Catalogue of High Protostellar Surface Density Regions in Nearby Embedded Clusters

Abstract

We analyze high-quality stellar catalogs for 24 young and nearby (within 1 kpc) embedded clusters and present a catalogue of 32 groups which have a high concentration of protostars. The median effective radius of these groups is 0.17 pc. The median protostellar and pre-main sequence star surface densities are 46 M_{\odot} pc^{-2} and 11 M_{\odot} pc^{-2}, respectively. We estimate the age of these groups using a model of constant birthrate and random accretion stopping and find a median value of 0.25 Myr. Some groups in Aquila and Serpens, Corona Australia and Ophichus L1688 show high protostellar surface density and high molecular gas surface density, which seem to be undergoing vigorous star formation. These groups provide an excellent opportunity to study initial conditions of clustered star formation. Comparison of protostellar and pre-main-sequence stellar surface densities reveal continuous low-mass star formation of these groups over several Myr in some clouds. For groups with typical protostellar separations of less than 0.4 pc, we find that these separations agree well with the thermal Jeans fragmentation scale. On the other hand, for groups with typical protostellar separations larger than 0.4 pc, these separations are always larger than the associated Jeans length.

29 pages, 24 figures, to be published in ApJ

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Cited by in corpus (7)

• Global Hierarchical Collapse In Molecular Clouds. Towards a Comprehensive Scenario
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• Star-Gas Surface Density Correlations in Twelve Nearby Molecular Clouds I: Data Collection and Star-Sampled Analysis
• IRAS23385+6053: An embedded massive cluster in the making
• Protostellar Evolution in Serpens Main: Possible Origin of Disk-Size Diversity
• Deep Near-Infrared Survey Toward the W40 and Serpens South Region in Aquila Rift: A Comprehensive Catalog of Young Stellar Objects
• Hierarchical Structure of YSO Clusters in the W40 and Serpens South Region: Group Extraction and Comparison with Fractal Clusters