GRAPESPH with Fully Periodic Boundary Conditions: Fragmentation of Molecular Clouds

A method of adapting smoothed particle hydrodynamics (SPH) with periodic boundary conditions for use with the special purpose device GRAPE is presented. GRAPE (GRAvity PipE) solves the Poisson and force equations for an N-body system by direct summation on a specially designed chip and in addition returns the neighbour list for each particle. Due to its design, GRAPE cannot treat periodic particle distributions directly. This limitation of GRAPESPH can be overcome by computing a correction force for each particle due to periodicity (Ewald correction) on the host computer using a PM-like method. This scheme is applied to study the fragmentation process in giant molecular clouds. Assuming a pure isothermal model, we follow the dynamical evolution in the interior of a molecular cloud starting from an Gaussian initial density distribution to the formation of selfgravitating clumps until most of the gas is consumed in these dense cores. Despite its simplicity, this model can reproduce some fundamental properties of observed molecular clouds, like a clump mass distribution of the form $dN/dm \propto m^n$, with $n ~ -1.5$.Comment: 8 pages; LaTeX + 7 PS figures; accepted for publication in MNRAS; also available at http://www.mpia-hd.mpg.de/MPIA/Projects/THEORY/klessen/Preprints/p5.p

The structure of self-gravitating clouds

To study the interaction of star-formation and turbulent molecular cloud structuring, we analyse numerical models and observations of self-gravitating clouds using the Delta-variance as statistical measure for structural characteristics. In the models we resolve the transition from purely hydrodynamic turbulence to gravitational collapse associated with the formation and mass growth of protostellar cores. We compare models of driven and freely decaying turbulence with and without magnetic fields. Self-gravitating supersonic turbulence always produces a density structure that contains most power on the smallest scales provided by collapsed cores as soon as local collapse sets in. This is in contrast to non-self-gravitating hydrodynamic turbulence where the Delta-variance is dominated by large scale structures. To detect this effect in star-forming regions observations have to resolve the high density contrast of protostellar cores with respect to their ambient molecular cloud. Using the 3mm continuum map of a star-forming cluster in Serpens we show that the dust emission traces the full density evolution. On the contrary, the density range accessible by molecular line observations is insufficient for this analysis. Only dust emission and dust extinction observations are able to to determine the structural parameters of star-forming clouds following the density evolution during the gravitational collapse.Comment: 12 pages, 9 figures, A&A in pres

The Star Formation Rate of Turbulent Magnetized Clouds: Comparing Theory, Simulations, and Observations

We derive and compare six theoretical models for the star formation rate (SFR) - the Krumholz & McKee (KM), Padoan & Nordlund (PN), and Hennebelle & Chabrier (HC) models, and three multi-freefall versions of these, suggested by HC - all based on integrals over the log-normal distribution of turbulent gas. We extend all theories to include magnetic fields, and show that the SFR depends on four basic parameters: (1) virial parameter alpha_vir; (2) sonic Mach number M; (3) turbulent forcing parameter b, which is a measure for the fraction of energy driven in compressive modes; and (4) plasma beta=2(M_A/M)^2 with the Alfven Mach number M_A. We compare all six theories with MHD simulations, covering cloud masses of 300 to 4x10^6 solar masses and Mach numbers M = 3 to 50 and M_A = 1 to infinity, with solenoidal (b=1/3), mixed (b=0.4) and compressive turbulent (b=1) forcings. We find that the SFR increases by a factor of four between M=5 and 50 for compressive forcing and alpha_vir~1. Comparing forcing parameters, we see that the SFR is more than 10x higher with compressive than solenoidal forcing for Mach 10 simulations. The SFR and fragmentation are both reduced by a factor of two in strongly magnetized, trans-Alfvenic turbulence compared to hydrodynamic turbulence. All simulations are fit simultaneously by the multi-freefall KM and multi-freefall PN theories within a factor of two over two orders of magnitude in SFR. The simulated SFRs cover the range and correlation of SFR column density with gas column density observed in Galactic clouds, and agree well for star formation efficiencies SFE = 1% to 10% and local efficiencies epsilon = 0.3 to 0.7 due to feedback. We conclude that the SFR is primarily controlled by interstellar turbulence, with a secondary effect coming from magnetic fields.Comment: 34 pages, 12 figures, ApJ in press, movies at http://www.ita.uni-heidelberg.de/~chfeder/pubs/sfr/sfr.shtm

On the Star Formation Efficiency of Turbulent Magnetized Clouds

We study the star formation efficiency (SFE) in simulations and observations of turbulent, magnetized, molecular clouds. We find that the probability density functions (PDFs) of the density and the column density in our simulations with solenoidal, mixed, and compressive forcing of the turbulence, sonic Mach numbers of 3-50, and magnetic fields in the super- to the trans-Alfvenic regime, all develop power-law tails of flattening slope with increasing SFE. The high-density tails of the PDFs are consistent with equivalent radial density profiles, rho ~ r^(-kappa) with kappa ~ 1.5-2.5, in agreement with observations. Studying velocity-size scalings, we find that all the simulations are consistent with the observed v ~ l^(1/2) scaling of supersonic turbulence, and seem to approach Kolmogorov turbulence with v ~ l^(1/3) below the sonic scale. The velocity-size scaling is, however, largely independent of the SFE. In contrast, the density-size and column density-size scalings are highly sensitive to star formation. We find that the power-law slope alpha of the density power spectrum, P(rho,k) ~ k^alpha, or equivalently the Delta-variance spectrum of column density, DV(Sigma,l) ~ l^(-alpha), switches sign from alpha 0 when star formation proceeds (SFE > 0). We provide a relation to compute the SFE from a measurement of alpha. Studying the literature, we find values ranging from alpha = -1.6 to +1.6 in observations covering scales from the large-scale atomic medium, over cold molecular clouds, down to dense star-forming cores. From those alpha values, we infer SFEs and find good agreement with independent measurements based on young stellar object (YSO) counts, where available. Our SFE-alpha relation provides an independent estimate of the SFE based on the column density map of a cloud alone, without requiring a priori knowledge of star-formation activity or YSO counts.Comment: 23 pages, 14 figures, ApJ in press, more info at http://www.ita.uni-heidelberg.de/~chfeder/pubs/sfe/sfe.shtml?lang=e