Developed CMD Plot Tool, a cross-platform standalone GUI application for plotting color-magnitude diagrams using Agile SDLC and object-oriented programming in Python.
Tracing the Conversion of Gas into Stars in Young Massive Cluster Progenitors
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abstract
Whilst young massive clusters (YMCs; $M$ $\gtrsim$ 10$^{4}$ M$_{\odot}$, age $\lesssim$ 100 Myr) have been identified in significant numbers, their progenitor gas clouds have eluded detection. Recently, four extreme molecular clouds residing within 200 pc of the Galactic centre have been identified as having the properties thought necessary to form YMCs. Here we utilise far-IR continuum data from the Herschel Infrared Galactic Plane Survey (HiGAL) and millimetre spectral line data from the Millimetre Astronomy Legacy Team 90 GHz Survey (MALT90) to determine their global physical and kinematic structure. We derive their masses, dust temperatures and radii and use virial analysis to conclude that they are all likely gravitationally bound -- confirming that they are likely YMC progenitors. We then compare the density profiles of these clouds to those of the gas and stellar components of the Sagittarius B2 Main and North proto-clusters and the stellar distribution of the Arches YMC. We find that even in these clouds -- the most massive and dense quiescent clouds in the Galaxy -- the gas is not compact enough to form an Arches-like ($M$ = 2x10$^{4}$ M$_{\odot}$, R$_{eff}$ = 0.4 pc) stellar distribution. Further dynamical processes would be required to condense the resultant population, indicating that the mass becomes more centrally concentrated as the (proto)-cluster evolves. These results suggest that YMC formation may proceed hierarchically rather than through monolithic collapse.
fields
astro-ph.IM 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Using the Agile software development lifecycle to develop a standalone application for generating colour magnitude diagrams
Developed CMD Plot Tool, a cross-platform standalone GUI application for plotting color-magnitude diagrams using Agile SDLC and object-oriented programming in Python.