2007
DOI: 10.1086/519443
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The Statistics of Supersonic Isothermal Turbulence

Abstract: We present results of large-scale three-dimensional simulations of supersonic Euler turbulence with the piecewise parabolic method and multiple grid resolutions up to 2048^3 points. Our numerical experiments describe non-magnetized driven turbulent flows with an isothermal equation of state and an rms Mach number of 6. We discuss numerical resolution issues and demonstrate convergence, in a statistical sense, of the inertial range dynamics in simulations on grids larger than 512^3 points. The simulations allow… Show more

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Cited by 555 publications
(961 citation statements)
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References 88 publications
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“…Heithausen et al (1998) found M ∝ r 2.31 for scales ranging from 0.01 to 1 pc. A similar mass-size relation is seen in numerical simulations where there is no gravity, and with or without heating and cooling processes included (Kritsuk et al 2007;Federrath et al 2009;Audit & Hennebelle 2010). Because of the fact that this relation is seen in different physical conditions, including isothermal gas, it is often attributed to turbulence.…”
Section: Masssupporting
confidence: 64%
“…Heithausen et al (1998) found M ∝ r 2.31 for scales ranging from 0.01 to 1 pc. A similar mass-size relation is seen in numerical simulations where there is no gravity, and with or without heating and cooling processes included (Kritsuk et al 2007;Federrath et al 2009;Audit & Hennebelle 2010). Because of the fact that this relation is seen in different physical conditions, including isothermal gas, it is often attributed to turbulence.…”
Section: Masssupporting
confidence: 64%
“…This might explain that the gradientsubtracted PDF still shows a weak second peak at a velocity of -v 4 km s 1 to the right of the main peak (v = 0). Finally, turbulence has intrinsic non-Gaussian features, broadly referred to as "intermittency," leading to deviations from Gaussian statistics, especially in the tails of the PDFs (Falgarone & Phillips 1990;Passot & VĂĄzquez-Semadeni 1998;Kritsuk et al 2007;Hily-Blant et al 2008;Schmidt et al 2008Schmidt et al , 2009Burkhart et al 2009;Falgarone et al 2009;Federrath et al 2009Federrath et al , 2010Federrath 2013;Hopkins 2013b). In summary, the Gaussian fit in Figure 4 and the standard deviation of the velocity data (without fitting) yield a consistent 1D turbulent velocity dispersion of s =  -3.9 0.1 km s…”
Section: Velocity Pdfmentioning
confidence: 79%
“…For compressible, isothermal and subsonic turbulence, Kim & Ryu (2005), Kritsuk et al (2007), Saury et al (2014) showed that the power spectrum of density follows that of the velocity (P k (n) ∌ k −11/3 ). This would produce a column density power spectrum with Îł = −3.7, far from what is observed.…”
Section: The Power Spectrum Of Density Fluctuationsmentioning
confidence: 99%