"A Nine-Member Protostellar System Forming via Filament Fragmentation and a Search for Streamers in Nine High-Mass Star Forming Regions"

Abstract:

Massive stars (> 8 Msun) are likely found in binaries or higher order multiples throughout their lives; however, due to observational challenges, the relative importance of the formation mechanisms giving rise to this multiplicity are not well constrained. The youngest multiple systems, whose system parameters best constrain theoretical models, are the most deeply embedded, and in the high-mass regime only a few examples of young multiples -that have not yet developed ultracompact/hypercompact HII regions or bright IR emission- have been identified. Using high angular resolution (~350 AU) ALMA observations taken as part of the The Complex Chemistry in hot Cores with ALMA (CoCCoA) survey I will present a case study of multiplicity in the massive star forming environment NGC 6334-43. We identify nine protostellar and prestellar sources that reside within a single filamentary structure, whose derived system parameters are consistent with a bound system in a simple stability analysis.

Streamers, high-aspect-ratio velocity-coherent structure of gas (and sometimes dust) that are falling towards a source, may play a crucial role in a variety of star formation processes. In contrast to numerous identifications towards low-mass sources, there is a comparatively sparse sample of streamers in high-mass star-forming regions. We aim to expand this sample through a search for streamers in H13CO+ emission across nine high-mass star forming regions observed as part of the CoCCoA survey. I will present ongoing work to this end, where we have obtained reliable Vlsr measurements for ~55 sources by fitting synthetic spectra to their CH3CN emission and analysed the complex H13CO+ emission via Gaussian decomposition and subsequent clustering into position-position-velocity coherent structures. I will also show early results of fitting candidate streamers using an MCMC implementation of TIPSY.