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We analyse the first giant molecular cloud (GMC) simulation to follow the formation of individual stars and their feedback from jets, radiation, winds, and supernovae, using the STARFORGE framework in the GIZMO code. We evolve the GMC for $\sim 9 \rm Myr$, from initial turbulent collapse to dispersal by feedback. Protostellar jets dominate feedback momentum initially, but radiation and winds cause cloud disruption at $\sim 8{{\ \rm per\ cent}}$ star formation efficiency (SFE), and the first supernova at $8.3\, \rm Myr$ comes too late to influence star formation significantly. The per-free-fall SFE is dynamic, accelerating from 0 per cent to $\sim 18{{\ \rm per\ cent}}$ before dropping quickly to <1 per cent, but the estimate from YSO counts compresses it to a narrower range. The primary cluster forms hierarchically and condenses to a brief ($\sim 1\, \mathrm{Myr}$) compact ($\sim 1\, \rm pc$) phase, but does not virialize before the cloud disperses, and the stars end as an unbound expanding association. The initial mass function resembles the Chabrier (2005) form with a high-mass slope α = −2 and a maximum mass of 55 M⊙. Stellar accretion takes $\sim 400\, \rm kyr$ on average, but $\gtrsim 1\,\rm Myr$ for >10 M⊙ stars, so massive stars finishmore »growing latest. The fraction of stars in multiples increase as a function of primary mass, as observed. Overall, the simulation much more closely resembles reality, compared to previous versions that neglected different feedback physics entirely. But more detailed comparison with synthetic observations will be needed to constrain the theoretical uncertainties.

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Simulations of isolated giant molecular clouds (GMCs) are an important tool for studying the dynamics of star formation, but their turbulent initial conditions (ICs) are uncertain. Most simulations have either initialized a velocity field with a prescribed power spectrum on a smooth density field (failing to model the full structure of turbulence) or ‘stirred’ turbulence with periodic boundary conditions (which may not model real GMC boundary conditions). We develop and test a new GMC simulation setup (called turbsphere) that combines advantages of both approaches: we continuously stir an isolated cloud to model the energy cascade from larger scales, and use a static potential to confine the gas. The resulting cloud and surrounding envelope achieve a quasi-equilibrium state with the desired hallmarks of supersonic ISM turbulence (e.g. density PDF and a ∼k−2 velocity power spectrum), whose bulk properties can be tuned as desired. We use the final stirred state as initial conditions for star formation simulations with self-gravity, both with and without continued driving and protostellar jet feedback, respectively. We then disentangle the respective effects of the turbulent cascade, simulation geometry, external driving, and gravity/MHD boundary conditions on the resulting star formation. Without external driving, the new setup obtains resultsmore »similar to previous simple spherical cloud setups, but external driving can suppress star formation considerably in the new setup. Periodic box simulations with the same dimensions and turbulence parameters form stars significantly slower, highlighting the importance of boundary conditions and the presence or absence of a global collapse mode in the results of star formation calculations.

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We characterize protostellar multiplicity in²⁰

Current address: Niels Bohr Institute, University of Copenhagen, Øster Voldgade 5–7, DK-1350, Copenhagen K, Denmark.

the Orion molecular clouds using Atacama Large Millimeter/submillimeter Array 0.87 mm and Very Large Array 9 mm continuum surveys toward 328 protostars. These observations are sensitive to projected spatial separations as small as ∼20 au, and we consider source separations up to 10⁴au as potential companions. The overall multiplicity fraction (MF) and companion fraction (CF) for the Orion protostars are 0.30 ± 0.03 and 0.44 ± 0.03, respectively, considering separations from 20 to 10⁴au. The MFs and CFs are corrected for potential contamination by unassociated young stars using a probabilistic scheme based on the surface density of young stars around each protostar. The companion separation distribution as a whole is double peaked and inconsistent with the separation distribution of solar-type field stars, while the separation distribution of Flat Spectrum protostars is consistent solar-type field stars. The multiplicity statistics and companion separation distributions of the Perseus star-forming region are consistent with those of Orion. Based on the observed peaks in the Class 0 separations at ∼100 au and ∼10³au, we argue that multiples with separations <500 au are likely produced bymore »both disk fragmentation and turbulent fragmentation with migration, and those at ≳10³au result primarily from turbulent fragmentation. We also find that MFs/CFs may rise from Class 0 to Flat Spectrum protostars between 100 and 10³au in regions of high young stellar object density. This finding may be evidence for the migration of companions from >10³au to <10³au, and that some companions between 10³and 10⁴au must be (or become) unbound.

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Abstract We adopt the deep learning method casi-3d (Convolutional Approach to Structure Identification-3D) to systemically identify protostellar outflows in 12 CO and 13 CO observations of the nearby molecular clouds, Ophiuchus, Taurus, Perseus, and Orion. The total outflow masses are 267 M ⊙ , 795 M ⊙ , 1305 M ⊙ , and 6332 M ⊙ for Ophiuchus, Taurus, Perseus, and Orion, respectively. We show the outflow mass in each cloud is linearly proportional to the total number of young stellar objects. The estimated total 3D deprojected outflow energies are 9 × 10 45 erg, 6 × 10 46 erg, 1.2 × 10 47 erg, and 6 × 10 47 erg for Ophiuchus, Taurus, Perseus, and Orion, respectively. The energy associated with outflows is sufficient to offset turbulent dissipation at the current epoch for all four clouds. All clouds also exhibit a break point in the spatial power spectrum of the outflow prediction map, which likely corresponds to the typical outflow mass and energy injection scale.

