Sutra trains a U-Net on the union of DisPerSE and getsf skeletons to predict filament crest-likelihood maps and then filters and characterizes them with beam-scale Plummer fits.
Comparison of Herschel and ArT\'eMiS observations of massive filaments
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abstract
Context: OMC-3 in the Orion A Cloud is a nearby, high-mass star-forming region, and therefore ideal to study massive filaments in detail. Aims: We analyze how the inclusion of higher-resolution data changes the estimates of the filament properties and test the robustness of filament fitting routines. Methods. ArT\'eMiS and Herschel data are combined to create high-resolution images. Column densities and temperatures are estimated with modified blackbody fitting. The nearby OMC-3 cloud is compared to the more distant G202 and G17 clouds. We compare the OMC-3 cloud as it appears at Herschel and ArT\'eMiS resolution. Results. Column densities of dense clumps in OMC-3 are higher in combined ArT\'eMiS and Herschel data (FWHM 8.5"), when compared to Herschel-only data (FWHM 20"). Estimated filament widths are smaller in the combined maps, and also show signs of further fragmentation when observed with the ArT\'eMiS resolution. In the analysis of Herschel data the estimated filament widths are correlated with the distance of the field. Conclusions. Median filament FWHM in OMC-3 at higher resolution is 0.05 pc, but 0.1 pc with the Herschel resolution, 0.3 pc in G202 and 1.0 pc in G17, also at the Herschel resolution. It is unclear what causes the steep relation between distance and filament FWHM, but likely reasons include the effect of the limited telescope resolution combined with existing hierarchical structure, and convolution of large-scale background structures within the ISM. Estimates of the asymptotic power-law index of the filament profile function p is high. When fit with the Plummer function, the individual parameters of the profile function are degenerate, while the FWHM is better constrained. OMC-3 shows negative kurtosis, and all but OMC-3 at the Herschel resolution some asymmetry.
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Sutra : An integrated framework for identification and characterization of filaments in the interstellar medium
Sutra trains a U-Net on the union of DisPerSE and getsf skeletons to predict filament crest-likelihood maps and then filters and characterizes them with beam-scale Plummer fits.