Distances to ~60 star-forming regions in Reipurth (2008, Star Formation Handbook, vols I and II) have been computed using stellar photometry and Gaia DR2 parallax measurements. Usually, several distance estimates are taken across each cloud.
For each sightline, the median distance (d50) is provided, plus the 16th and 84th percentiles on the distance probability distribution function. There is an additional systematic uncertainty, which is unknown but estimated to be ~5% in distance for clouds <1.5kpc, ~10% in distance for clouds >1.5kpc, and ~7% in distance for the southern clouds Lupus, Chamaeleon, and Corona Australis. These should be added in quadrature with the statistical uncertainties reported in the table. In addition to the distances, ancillary model parameters used in our fit are also included (e.g. the amount of foreground extinction "f"). See Section 3.2.1 and Section 3.2.2 in Zucker et al. (2019ApJ...879..125Z) for a complete description of model parameters.
We extract equidistant cuts perpendicular to the spine of the filament and fit a modified Plummer profile as well as a Gaussian to each of the cuts. The filament widths (deconvolved FWHM) range between 6500-7000 au (~0.03 pc) along the filaments. This equals ~2.0 times the radius of the flat inner region. We find an anti-correlation between the central density and this flattening radius, suggestive of contraction. Further, we also find a strong correlation between the power-law exponent at large radii and the flattening radius. We note that the measurements of these three parameters fall in a plane and derive their empirical relation. Our high-resolution observations provide direct constraints of the distribution of the dense gas within super-critical filaments showing pre- and protostellar activity.
Context. Star formation takes place in cold dense cores in molecular clouds. Earlier observations have found that dense cores exhibit subsonic non-thermal velocity dispersions. In contrast, CO observations show that the ambient large-scale cloud is warmer and has supersonic velocity dispersions.
Aims. We aim to study the ammonia (NH3) molecular line profiles with exquisite sensitivity towards the coherent cores in L1688 in order to study their kinematical properties in unprecedented detail.
Methods. We used NH3 (1,1) and (2,2) data from the first data release (DR1) in the Green Bank Ammonia Survey (GAS). We first smoothed the data to a larger beam of 1′ to obtain substantially more extended maps of velocity dispersion and kinetic temperature, compared to the DR1 maps. We then identified the coherent cores in the cloud and analysed the averaged line profiles towards the cores.
Results. For the first time, we detected a faint (mean NH3(1,1) peak brightness < 0.25 K in TMB), supersonic component towards all the coherent cores in L1688. We fitted two components, one broad and one narrow, and derived the kinetic temperature and velocity dispersion of each component. The broad components towards all cores have supersonic linewidths (ℳS ≥ 1). This component biases the estimate of the narrow dense core component’s velocity dispersion by ≈28% and the kinetic temperature by ≈10%, on average, as compared to the results from single-component fits.
Conclusions. Neglecting this ubiquitous presence of a broad component towards all coherent cores causes the typical single-component fit to overestimate the temperature and velocity dispersion. This affects the derived detailed physical structure and stability of the cores estimated from NH3 observations.