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Star Formation

Star formation occurs in Giant Molecular Clouds (GMCs) within galaxies. These star forming clouds are turbulent and are threaded by magnetic fields. Since these clouds are molecular in nature, they are not that easy to study observationally. The presence of molecular hydrogen and dust block our views of stellar birth by absorbing all the nascent starlight. These stellar birthplaces can be described as fluids, and we can use numerical simulations to answer the questions we can't find answers to using observations. However, being turbulent and magnetised fluids, along with having 'feedback' in the form of protostellar jets and outflows, makes things a lot harder. I perform numerical simulations of star forming regions on supercomputers to study how stars form in these incredibly complex regions. A central theme of my research is looking at the interplay between self-gravity, turbulence and feedback from protostars.

In a recent work with Prof. Mark Krumholz and Prof. Christoph Federrath , I looked at star formation thresholds in observations. Most gas in giant molecular clouds is relatively low-density and forms star inefficiently, converting only a small fraction of its mass to stars per dynamical time. However, star formation models generally predict the existence of a threshold density above which the process is efficient and most mass collapses to stars on a dynamical timescale. A number of authors have proposed observational techniques to search for a threshold density above which star formation is efficient, but it is unclear which of these techniques, if any, are reliable. In this work we used detailed simulations of turbulent, magnetised star-forming clouds, including stellar radiation and outflow feedback, to investigate whether it is possible to recover star formation thresholds using current observational techniques. Using mock observations of the simulations at realistic resolutions, we show that plots of projected star formation efficiency per free-fall time εff can detect the presence of a threshold, but that the resolutions typical of current dust emission or absorption surveys are insufficient to determine its value. In contrast, proposed alternative diagnostics based on a change in the slope of the gas surface density versus star formation rate surface density (Kennicutt-Schmidt relation) or on the correlation between young stellar object counts and gas mass as a function of density are ineffective at detecting thresholds even when they are present. The signatures in these diagnostics is sometimes taken as indicative of a threshold in observations, which we generally reproduce in our mock observations, do not prove to correspond to real physical features in the 3D gas distribution.
The density PDF in turbulent fluids takes the form of a lognormal distribution. In the presence of self-gravity, we get a power-law tail in the density PDF. Along with Prof. Mark Krumholz and Prof. Christoph Federrath , Prof. Chris Matzner and I are looking at how self-gravity and turbulence affect the density PDF and what do different sections of the density PDF correspond to.
Along with Dr. Mike Grudic , Dr. David Guszejnov and collaborators, Prof. Norman Murray and I are looking at star formation in the FIRE simulations . We're interested in what typical GMC lifetimes are and how the lifetimes of GMCs affect their efficiencies and what properties of the star forming clouds matter for star formation.

Reionization and Cosmology

In a recent work with Prof. Benedetta Ciardi and collaborators, I looked at the hyperfine transition of 3He+ as a probe of the high-z universe. The hyperfine transition of 3He+ at 3.5 cm has been thought as a probe of the high-z IGM since it offers a unique insight into the evolution of the helium component of the gas, as well as potentially give an independent constraint on the 21 cm signal from neutral hydrogen. In this paper, we use radiative transfer simulations of reionization driven by sources such as stars, X-ray binaries, accreting black holes and shock heated interstellar medium, and simulations of a high-z quasar to characterize the signal and analyze its prospects of detection. We find that the peak of the signal lies in the range ∼ 1 − 50 μK for both environments, but while around the quasar it is always inemission, in the case of cosmic reionization a brief period of absorption is expected. As the evolution of HeII is determined by stars, we find that it is not possible to distinguish reionization histories driven by more energetic sources. On the other hand, while a bright QSO produces a signal in 21 cm that is very similar to the one from a large collection of galaxies, its signature in 3.5 cm is very peculiar and could be a powerful probe to identify the presence of the QSO. We analyze the prospects of the signal’s detectability using SKA1-mid as our reference telescope. We find that the noise power spectrum dominates over the power spectrum of the signal, although the S/N ratio can be appreciable when the wavenumber bin width and the survey volume are sufficiently large.