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The width of Herschel filaments varies with distance

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arxiv 2111.08125 v3 pith:UYFPN3YF submitted 2021-11-15 astro-ph.GA

classification astro-ph.GA
keywords cloudswidthwidthsdistancefilamentfilamentsherschelmolecular
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Context: Filamentary structures in nearby molecular clouds have been found to exhibit a characteristic width of 0.1 pc, as observed in dust emission. Understanding the origin of this universal width has become a topic of central importance in the study of molecular cloud structure and the early stages of star formation. Aims: We investigate how the recovered widths of filaments depend on the distance from the observer, by using previously published results from the Herschel Gould Belt Survey. Methods: We obtained updated estimates on the distances to nearby molecular clouds observed with Herschel by using recent results based on 3D dust extinction mapping and Gaia. We examined the widths of filaments from individual clouds separately, as opposed to treating them as a single population. We used these per-cloud filament widths to search for signs of variation amongst the clouds of the previously published study. Results: We find a significant dependence of the mean per-cloud filament width with distance. The distribution of mean filament widths for nearby clouds is incompatible with that of farther away clouds. The mean per-cloud widths scale with distance approximately as 4--5 times the beam size. We examine the effects of resolution by performing a convergence study of a filament profile in the Herschel image of the Taurus Molecular Cloud. We find that resolution can severely affect the shapes of radial profiles over the observed range of distances. Conclusions: We conclude that the data are inconsistent with 0.1 pc being the universal characteristic width of filaments.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 44 citations worldwide. Full citation record

  1. Sutra : An integrated framework for identification and characterization of filaments in the interstellar medium

    astro-ph.GA 2026-07 conditional novelty 5.0 of 10

    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.

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