|
Turbulence is one of the key architects of interstellar medium (ISM) structure, and regulates many processes within galaxies, from star formation on au scales, to the mixing of metals on kpc scales. The way in which turbulence is driven and energy is injected into the ISM has a significant impact on these processes, as has been well-described by computational studies of, for example, star formation in controlled (magneto-)hydrodynamical simulations. From simulation work it has been shown that, for an isothermal, compressible gas, the volume density dispersion is proportional to the sonic Mach number. The constant of proportionality, b, is known as the turbulence driving parameter, and describes the ratio of solenoidal to compressive modes in the turbulent acceleration field of the gas. Theoretically, the turbulence driving parameter ranges from b = 1/3 (purely solenoidal) to b = 1 (purely compressive), with b = 0.38 characterising the natural mixture (1/3 compressive, 2/3 solenoidal) of the two driving modes. In simulations we can dictate the value of b and observe its influence. But what about in reverse? Can we observe b and therefore infer how different physical processes in the ISM drive turbulence? The underlying challenge of this work is that turbulence is a distinctly three-dimensional processes, described using three-dimensional quantities. In observations we lack access to the third spatial dimension, and therefore careful assumptions need to be made in order to convert what we see on the plane of the sky to quantities that can diagnose turbulence. In this talk I will discuss a collection of works in which I have developed a robust set of tools to extract turbulence characteristics from observations of primarily HI emission, focusing on recovering the turbulence driving parameter. I will present our findings from three studies carried out in different ISM environments and discuss their implications in the context of the physical driving processes present in those environments. |
|