Compiling data from the literature, we found that the gas thermal pressure increases with the intensity of the UV radiation field given by , following a trend in line with recent simulations of the photoevaporation of illuminated edges of molecular clouds. This relation can help rationalising the analysis of high-J CO emission in massive star formation and provides an observational constraint for models that study stellar feedback on molecular clouds.
We present the first results from a new, high resolution, 12 CO(1-0), 13 CO(1-0), and C 18 O(1-0) molecular line survey of the Orion A cloud, hereafter referred to as the CARMA-NRO Orion Survey. CARMA observations have been combined with single-dish data from the Nobeyama 45m telescope to provide extended images at about 0.01 pc resolution, with a dynamic range of approximately 1200 in spatial scale. Here we describe the practical details of the data combination in uv space, including flux scale matching, the conversion of single dish data to visibilities, and joint deconvolution of single dish and interferometric data. A ∆-variance analysis indicates that no artifacts are caused by combining data from the two instruments. Initial analysis of the data cubes, including moment maps, average spectra, channel maps, position-velocity diagrams, excitation temperature, column density, and line ratio maps provides evidence of complex and interesting structures such as filaments, bipolar outflows, shells, bubbles, and photo-eroded pillars. The implications for star formation processes are profound and follow-up scientific studies by the CARMA-NRO Orion team are now underway. We plan to make all the data products described here generally accessible; some are already available at [https://dataverse.harvard.edu/dataverse/CARMA-NRO-Orion].
Context. We present an initial overview of the filamentary structure in the Orion A molecular cloud utilizing a high angular and velocity resolution C18O(1–0) emission map that was recently produced as part of the CARMA-NRO Orion Survey. Aims. The main goal of this study is to build a credible method to study varying widths of filaments which has previously been linked to star formation in molecular clouds. Due to the diverse star forming activities taking place throughout its ~20 pc length, together with its proximity of 388 pc, the Orion A molecular cloud provides an excellent laboratory for such an experiment to be carried out with high resolution and high sensitivity. Methods. Using the widely-known structure identification algorithm, DisPerSE, on a three-dimensional (PPV) C18O cube, we identify 625 relatively short (the longest being 1.74 pc) filaments over the entire cloud. We studied the distribution of filament widths using FilChaP, a python package that we have developed and made publicly available. Results. We find that the filaments identified in a two square-degree PPV cube do not overlap spatially, except for the complex OMC-4 region that shows distinct velocity components along the line of sight. The filament widths vary between 0.02 and 0.3 pc depending on the amount of substructure that a filament possesses. The more substructure a filament has, the larger is its width. We also find that despite this variation, the filament width shows no anticorrelation with the central column density which is in agreement with previous Herschel observations.
Context. Models of photon-dominated regions (PDRs) still fail to fully reproduce some of the observed properties. In particular they do not reproduce the combination of the intensities of different PDR cooling lines together with the chemical stratification, as observed for example for the Orion Bar PDR. Aims. We aim to construct a numerical PDR model, KOSMA-τ 3D, to simulate full spectral cubes of line emission from arbitrary PDRs in three dimensions (3D). The model will reproduce the intensity of the main cooling lines from the Orion Bar PDR and the observed layered structure of the different transitions. Methods. We built up a 3D compound, made of voxels (3D pixels) that contain a discrete mass distribution of spherical "clumpy" structures, approximating the fractal ISM. To analyse each individual clump the new code was combined with the KOSMA-τ PDR model. Probabilistic algorithms were used to calculate the local FUV flux for each voxel as well as the voxel-averaged line emissivities and optical depths, based on the properties of the individual clumps. Finally, the computation of the radiative transfer through the compound provided full spectral cubes. To test the new model we tried to simulate the structure of the Orion Bar PDR and compared the results to observations from HIFI/Herschel and from the Caltech Submillimetre Observatory (CSO). In this context new Herschel data from the HEXOS guaranteed-time key program is presented. Results. Our model is able to reproduce the line-integrated intensities within a factor of 2.5 and the observed stratification pattern within 0.016 pc for the [Cii] 158 µm and different 12/13 CO and HCO + transitions, based on the representation of the Orion Bar PDR by a clumpy edge-on cavity wall. In the cavity wall, a large fraction of the total mass needs to be contained in clumps. The mass of the interclump medium is constrained by the FUV penetration. Furthermore, the stratification profile cannot be reproduced by a model that has the same amount of clump and interclump mass in each voxel; dense clumps need to be removed from the PDR surface.Article published by EDP Sciences A2, page 1 of 32 A&A 598, A2 (2017)
Context. Probability distribution functions (PDFs) of column densities are an established tool to characterize the evolutionary state of interstellar clouds. Aims. Using simulations, we show to what degree their determination is affected by noise, line-of-sight contamination, field selection, and the incomplete sampling in interferometric measurements. Methods. We solve the integrals that describe the convolution of a cloud PDF with contaminating sources such as noise and line-ofsight emission, and study the impact of missing information on the measured column density PDF. In this way we can quantify the effect of the different processes and propose ways to correct for their impact to recover the intrinsic PDF of the observed cloud. Results. The effect of observational noise can be easily estimated and corrected for if the root mean square (rms) of the noise is known. For σ noise values below 40% of the typical cloud column density, N peak , this involves almost no degradation in the accuracy of the PDF parameters. For higher noise levels and narrow cloud PDFs the width of the PDF becomes increasingly uncertain. A contamination by turbulent foreground or background clouds can be removed as a constant shield if the peak of the contamination PDF falls at a lower column or is narrower than that of the observed cloud. Uncertainties in cloud boundary definition mainly affect the low-column density part of the PDF and the mean density. As long as more than 50% of a cloud is covered, the impact on the PDF parameters is negligible. In contrast, the incomplete sampling of the uv-plane in interferometric observations leads to uncorrectable PDF distortions in the maps produced. An extension of the capabilities of the Atacama Large Millimeter Array (ALMA) would allow us to recover the high-column density tail of the PDF, but we found no way to measure the intermediate-and low-column density part of the underlying cloud PDF in interferometric observations.
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