Star formation in the solar neighbourhood

Peer reviewe

Fast fitting of spectral lines with Gaussian and hyperfine structure models

The fitting of spectral lines is a common step in the analysis of line observations and simulations. However, the observational noise, the presence of multiple velocity components, and potentially large data sets make it a non-trivial task. We present a new computer program Spectrum Iterative Fitter (SPIF) for the fitting of spectra with Gaussians or with hyperfine line profiles. The aim is to show the computational efficiency of the program and to use it to examine the general accuracy of approximating spectra with simple models. We describe the implementation of the program. To characterise its performance, we examined spectra with isolated Gaussian components or a hyperfine structure, also using synthetic observations from numerical simulations of interstellar clouds. We examined the search for the globally optimal fit and the accuracy to which single-velocity-component and multi-component fits recover true values for parameters such as line areas, velocity dispersion, and optical depth. The program is shown to be fast, with fits of single Gaussian components reaching on graphics processing units speeds approaching one million spectra per second. This also makes it feasible to use Monte Carlo simulations or Markov chain Monte Carlo calculations for the error estimation. However, in the case of hyperfine structure lines, degeneracies affect the parameter estimation and can complicate the derivation of the error estimates. The use of many random initial values makes the fits more robust, both for locating the global $\chi^2$ minimum and for the selection of the optimal number of velocity components.Comment: Accepted for publication in A&

Super-Sonic Turbulence in the Perseus Molecular Cloud

We compare the statistical properties of J=1-0 13CO spectra observed in the Perseus Molecular Cloud with synthetic J=1-0 13CO spectra, computed solving the non-LTE radiative transfer problem for a model cloud obtained as solutions of the three dimensional magneto-hydrodynamic (MHD) equations. The model cloud is a randomly forced super-Alfvenic and highly super-sonic turbulent isothermal flow. The purpose of the present work is to test if idealized turbulent flows, without self-gravity, stellar radiation, stellar outflows, or any other effect of star formation, are inconsistent or not with statistical properties of star forming molecular clouds. We present several statistical results that demonstrate remarkable similarity between real data and the synthetic cloud. Statistical properties of molecular clouds like Perseus are appropriately described by random super-sonic and super-Alfvenic MHD flows. Although the description of gravity and stellar radiation are essential to understand the formation of single protostars and the effects of star formation in the cloud dynamics, the overall description of the cloud and of the initial conditions for star formation can apparently be provided on intermediate scales without accounting for gravity, stellar radiation, and a detailed modeling of stellar outflows. We also show that the relation between equivalent line width and integrated antenna temperature indicates the presence of a relatively strong magnetic field in the core B1, in agreement with Zeeman splitting measurements.Comment: 20 pages, 8 figures included, ApJ (in press

SOC program for dust continuum radiative transfer

Context. Thermal dust emission carries information on physical conditions and dust properties in many astronomical sources. Because observations represent a sum of emission along the line of sight, their interpretation often requires radiative transfer (RT) modelling. Aims. We describe a new RT program, SOC, for computations of dust emission, and examine its performance in simulations of interstellar clouds with external and internal heating. Methods. SOC implements the Monte Carlo RT method as a parallel program for shared-memory computers. It can be used to study dust extinction, scattering, and emission. We tested SOC with realistic cloud models and examined the convergence and noise of the dust-temperature estimates and of the resulting surface-brightness maps. Results. SOC has been demonstrated to produce accurate estimates for dust scattering and for thermal dust emission. It performs well with both CPUs and GPUs, the latter providing a speed-up of processing time by up to an order of magnitude. In the test cases, accelerated lambda iterations (ALIs) improved the convergence rates but was also sensitive to Monte Carlo noise. Run-time refinement of the hierarchical-grid models did not help in reducing the run times required for a given accuracy of solution. The use of a reference field, without ALI, works more robustly, and also allows the run time to be optimised if the number of photon packages is increased only as the iterations progress. Conclusions. The use of GPUs in RT computations should be investigated further.Peer reviewe

Can we trace very cold dust from its emission alone ?

Context. Dust is a good tracer of cold dark clouds but its column density is difficult to quantify. Aims. We want to check whether the far-infrared and submillimeter high-resolution data from Herschel SPIRE and PACS cameras combined with ground-based telescope bolometers allow us to retrieve the whole dust content of cold dark clouds. Methods. We compare far-infrared and submillimeter emission across L183 to the 8 $\mu$m absorption map from Spitzer data and fit modified blackbody functions towards three different positions. Results. We find that none of the Herschel SPIRE channels follow the cold dust profile seen in absorption. Even the ground-based submillimeter telescope observations, although more closely following the absorption profile, cannot help to characterize the cold dust without external information such as the dust column density itself. The difference in dust opacity can reach up to a factor of 3 in prestellar cores of high extinction. Conclusions. In dark clouds, the amount of very cold dust cannot be measured from its emission alone. In particular, studies of dark clouds based only on Herschel data can miss a large fraction of the dust content. This has an impact on core and filament density profiles, masse and stability estimates.Comment: Letter to A&A (accepted for publication). must be viewed with ACROBAT READER for full enhancement. Otherwise, check images in Appendix

Molecular cloud cores with high deuterium fractions : nobeyama mapping survey

Publisher Copyright: © 2021. The American Astronomical Society.We present the results of on-the-fly mapping observations of 44 fields containing 107 SCUBA-2 cores in the emission lines of molecules N2H+, HC3N, and CCS at 82-94 GHz using the Nobeyama 45 m telescope. This study aimed at investigating the physical properties of cores that show high deuterium fractions and might be close to the onset of star formation. We found that the distributions of the N2H+ and HC3N line emissions are approximately similar to the distribution of the 850 mu m dust continuum emission, whereas the CCS line emission is often undetected or is distributed in a clumpy structure surrounding the peak position of the 850 mu m dust continuum emission. Occasionally (12%), we observe CCS emission, which is an early-type gas tracer toward the young stellar object, probably due to local high excitation. Evolution toward star formation does not immediately affect the nonthermal velocity dispersion.Peer reviewe