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Abstract
Context.The spatial and dynamical structure of star-forming regions can offer insights into stellar formation patterns. The amount of data from current and upcoming surveys calls for robust and objective procedures for detecting structures in order to statistically analyse the various regions and compare them.Aims.We aim to provide the community with a tool capable of detecting, above random expectations, the small-scale significant structure in star-forming regions that could serve as an imprint of the stellar formation process. The tool makes use of the one-point correlation function to determine an appropriate length scale forϵand uses nearest-neighbour statistics to determine a minimum number of pointsNminfor the DBSCAN algorithm in the neighbourhood ofϵ.Methods.We implemented the procedure and applied it to synthetic star-forming regions of different nature and characteristics to obtain its applicability range. We also applied the method to observed star-forming regions to demonstrate its performance in realistic circumstances and to analyse its results.Results.The procedure successfully detects significant small-scale substructures in heterogeneous regions, fulfilling the goals it was designed for and providing very reliable structures. The analysis of regions close to complete spatial randomness (Q ∈ [0.7, 0.87]) shows that even when some structure is present and recovered, it is hardly distinguishable from spurious detection in homogeneous regions due to projection effects. Thus, any interpretation should be done with care. For concentrated regions, we detect a main structure surrounded by smaller ones, corresponding to the core plus some Poisson fluctuations around it. We argue that these structures do not correspond to the small compact regions we are looking for. In some realistic cases, a more complete hierarchical, multi-scale analysis would be needed to capture the complexity of the region.Conclusions.We carried out implementations of our procedure and devised a catalogue of the Nested Elementary STructures (NESTs) detected as a result in four star-forming regions (Taurus, IC 348, Upper Scorpius, and Carina). This catalogue is being made publicly available to the community. Implementations of the 3D versionsof the procedure, as well as up to 6D versions, including proper movements, are in progress and will be provided in a future work.
Highlights
While a number of related processes have already been well established, a coherent and detailed portrait of stellar formation is not yet complete
We aim to provide the community with a tool capable of detecting, above random expectations, the small-scale significant structure in star-forming regions that could serve as an imprint of the stellar formation process
The tool makes use of the one-point correlation function to determine an appropriate length scale for and uses nearest-neighbour statistics to determine a minimum number of points Nmin for the DBSCAN algorithm in the neighbourhood of
Summary
While a number of related processes have already been well established, a coherent and detailed portrait of stellar formation is not yet complete. Our current understanding is based on molecular clouds with intricate structures that undergo very complex fragmentation and where dense filamentary structures appear. These filaments, and their intersections, host dense molecular cores and facilitate star formation (see Robitaille et al 2019; Hacar et al 2017, and references therein). In such scenarios, star formation is not expected to occur in isolation, underlining the importance of taking into consideration the environmental effects that influence the whole process. The different effects that forming and young stellar objects can have on their environment ( if massive) suggests that the clustered environment of forming stars will have significant effects on a variety of observable phenomena, such as: high-mass star formation, protoplanetary disk survival, binary ratio, or the Hα cut-off observed in disc galaxies
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