Abstract
Modern multiwavelength observations of star-forming regions that reveal complex, highly structured molecular clouds require adequate extraction methods that provide both complete detection of the structures and their accurate measurements. The omnipresence of filamentary structures and their physical connection to prestellar cores make it necessary to use methods that are able to disentangle and extract both sources and filaments. It is fundamentally important to test all extraction methods on standard benchmarks to compare their detection and measurement qualities and fully understand their capabilities before their scientific applications. A recent publication described getsf, the new method for source and filament extraction that employs the separation of the structural components, a successor to getsources, getfilaments, and getimages (collectively referred to as getold). This new paper describes a detailed benchmarking of both getsf and getold using two multicomponent, multiwavelength benchmarks resembling the Herschel observations of the nearby star-forming regions. Each benchmark consists of simulated images at six Herschel wavelengths and one additional derived surface density image with a 13″ resolution. The structural components of the benchmark images include a background cloud, a dense filament, hundreds of starless and protostellar cores, and instrumental noise. Five variants of benchmark images of different complexity are derived from the two benchmarks and are used to perform the source and filament extractions with getsf and getold. A formalism for evaluating source detection and measurement qualities is presented, allowing quantitative comparisons of different extraction methods in terms of their completeness, reliability, and goodness, as well as the detection and measurement accuracies and the overall quality. A detailed analysis of the benchmarking results shows that getsf has better source and filament extraction qualities than getold and that the best choice of the images for source detection with getsf is the high-resolution surface density, alone or with the other available Herschel images. The benchmarks explored in this paper provide the standard tests for calibrating existing and future source- and filament-extraction methods to choose the best tool for astrophysical studies.
Highlights
Extraction methods are critically important research tools, interfacing the astronomical imaging observations with their analyses and physical interpretations
All structural components were added to each other, without any attempt to account for the physical picture that the star-forming cores are the integral parts of the filaments that, in turn, are the integral parts of the molecular clouds. This is unnecessary for a benchmark, because the existing extraction tools do not discriminate between the embedded structures and chance projections of the structural components along the line of sight
The quality evaluation system represented by Eqs. (2)–(6) is not unique and other formalisms might be devised and applied to the benchmark truth catalogs and the getsf and getold extraction catalogs found on the benchmarking page of the getsf website2
Summary
Extraction methods are critically important research tools, interfacing the astronomical imaging observations with their analyses and physical interpretations. Subsequent comparisons of the resulting extraction catalogs with the truth catalogs using a reasonable set of quality estimators would determine their detection and measurement qualities, inaccuracies, and biases It would be highly desirable, if various studies used the extraction tool that shows the best performance in benchmarks, to exclude any discrepancies caused by different methods. Instead of describing benchmarking results for an arbitrary selection of existing sourceextraction tools, this paper provides researchers in star formation with an extraction quality evaluation system and the sourceextraction results obtained with getsf and getold for five variants of the benchmarks with increasing complexity levels Such an approach enables researchers to benchmark any number of source-extraction tools of their choice and evaluate improved or newly developed methods in the future. {a|b} refers to a or b and {A|B}{a|b}c expands to A{a|b}c or B{a|b}c, as well as to Aac, Abc, Bac, or Bbc
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