproduces trends in the counts of young stellar objects and the median slope of the S-G correlation. This implies that the S-G correlation is not simply the result of observational biases, but is in fact a real effect. However, other statistics, such as the Class II:I ratio and dense gas-mass fraction, do not always match observed equivalents in nearby clouds. This motivates further observations covering the full simulation age range and more realistic modeling of cloud formation. 

Recently, we demonstrated self-consistent formation of strongly-magnetized quasar accretion disks (QADs) from cosmological radiation-magnetohydrodynamic-thermochemical galaxy-star formation simulations, including the full STARFORGE physics shown previously to produce a reasonable IMF under typical ISM conditions. Here we study star formation and the stellar IMF in QADs, on scales from 100 au to 10 pc from the SMBH. We show it is critical to include physics often previously neglected, including magnetic fields, radiation, and (proto)stellar feedback. Closer to the SMBH, star formation is suppressed, but the (rare) stars that do form exhibit top-heavy IMFs. Stars can form only in special locations (e.g. magnetic field switches) in the outer QAD. Protostars accrete their natal cores rapidly but then dynamically decouple from the gas and ‘wander,’ ceasing accretion on timescales ~100 yr. Their jets control initial core accretion, but the ejecta are ‘swept up’ into the larger-scale QAD flow without much dynamical effect. The strong tidal environment strongly suppresses common-core multiplicity. The IMF shape depends sensitively on un-resolved dynamics of protostellar disks (PSDs), as the global dynamical times can become incredibly short (< yr) and tidal fields are incredibly strong, so whether PSDs can efficiently transport angular momentum or fragment catastrophically at <10 au scales requires novel PSD simulations to properly address. Most analytic IMF models and analogies with planet formation in PSDs fail qualitatively to explain the simulation IMFs, though we discuss a couple of viable models.