Abstract We use hydrodynamical simulations of star-forming gas with stellar feedback and sink particles—proxies for young stellar objects (YSOs)—to produce and analyze synthetic 1.1 mm continuum observations at different distances (150–1000 pc) and ages (0.49–1.27 Myr). We characterize how the inferred core properties, including mass, size, and clustering with respect to diffuse natal gas structure, change with distance, cloud evolution, and the presence of YSOs. We find that atmospheric filtering and core segmentation treatments have distance-dependent impacts on the resulting core properties for d < 300 pc and 500 pc, respectively, which dominate over evolutionary differences. Concentrating on synthetic observations at further distances (650–1000 pc), we find a growing separation between the inferred sizes and masses of cores with and without YSOs in the simulations, which is not seen in recent observations of the Monoceros R2 (Mon R2) cloud at 860 pc. We find that the synthetic cores cluster in smaller groups, and that their mass densities are correlated with gas column density over a much narrower range, than those in the Mon R2 observations. Such differences limit the applicability of the evolutionary predictions we report here, but will motivate our future efforts to adapt our synthetic observation and analysismore »framework to next generation simulations, such as Star Formation in Gaseous Environments (STARFORGE). These predictions and systematic characterizations will help to guide the analysis of cores on the upcoming TolTEC Clouds to Cores Legacy Survey on the Large Millimeter Telescope Alfonso Serrano.« less

Abstract We present STARFORGE (STAR FORmation in Gaseous Environments): a new numerical framework for 3D radiation MHD simulations of star formation that simultaneously follow the formation, accretion, evolution, and dynamics of individual stars in massive giant molecular clouds (GMCs) while accounting for stellar feedback, including jets, radiative heating and momentum, stellar winds, and supernovae. We use the GIZMO code with the MFM mesh-free Lagrangian MHD method, augmented with new algorithms for gravity, timestepping, sink particle formation and accretion, stellar dynamics, and feedback coupling. We survey a wide range of numerical parameters/prescriptions for sink formation and accretion and find very small variations in star formation history and the IMF (except for intentionally-unphysical variations). Modules for mass-injecting feedback (winds, SNe, and jets) inject new gas elements on-the-fly, eliminating the lack of resolution in diffuse feedback cavities otherwise inherent in Lagrangian methods. The treatment of radiation uses GIZMO’s radiative transfer solver to track 5 frequency bands (IR, optical, NUV, FUV, ionizing), coupling direct stellar emission and dust emission with gas heating and radiation pressure terms. We demonstrate accurate solutions for SNe, winds, and radiation in problems with known similarity solutions, and show that our jet module is robust to resolution and numerical details,more »and agrees well with previous AMR simulations. STARFORGE can scale up to massive (>105M⊙) GMCs on current supercomputers while predicting the stellar (≳ 0.1M⊙) range of the IMF, permitting simulations of both high- and low-mass cluster formation in a wide range of conditions.« less

Context. Stars form in cold dense cores showing subsonic velocity dispersions. The parental molecular clouds display higher temperatures and supersonic velocity dispersions. The transition from core to cloud has been observed in velocity dispersion, but temperature and abundance variations are unknown. Aims. We aim to measure the temperature and velocity dispersion across cores and ambient cloud in a single tracer to study the transition between the two regions. Methods. We use NH 3 (1,1) and (2,2) maps in L1688 from the Green Bank Ammonia Survey, smoothed to 1′, and determine the physical properties by fitting the spectra. We identify the coherent cores and study the changes in temperature and velocity dispersion from the cores to the surrounding cloud. Results. We obtain a kinetic temperature map extending beyond dense cores and tracing the cloud, improving from previous maps tracing mostly the cores. The cloud is 4–6 K warmer than the cores, and shows a larger velocity dispersion (Δ σ v = 0.15–0.25 km s −1 ). Comparing to Herschel -based dust temperatures, we find that cores show kinetic temperatures that are ≈1.8 K lower than the dust temperature, while the gas temperature is higher than the dust temperature in the cloud.more »We find an average p-NH 3 fractional abundance (with respect to H 2 ) of (4.2 ± 0.2) × 10 −9 towards the coherent cores, and (1.4 ± 0.1) × 10 −9 outside the core boundaries. Using stacked spectra, we detect two components, one narrow and one broad, towards cores and their neighbourhoods. We find the turbulence in the narrow component to be correlated with the size of the structure (Pearson- r = 0.54). With these unresolved regional measurements, we obtain a turbulence–size relation of σ v,NT ∝ r 0.5 , which is similar to previous findings using multiple tracers. Conclusions. We discover that the subsonic component extends up to 0.15 pc beyond the typical coherent boundaries, unveiling larger extents of the coherent cores and showing gradual transition to coherence over ~0.2 pc.« less