The Physics of Cloud-scale Star Formation and Feedback Across Cosmic Time

Alexander Philip Stuart Hygate
2020
Stars are an important visible and massive constituent of galaxies. They form out of cool, dense molecular gas regions known as molecular clouds and in turn impact this gas by emitting energy and mass known as "stellar feedback". Therefore, understanding the formation of stars and the feedback they generate is crucial for understanding galaxy formation. As a result of modern telescope facilities, high sensitivity, high resolution (cloud-scale) imaging of molecular gas is becoming available in
more » ... increasing number of galaxies. Analysis of this data with matched resolution observations of recently-formed, massive stars allows the characterisation of the star formation process on the cloud scale. The "uncertainty principle for star formation" is a statistical method for measuring the relative duration and spatial distribution of evolutionary phases of the star formation process. When applied to observational images that trace molecular clouds and regions of young stars, the method measures the duration of molecular cloud lifetimes, the timescale of their destruction by stellar feedback and the mean separation length between star forming regions. In this thesis, I investigate the physics of star formation and feedback on the cloud scale and present contributions to the development of methods for this analysis. First, I assess the impact of noise, astrometric offsets and diffuse emission on measurements made with the "uncertainty principle for star formation". I present a physically motivated method for separating emission from compact structures and diffuse extended structure in an image. The method separates diffuse and compact emission via filtering in Fourier space, with a filter defined by the mean separation length between star forming regions. This method enables the determination of the molecular cloud lifecycle and the mean separation between star forming regions with the "uncertainty principle for star formation" in data containing a diffuse background component. Second, I present the application of the "uncertainty principle for star formation" to determine the lifecycles of molecular clouds in the nearby flocculent galaxy M33. These measurements indicate that clouds in M33 have lifetimes approximately once or twice the timescale for their collapse due to gravitational freefall. Subsequently clouds are dispersed by stellar feedback over a timescale that could allow the earliest supernovae to explode whilst still embedded in their natal clouds. Third, I present the decomposition of tracer images of the molecular and ionised gas in nine nearby galaxies into compact and diffuse components and thus determine the fraction of emission coming from these components. I then present a correlation analysis between these emission fractions and a number of parameters characterising the galaxies in the sample. Last, I summarise the work of the thesis and present some future prospects for extending analyses such as the work presented in this thesis to other galactic environments in the Nearby Universe and further out into cosmic history.
doi:10.11588/heidok.00027948 fatcat:4ddjjovhtzbotokof2uujbxmcy