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Register a new userThe Effect of Supernovae on the Turbulence and Dispersal of Molecular Clouds
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While the importance of supernova feedback in galaxies is well established, its role on the scale of molecular clouds is still debated. In this work, we focus on the impact of supernovae on individual clouds, using a high-resolution magneto-hydrodynamic simulation of a region of 250 pc where we resolve the formation of individual massive stars. The supernova feedback is implemented with real supernovae that are the natural evolution of the resolved massive stars, so their position and timing are self-consistent. We select a large sample of molecular clouds from the simulation to investigate the supernova energy injection and the resulting properties of molecular clouds. We find that molecular clouds have a lifetime of a few dynamical times, less then half of them contract to the point of becoming gravitationally bound, and the dispersal time of bound clouds, of order one dynamical time, is a factor of two shorter than that of unbound clouds. We stress the importance of internal supernovae, that is massive stars that explode inside their parent cloud, in setting the cloud dispersal time, and their huge overdensity compared to models where the supernovae are randomly distributed. We also quantify the energy injection efficiency of supernovae as a function of supernova distance to the clouds. We conclude that intermittent driving by supernovae can maintain molecular-cloud turbulence and may be the main process of cloud dispersal. The role of supernovae in the evolution of molecular clouds cannot be fully accounted for without a self-consistent implementation of their feedback.
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Giant Molecular Clouds (GMCs) are observed to be turbulent, but theory shows that without a driving mechanism turbulence should quickly decay. The question arises by which mechanisms turbulence is driven or sustained. It has been shown that photoionising feedback from massive stars has an impact on the surrounding GMC and can for example create vast HII bubbles. We therefore address the question of whether turbulence is a consequence of this effect of feedback on the cloud. To investigate this, we analyse the velocity field of simulations of high mass star forming regions by studying velocity structure functions and power spectra. We find that clouds whose morphology is strongly affected by photoionising feedback also show evidence of driving of turbulence by preserving or recovering a Kolmogorov-type velocity field. On the contrary, control run simulations without photoionising feedback have a velocity distribution that bears the signature of gravitational collapse and of the dissipation of energy, where the initial Kolmogorov-type structure function is erased.
Simulations generally show that non-self-gravitating clouds have a lognormal column density ($Sigma$) probability distribution function (PDF), while self-gravitating clouds with active star formation develop a distinct power-law tail at high column density. Although the growth of the power law can be attributed to gravitational contraction leading to the formation of condensed cores, it is often debated if an observed lognormal shape is a direct consequence of supersonic turbulence alone, or even if it is really observed in molecular clouds. In this paper we run three-dimensional magnetohydrodynamic simulations including ambipolar diffusion with different initial conditions to see the effect of strong magnetic fields and nonlinear initial velocity perturbations on the evolution of the column density PDFs. Our simulations show that column density PDFs of clouds with supercritical mass-to-flux ratio, with either linear perturbations or nonlinear turbulence, quickly develop a power-law tail such that $dN/d log Sigma propto Sigma^{-alpha}$ with index $alpha simeq 2$. Interestingly, clouds with subcritical mass-to-flux ratio also proceed directly to a power-law PDF, but with a much steeper index $alpha simeq 4$. This is a result of gravitationally-driven ambipolar diffusion. However, for nonlinear perturbations with a turbulent spectrum ($v_{k}^{2} propto k^{-4}$), the column density PDFs of subcritical clouds do retain a lognormal shape for a major part of the cloud evolution, and only develop a distinct power-law tail with index $alpha simeq 2$ at greater column density when supercritical pockets are formed.
The magnetic field of molecular clouds (MCs) plays an important role in the process of star formation: it determins the statistical properties of supersonic turbulence that controls the fragmentation of MCs, controls the angular momentum transport during the protostellar collapse, and affects the stability of circumstellar disks. In this work, we focus on the problem of the determination of the magnetic field strength. We review the idea that the MC turbulence is super-Alfv{e}nic, and we argue that MCs are bound to be born super-Alfv{e}nic. We show that this scenario is supported by results from a recent simulation of supernova-driven turbulence on a scale of 250 pc, where the turbulent cascade is resolved on a wide range of scales, including the interior of MCs.
We perform ideal MHD high resolution AMR simulations with driven turbulence and self-gravity and find that long filamentary molecular clouds are formed at the converging locations of large-scale turbulence flows and the filaments are bounded by gravity. The magnetic field helps shape and reinforce the long filamentary structures. The main filamentary cloud has a length of ~4.4 pc. Instead of a monolithic cylindrical structure, the main cloud is shown to be a collection of fiber/web-like sub-structures similar to filamentary clouds such as L1495. Unless the line-of-sight is close to the mean field direction, the large-scale magnetic field and striations in the simulation are found roughly perpendicular to the long axis of the main cloud, similar to 1495. This provides strong support for a large-scale moderately strong magnetic field surrounding L1495. We find that the projection effect from observations can lead to incorrect interpretations of the true three-dimensional physical shape, size, and velocity structure of the clouds. Helical magnetic field structures found around filamentary clouds that are interpreted from Zeeman observations can be explained by a simple bending of the magnetic field that pierces through the cloud. We demonstrate that two dark clouds form a T-shape configuration which are strikingly similar to the Infrared dark cloud SDC13 leading to the interpretation that SDC13 results from a collision of two long filamentary clouds. We show that a moderately strong magnetic field (M_A ~ 1) is crucial for maintaining a long and slender filamentary cloud for a long period of time ~0.5 million years.
The structure of molecular clouds (MCs) holds important clues on the physical processes that lead to their formation and subsequent evolution. While it is well established that turbulence imprints a self-similar structure to the clouds, other processes, such as gravity and stellar feedback, can break their scale-free nature. The break of self-similarity can manifest itself in the existence of characteristic scales that stand out from the underlying structure generated by turbulent motions. We investigate the structure of the Cygnus-X North and the Polaris MCs which represent two extremes in terms of their star formation activity. We characterize the structure of the clouds using the delta-variance ($Delta$-variance) spectrum. In Polaris, the structure of the cloud is self-similar over more than one order of magnitude in spatial scales. In contrast, the $Delta$-variance spectrum of Cygnus-X exhibits an excess and a plateau on physical scales of ~0.5-1.2 pc. In order to explain the observations for Cygnus-X, we use synthetic maps in which we overlay populations of discrete structures on top of a fractal Brownian motion (fBm) image. The properties of these structures such as their major axis sizes, aspect ratios, and column density contrasts are randomly drawn from parameterized distribution functions. We show that it is possible to reproduce a $Delta$-variance spectrum that resembles the one of the Cygnus-X cloud. We also use a reverse engineering approach in which we extract the compact structures in the Cygnus-X cloud and re-inject them on an fBm map. The calculated $Delta$-variance using this approach deviates from the observations and is an indication that the range of characteristic scales observed in Cygnus-X is not only due to the existence of compact sources, but is a signature of the whole population of structures, including more extended and elongated structures
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