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Context. When dust far-infrared spectral energy distributions (SEDs) are fitted with a single modified black body (MBB), the optical depths tend to be underestimated. This is caused by temperature variations, and fits with several temperature components could lead to smaller errors. Aims. We want to quantify the performance of the standard model of a single MBB in comparison with some multi-component models. We are interested in both the accuracy and computational cost. Methods. We examine some cloud models relevant for interstellar medium studies. Synthetic spectra are fitted with a single MBB, a sum of several MBBs, and a sum of fixed spectral templates, but keeping the dust opacity spectral index fixed. Results. When observations are used at their native resolution, the beam convolution becomes part of the fitting procedure. This increases the computational cost, but the analysis of large maps is still feasible with direct optimisation or even with Markov chain Monte Carlo methods. Compared to the single MBB fits, multi-component models can show significantly smaller systematic errors, at the cost of more statistical noise. The χ 2 values of the fits are not a good indicator of the accuracy of the τ estimates, due to the potentially dominant role of the model errors. The single-MBB model also remains a valid alternative if combined with empirical corrections to reduce its bias. Conclusions. It is technically feasible to fit multi-component models to maps of millions of pixels. However, the SED model and the priors need to be selected carefully, and the model errors can only be estimated by comparing alternative models.
Context. When dust far-infrared spectral energy distributions (SEDs) are fitted with a single modified black body (MBB), the optical depths tend to be underestimated. This is caused by temperature variations, and fits with several temperature components could lead to smaller errors. Aims. We want to quantify the performance of the standard model of a single MBB in comparison with some multi-component models. We are interested in both the accuracy and computational cost. Methods. We examine some cloud models relevant for interstellar medium studies. Synthetic spectra are fitted with a single MBB, a sum of several MBBs, and a sum of fixed spectral templates, but keeping the dust opacity spectral index fixed. Results. When observations are used at their native resolution, the beam convolution becomes part of the fitting procedure. This increases the computational cost, but the analysis of large maps is still feasible with direct optimisation or even with Markov chain Monte Carlo methods. Compared to the single MBB fits, multi-component models can show significantly smaller systematic errors, at the cost of more statistical noise. The χ 2 values of the fits are not a good indicator of the accuracy of the τ estimates, due to the potentially dominant role of the model errors. The single-MBB model also remains a valid alternative if combined with empirical corrections to reduce its bias. Conclusions. It is technically feasible to fit multi-component models to maps of millions of pixels. However, the SED model and the priors need to be selected carefully, and the model errors can only be estimated by comparing alternative models.
Context. Dust emission is an important tool in studies of star-forming clouds as a tracer of column density. This is done indirectly via the dust evolution that is connected to the history and physical conditions of the clouds. Aims. We examine the radiative transfer (RT) modelling of dust emission over an extended cloud region, using a filament in the Taurus molecular cloud as an example. We examine how well far-infrared (FIR) observations can be used to determine both the cloud and the dust properties. Methods. Using different assumptions on the cloud shape, radiation field, and dust properties, we fit RT models to Herschel observations of the Taurus filament. We made further comparisons with measurements of the near-infrared extinction. The models were used to examine the degeneracies between the different cloud parameters and the dust properties. Results. The results show a significant dependence on the assumed cloud structure and the spectral shape of the external radiation field. If these are constrained to the most likely values, the observations can be explained only if the dust FIR opacity has increased by a factor of 2–3 relative to the values in diffuse medium. However, a narrow range of FIR wavelengths provides only weak evidence of the spatial variations in dust, even in the models covering several square degrees of a molecular cloud. Conclusions. The analysis of FIR dust emission is affected by several sources of uncertainty. Further constraints are therefore needed from observations at shorter wavelengths, especially with respect to trends in dust evolution.
Recent molecular surveys have revealed the rich gas organization of sonic-like filaments at small scales (so-called fibers) in all types of environments prior to the formation of low- and high-mass stars. These fibers form at the end of the turbulent cascade and are identified as the fine substructure within the hierarchical nature of the gas in the interstellar medium (ISM). Isolated fibers provide the subsonic conditions for the formation of low-mass stars. This paper introduces the Emergence of high-mass stars in complex fiber networks (EMERGE) project, which investigates whether complex fiber arrangements (networks) can also explain the origin of high-mass stars and clusters. We analyzed the EMERGE Early ALMA Survey including seven star-forming regions in Orion (OMC-1,2,3, and 4 South, LDN 1641N, NGC 2023, and the Flame Nebula) that were homogeneously surveyed in three molecular lines (N$_2$H$^+$ J=1-0, HNC J=1-0, and HC$_3$N J=10-9) and in the 3mm continuum using a combination of interferometric ALMA mosaics and IRAM-30m single-dish (SD) maps, together with a series of Herschel Spitzer and WISE archival data. We also developed a systematic data reduction framework allowing the massive data processing of ALMA observations. We obtained independent continuum maps and spectral cubes for all our targets and molecular lines at different (SD and interferometric) resolutions, and we explored multiple data combination techniques. Based on our low-resolution (SD) observations (30 or sim 12\ 000 au), we describe the global properties of our sample, which covers a wide range of physical conditions, including low- (OMC-4 South and NGC 2023), intermediate (OMC-2, OMC-3, and LDN 1641N), and high-mass (OMC-1 and Flame Nebula) star-forming regions in different evolutionary stages. The comparison between our single-dish maps and ancillary YSO catalogs denotes N$_2$H$^+$ (1-0) as the best proxy for the dense, star-forming gas in our targets, which show a constant star formation efficiency and a fast time evolution of lesssim 1 Myr. While apparently clumpy and filamentary in our SD data, all targets show a much more complex fibrous substructure at the enhanced resolution of our combined ALMA+IRAM-30m maps (4 or sim 2\ 000 au). A large number of filamentary features at subparsec scales are clearly recognized in the high-density gas ($ $) that is traced by N$_2$H$^+$ (1-0) directly connected to the formation of individual protostars. Surprisingly, this complex gas organization appears to extend farther into the more diffuse gas ($ $) traced by HNC (1-0). This paper presents the EMERGE Early ALMA Survey, which includes a first data release of continuum maps and spectral products for this project that are to be analysed in future papers of this series. A first look at these results illustrates the need of advanced data combination techniques between high-resolution interferometric (ALMA) and high-sensitivity, low-resolution single-dish (IRAM-30m) datasets to investigate the intrinsic multiscale, gas structure of the ISM.
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