Spatial statistics in star-forming regions
Retter, B
Date: 19 July 2021
Publisher
University of Exeter
Degree Title
PhD in Astrophysics
Abstract
Observational studies of star formation reveal spatial distributions of Young Stellar Objects (YSOs) that are `snapshots' of an ongoing star formation process. Using methods from spatial statistics it is possible to test the likelihood that a given distribution process could produce the observed patterns of YSOs. I determine the ...
Observational studies of star formation reveal spatial distributions of Young Stellar Objects (YSOs) that are `snapshots' of an ongoing star formation process. Using methods from spatial statistics it is possible to test the likelihood that a given distribution process could produce the observed patterns of YSOs. I determine the sensitivity of the spatial statistical tests Diggle's G function (G), the `free-space' function (F), Ripley's K and O-ring for application to astrophysical data. To do this I applied each test to simulated data containing 2D Gaussian clusters projected on a random distribution of background stars. By varying the number of stars within the Gaussian cluster and the number of background stars I determined the ability of the tests to reject complete spatial randomness (CSR) with changing signal-to-noise. Ripley's K and O-ring were shown to be much more sensitive to Gaussian clusters than G and F. I then apply the O-ring test to determine if column density alone is sufficient to explain the locations of Class 0/I YSOs within Serpens South, Serpens Core, Ophiuchus, NGC1333 and IC348. Star formation is known to occur more readily where more raw materials are available, a relationship that is often expressed in the form of a 'Kennicutt--Schmidt' relation where the surface density of Young Stellar Objects (YSOs) is proportional to column density to some power, μ. Using the O-ring test as a summary statistic, confidence envelopes were produced for different values of μ from probability models made using the Herschel column density maps. The YSOs were tested against four distribution models: the best-estimate of μ for the region, μ = 0 (i.e. random) above a column density threshold and zero probability elsewhere, μ = 1, and the power-law that best represents the five regions as a collective, μ = 2.05 ± 0.20. Serpens South and NGC1333 rejected the μ = 2.05 model on small scales of ~ 0.15 pc which implies that small-scale interactions may be influencing their distribution. On scales above 0.15 pc, the positions of YSOs in all five regions can be well described using column density alone.
Doctoral Theses
Doctoral College
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