No Arabic abstract
Magnetohydrodynamic (MHD) turbulence is a crucial component of the current paradigms of star formation, dynamo theory, particle transport, magnetic reconnection and evolution of structure in the interstellar medium (ISM) of galaxies. Despite the importance of turbulence to astrophysical fluids, a full theoretical framework based on solutions to the Navier-Stokes equations remains intractable. Observations provide only limited line-of-sight information on densities, temperatures, velocities and magnetic field strengths and therefore directly measuring turbulence in the ISM is challenging. A statistical approach has been of great utility in allowing comparisons of observations, simulations and analytic predictions. In this review article we address the growing importance of MHD turbulence in many fields of astrophysics and review statistical diagnostics for studying interstellar and interplanetary turbulence. In particular, we will review statistical diagnostics and machine learning algorithms that have been developed for observational data sets in order to obtain information about the turbulence cascade, fluid compressibility (sonic Mach number), and magnetization of fluid (Alfvenic Mach number). These techniques have often been tested on numerical simulations of MHD turbulence, which may include the creation of synthetic observations, and are often formulated on theoretical expectations for compressible magnetized turbulence. We stress the use of multiple techniques, as this can provide a more accurate indication of the turbulence parameters of interest. We conclude by describing several open-source tools for the astrophysical community to use when dealing with turbulence.
Turbulence is ubiquitous in the insterstellar medium and plays a major role in several processes such as the formation of dense structures and stars, the stability of molecular clouds, the amplification of magnetic fields, and the re-acceleration and diffusion of cosmic rays. Despite its importance, interstellar turbulence, alike turbulence in general, is far from being fully understood. In this review we present the basics of turbulence physics, focusing on the statistics of its structure and energy cascade. We explore the physics of compressible and incompressible turbulent flows, as well as magnetized cases. The most relevant observational techniques that provide quantitative insights of interstellar turbulence are also presented. We also discuss the main difficulties in developing a three-dimensional view of interstellar turbulence from these observations. Finally, we briefly present what could be the the main sources of turbulence in the interstellar medium.
Two major questions in galaxy evolution are how star-formation on small scales leads to global scaling laws and how galaxies acquire sufficient gas to sustain their star formation rates. HI observations with high angular resolution and with sensitivity to very low column densities are some of the important observational ingredients that are currently still missing. Answers to these questions are necessary for a correct interpretation of observations of galaxy evolution in the high-redshift universe and will provide crucial input for the sub-grid physics in hydrodynamical simulations of galaxy evolutions. In this chapter we discuss the progress that will be made with the SKA using targeted observations of nearby individual disk and dwarf galaxies.
We investigate the clustering and dynamics of nano-sized particles (nano-dust) in high-resolution ($1024^3$) simulations of compressible isothermal hydrodynamic turbulence. It is well-established that large grains will decouple from a turbulent gas flow, while small grains will tend to trace the motion of the gas. We demonstrate that nano-sized grains may cluster in a turbulent flow (fractal small-scale clustering), which increases the local grain density by at least a factor of a few. In combination with the fact that nano-dust grains may be abundant in general, and the increased interaction rate due to turbulent motions, aggregation involving nano dust may have a rather high probability. Small-scale clustering will also affect extinction properties. As an example we present an extinction model based on silicates, graphite and metallic iron, assuming strong clustering of grain sizes in the nanometre range, could explain the extreme and rapidly varying ultraviolet extinction in the host of GRB 140506A.
Externally driven interstellar turbulence plays an important role in shaping the density structure in molecular clouds. Here we study the dynamical role of internally driven turbulence in a self-gravitating molecular cloud core. Depending on the initial conditions and evolutionary stages, we find that a self-gravitating core in the presence of gravity-driven turbulence can undergo constant, decelerated, and accelerated infall, and thus has various radial velocity profiles. In the gravity-dominated central region, a higher level of turbulence results in a lower infall velocity, a higher density, and a lower mass accretion rate. As an important implication of this study, efficient reconnection diffusion of magnetic fields against the gravitational drag naturally occurs due to the gravity-driven turbulence, without invoking externally driven turbulence.
Turbulence is ubiquitous in the interstellar medium (ISM) of the Milky Way and other spiral galaxies. The energy source for this turbulence has been much debated with many possible origins proposed. The universality of turbulence, its reported large-scale driving, and that it occurs also in starless molecular clouds, challenges models invoking any stellar source. A more general process is needed to explain the observations. In this work we study the role of galactic spiral arms. This is accomplished by means of three-dimensional hydrodynamical simulations which follow the dynamical evolution of interstellar diffuse clouds (100cm-3) interacting with the gravitational potential field of the spiral pattern. We find that the tidal effects of the arms potential on the cloud result in internal vorticity, fragmentation and hydrodynamical instabilities. The triggered turbulence result in large-scale driving, on sizes of the ISM inhomogeneities, i.e. as large as 100pc, and efficiencies in converting potential energy into turbulence in the range 10 to 25 percent per arm crossing. This efficiency is much higher than those found in previous models. The statistics of the turbulence in our simulations are strikingly similar to the observed power spectrum and Larson scaling relations of molecular clouds and the general ISM. The dependency found from different models indicate that the ISM turbulence is mainly related to local spiral arm properties, such as its mass density and width. This correlation seems in agreement with recent high angular resolution observations of spiral galaxies, e.g. M51 and M33.