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Abstract We define a sample of 200 protostellar outflows showing blue- and redshifted CO emission in the nearby molecular clouds Ophiuchus, Taurus, Perseus, and Orion, to investigate the correlation between outflow orientations and local, but relatively large-scale, magnetic field directions traced by Planck 353 GHz dust polarization. At high significance ( p ∼ 10 −4 ), we exclude a random distribution of relative orientations and find that there is a preference for alignment of projected plane of sky outflow axes with magnetic field directions. The distribution of relative position angles peaks at ∼30° and exhibits a broad dispersion of ∼50°. These results indicate that magnetic fields have dynamical influence in regulating the launching and/or propagation directions of outflows. However, the significant dispersion around perfect alignment orientation implies that there are large measurement uncertainties and/or a high degree of intrinsic variation caused by other physical processes, such as turbulence or strong stellar dynamical interactions. Outflow to magnetic field alignment is expected to lead to a correlation in the directions of nearby outflow pairs, depending on the degree of order of the field. Analyzing this effect, we find limited correlation, except on relatively small scales ≲0.5 pc. Furthermore, we train a convolutionalmore »neural network to infer the inclination angle of outflows with respect to the line of sight and apply it to our outflow sample to estimate their full 3D orientations. We find that the angles between outflow pairs in 3D space also show evidence of small-scale alignment.« less

ABSTRACT We study the formation, evolution, and collapse of dense cores by tracking structures in a magnetohydrodynamic simulation of a star-forming cloud. We identify cores using the dendrogram algorithm and utilize machine learning techniques, including Neural Gas prototype learning and Fuzzy c-means clustering to analyse the density and velocity dispersion profiles of cores together with six bulk properties. We produce a 2-d visualization using a Uniform Manifold Approximation and Projection (UMAP), which facilitates the connection between physical properties and three partially-overlapping phases: i) unbound turbulent structures (Phase I), ii) coherent cores that have low turbulence (Phase II), and iii) bound cores, many of which become protostellar (Phase III). Within Phase II, we identify a population of long-lived coherent cores that reach a quasi-equilibrium state. Most prestellar cores form in Phase II and become protostellar after evolving into Phase III. Due to the turbulent cloud environment, the initial core properties do not uniquely predict the eventual evolution, i.e. core evolution is stochastic, and cores follow no one evolutionary path. The phase lifetimes are 1.0 ± 0.1 × 105 yr, 1.3 ± 0.2 × 105 yr, and 1.8 ± 0.3 × 105 yr for Phase I, II, and III, respectively. We compare our results to NH3 observations of dense cores. Known coherent cores predominantly map into Phasemore »II, while most turbulent pressure-confined cores map to Phase I or III. We predict that a significant fraction of observed starless cores have unresolved coherent regions and that ≳20 per cent of observed starless cores will not form stars. Measurements of core radial profiles in addition to the usual bulk properties will enable more accurate predictions of core evolution.« less

Most observed stars are part of a multiple star system, but the formation of such systems and the role of environment and various physical processes is still poorly understood. We present a suite of radiation-magnetohydrodynamic simulations of star-forming molecular clouds from the STARFORGE project that include stellar feedback with varied initial surface density, magnetic fields, level of turbulence, metallicity, interstellar radiation field, simulation geometry and turbulent driving. In our fiducial cloud, the raw simulation data reproduces the observed multiplicity fractions for Solar-type and higher mass stars, similar to previous works. However, after correcting for observational incompleteness the simulation underpredicts these values. The discrepancy is likely due to the lack of disc fragmentation, as the simulation only resolves multiples that form either through capture or core fragmentation. The raw mass distribution of companions is consistent with randomly drawing from the initial mass function for the companions of $\gt 1\, \mathrm{M}_{\rm \odot }$ stars. However, accounting for observational incompleteness produces a flatter distribution similar to observations. We show that stellar multiplicity changes as the cloud evolves and anticorrelates with stellar density. This relationship also explains most multiplicity variations between runs, i.e. variations in the initial conditions that increase stellar density (increasedmore »surface density, reduced turbulence) also act to decrease multiplicity. While other parameters, such as metallicity, interstellar radiation, and geometry significantly affect the star formation history or the IMF, varying them produces no clear trend in stellar multiplicity properties.

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One of the key mysteries of star formation is the origin of the stellar initial mass function (IMF). The IMF is observed to be nearly universal in the Milky Way and its satellites, and significant variations are only inferred in extreme environments, such as the cores of massive elliptical galaxies and the Central Molecular Zone. In this work, we present simulations from the STARFORGE project that are the first cloud-scale radiation-magnetohydrodynamic simulations that follow individual stars and include all relevant physical processes. The simulations include detailed gas thermodynamics, as well as stellar feedback in the form of protostellar jets, stellar radiation, winds, and supernovae. In this work, we focus on how stellar radiation, winds, and supernovae impact star-forming clouds. Radiative feedback plays a major role in quenching star formation and disrupting the cloud; however, the IMF peak is predominantly set by protostellar jet physics. We find that the effect of stellar winds is minor, and supernovae ‘occur too late’ to affect the IMF or quench star formation. We also investigate the effects of initial conditions on the IMF. We find that the IMF is insensitive to the initial turbulence, cloud mass, and cloud surface density, even though these parametersmore »significantly shape the star formation history of the cloud, including the final star formation efficiency. Meanwhile, the characteristic stellar mass depends weakly on metallicity and the interstellar radiation field, which essentially set the average gas temperature. Finally, while turbulent driving and the level of magnetization strongly influence the star formation history, they only influence the high-mass slope of the IMF.

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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.

Stars form in dense, clustered environments, where feedback from newly formed stars eventually ejects the gas, terminating star formation and leaving behind one or more star clusters. Using the STARFORGE simulations, it is possible to simulate this process in its entirety within a molecular cloud, while explicitly evolving the gas radiation and magnetic fields and following the formation of individual, low-mass stars. We find that individual star-formation sites merge to form ever larger structures, while still accreting gas. Thus clusters are assembled through a series of mergers. During the cluster assembly process, a small fraction of stars are ejected from their clusters; we find no significant difference between the mass distribution of the ejected stellar population and that of stars inside clusters. The star-formation sites that are the building blocks of clusters start out mass segregated with one or a few massive stars at their centre. As they merge the newly formed clusters maintain this feature, causing them to have mass-segregated substructures without themselves being centrally condensed. The merged clusters relax to a centrally condensed mass-segregated configuration through dynamical interactions between their members, but this process does not finish before feedback expels the remaining gas from the cluster. Inmore »the simulated runs, the gas-free clusters then become unbound and breakup. We find that turbulent driving and a periodic cloud geometry can significantly reduce clustering and prevent gas expulsion. Meanwhile, the initial surface density and level of turbulence have little qualitative effect on cluster evolution, despite the significantly different star formation histories.

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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 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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