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Abstract The dynamics of star-forming gas can be affected by many physical processes, such as turbulence, gravity, supernova explosions, and magnetic fields. In this paper, we investigate several nearby star-forming regions (Orion, Upper Sco, Taurus, and Perseus) for kinematic imprints of these influences on the newly formed stars. Using Gaia DR3 astrometry and APOGEE DR17 radial velocities, we compute first-order velocity structure functions (VSFs) of young stars in galactic Cartesian coordinates in both 6D (3D positions and 3D velocities) and 4D (3D positions and each 1D velocity) to identify signatures of turbulence and anisotropic motion. We also construct 3D and 1D radial velocity profiles to identify coherent expansion trends, and compare stellar proper motions to plane-of-sky magnetic field orientations in Taurus and Perseus. We find that the VSFs are mildly anisotropic, with slightly different amplitudes, slopes, or features in different directions in several groups, but in general, they are all consistent with Larson’s Relation at intermediate length scales, especially in less compact groups. In several cases, the VSFs exhibit features suggestive of local energy injection from supernovae. Radial velocity profiles reveal clear anisotropic expansion in multiple groups, with the most extreme cases corresponding to those with the most anisotropic VSFs. In Perseus, we find that the motions of young stars are preferentially perpendicular to the local magnetic field. We find multiple, overlapping causes in each group for the observed kinematics. Our findings support that young stars remember more than just the turbulent state of their natal clouds. 

Abstract Accurately quantifying the impact of radiation feedback in star formation is challenging. To address this complex problem, we employ deep-learning techniques known as denoising diffusion probabilistic models (DDPMs) to predict the interstellar radiation field (ISRF) strength based on three-band dust emission at 4.5, 24, and 250μm. We adopt magnetohydrodynamic simulations from the STARFORGE project that model star formation and giant molecular cloud (GMC) evolution. We generate synthetic dust emission maps matching observed spectral energy distributions in the Monoceros R2 (MonR2) GMC. We train DDPMs to estimate the ISRF using synthetic three-band dust emission. The dispersion between the predictions and true values is within a factor of 0.1 for the test set. We extended our assessment of the diffusion model to include new simulations with varying physical parameters. While there is a consistent offset observed in these out-of-distribution simulations, the model effectively constrains the relative intensity to within a factor of 2. Meanwhile, our analysis reveals a weak correlation between the ISRF solely derived from dust temperature and the actual ISRF. We apply our trained model to predict the ISRF in MonR2, revealing a correspondence between intense ISRF, bright sources, and high dust emission, confirming the model’s ability to capture ISRF variations. Our model robustly predicts radiation feedback distribution, even in complex, poorly constrained ISRF environments like those influenced by nearby star clusters. However, precise ISRF predictions require an accurate training data set mirroring the target molecular cloud’s unique physical conditions. 

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. 

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 convolutional 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. 

Abstract We present a Spitzer/Herschel focused survey of the Aquila molecular clouds ( d ∼ 436 pc) as part of the eHOPS (extension of the Herschel orion protostar survey, or HOPS, Out to 500 ParSecs) census of nearby protostars. For every source detected in the Herschel/PACS bands, the eHOPS-Aquila catalog contains 1–850 μ m SEDs assembled from the Two Micron All Sky Survey, Spitzer, Herschel, the Wide-field Infrared Survey Explorer, and James Clerk Maxwell Telescope/SCUBA-2 data. Using a newly developed set of criteria, we classify objects by their SEDs as protostars, pre-main-sequence stars with disks, and galaxies. A total of 172 protostars are found in Aquila, tightly concentrated in the molecular filaments that thread the clouds. Of these, 71 (42%) are Class 0 protostars, 54 (31%) are Class I protostars, 43 (25%) are flat-spectrum protostars, and four (2%) are Class II sources. Ten of the Class 0 protostars are young PACS bright red sources similar to those discovered in Orion. We compare the SEDs to a grid of radiative transfer models to constrain the luminosities, envelope densities, and envelope masses of the protostars. A comparison of the eHOPS-Aquila to the HOPS protostars in Orion finds that the protostellar luminosity functions in the two star-forming regions are statistically indistinguishable, the bolometric temperatures/envelope masses of eHOPS-Aquila protostars are shifted to cooler temperatures/higher masses, and the eHOPS-Aquila protostars do not show the decline in luminosity with evolution found in Orion. We briefly discuss whether these differences are due to biases between the samples, diverging star formation histories, or the influence of environment on protostellar evolution. 

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.