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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 Phase 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. 

Filamentary structures have been found nearly ubiquitously in molecular clouds and yet their formation and evolution is still poorly understood. We examine a segment of Taurus Molecular Cloud 1 (TMC-1) that appears as a single, narrow filament in continuum emission from dust. We use the Regularized Optimization for Hyper-Spectral Analysis (ROHSA), a Gaussian decomposition algorithm that enforces spatial coherence when fitting multiple velocity components simultaneously over a data cube. We analyse HC5N (9–8) line emission as part of the Green Bank Ammonia Survey and identify three velocity-coherent components with ROHSA. The two brightest components extend the length of the filament, while the third component is fainter and clumpier. The brightest component has a prominent transverse velocity gradient of 2.7 ± 0.1 km s−1 pc−1 that we show to be indicative of gravitationally induced inflow. In the second component, we identify regularly spaced emission peaks along its length. We show that the local minima between pairs of adjacent HC5N peaks line up closely with submillimetre continuum emission peaks, which we argue is evidence for fragmentation along the spine of TMC-1. While coherent velocity components have been described as separate physical structures in other star-forming filaments, we argue that the two bright components identified in HC5N emission in TMC-1 are tracing two layers in one filament: a lower density outer layer whose material is flowing under gravity towards the higher density inner layer of the filament.

 

Abstract Spectral lines of ammonia, NH 3 , are useful probes of the physical conditions in dense molecular cloud cores. In addition to advantages in spectroscopy, ammonia has also been suggested to be resistant to freezing onto grain surfaces, which should make it a superior tool for studying the interior parts of cold, dense cores. Here we present high-resolution NH 3 observations with the Very Large Array and Green Bank Telescope toward a prestellar core. These observations show an outer region with a fractional NH 3 abundance of X (NH 3 ) = (1.975 ± 0.005) × 10 −8 (±10% systematic), but it also reveals that, after all, the X (NH 3 ) starts to decrease above a H 2 column density of ≈2.6 × 10 22 cm −2 . We derive a density model for the core and find that the break point in the fractional abundance occurs at the density n (H 2 ) ∼ 2 × 10 5 cm −3 , and beyond this point the fractional abundance decreases with increasing density, following the power law n −1.1 . This power-law behavior is well reproduced by chemical models where adsorption onto grains dominates the removal of ammonia and related species from the gas at high densities. We suggest that the break-point density changes from core to core depending on the temperature and the grain properties, but that the depletion power law is anyway likely to be close to n −1 owing to the dominance of accretion in the central parts of starless cores. 

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. 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.