Person:

Goodman, Alyssa

In this work, we present a detailed study of the rotational properties of magnetized and self-gravitating dense molecular cloud cores formed in a set of two very high resolution three-dimensional molecular cloud simulations with decaying turbulence. The simulations have been performed using the adaptative mesh refinement code RAMSES with an effective resolution of (4096^3) grid cells. One simulation represents a mildly magnetically-supercritical cloud and the other a strongly magnetically-supercritical cloud. We identify dense cores at a number of selected epochs in the simulations at two density thresholds which roughly mimick the excitation densities of the (NH_{3} (J − K)=(1,1)) transition and the (N_{2}H^{+}(1-0)) emission line. A noticeable global difference between the two simulations is the core formation efficiency (CFE) of the high density cores. In the strongly supercritical simulations the CFE is 33 percent per unit free-fall time of the cloud ((t_{ff,cl})), whereas in the mildly supercritical simulations this value goes down to (\sim 6) percent per unit (t_{ff,cl}). A comparison of the intrinsic specific angular momentum ((j_{3D})) distributions of the cores with the specific angular momentum derived using synthetic two-dimensional velocity maps of the cores ((j_{3D})) , shows that the synthetic observations tend to overestimate the true value of the specific angular momentum by a factor of (\sim 8−10). We find that the distribution of the ratio (j_{3D}/j_{2D}) of the cores peaks at around (\sim 0.1). The origin of this discrepancy lies in the fact that contrary to the intrinsic determination of j which sums up the individual gas parcels contributions to the angular momentum, the determination of the specific angular momentum using the standard observational procedure which is based on a measurement on the global velocity gradient under the hypothesis of uniform rotation smoothes out the complex fluctuations present in the three-dimensional velocity field. Our results may well provide a natural explanation for the discrepancy by a factor ∼ 10 observed between the intrinsic three-dimensional distributions of the specific angular momentum and the corresponding distributions derived in real observations. We suggest that previous and future measurements of the specific angular momentum of dense cores which are based on the measurement of the observed global velocity gradients may need to be reduced by a factor of (\sim 10) in order to derive a more accurate estimate of the true specific angular momentum in the cores. We also show that the exponent of the size-specific angular momentum relation are smaller ((\sim 1.4)) in the synthetic observations than their values derived in the three-dimensional space ((\sim 1.8)).

We utilize the extensive datasets available for the Perseus molecular cloud to analyze the relationship between the kinematics of small-scale dense cores and the larger structures in which they are embedded. The kinematic measures presented here can be used in conjunction with those discussed in our previous work as strong observational constraints that numerical simulations (or analytic models) of star formation should match. We find that dense cores have small motions with respect to the (^{13}CO) gas, about one third of the (^{13}CO) velocity dispersion along the same line of sight. Within each extinction region, the core- to-core velocity dispersion is about half of the total ((^{13}CO)) velocity dispersion seen in the region. Large-scale velocity gradients account for roughly half of the total velocity dispersion in each region, similar to what is predicted from large-scale turbulent modes following a power spectrum of (P(k) \alpha \ k^{−4}).

Magnetohydrodynamic turbulence is able to create hierarchical structures in the interstellar medium (ISM) that are correlated on a wide range of scales via the energy cascade. We use hierarchical tree diagrams known as dendrograms to characterize structures in synthetic position-position-velocity (PPV) emission cubes of isothermal magnetohydrodynamic turbulence. We show that the structures and degree of hierarchy observed in PPV space are related to the presence of self-gravity and the global sonic and Alfvénic Mach numbers. Simulations with higher Alfvénic Mach number, self-gravity and supersonic flows display enhanced hierarchical structure. We observe a strong dependency on the sonic and Alfvénic Mach numbers and self-gravity when we apply the statistical moments (i.e., mean, variance, skewness, kurtosis) to the leaf and node distribution of the dendrogram. Simulations with self-gravity, larger magnetic field and higher sonic Mach number have dendrogram distributions with higher statistical moments. Application of the dendrogram to three-dimensional density cubes, also known as position-position-position (PPP) cubes, reveals that the dominant emission contours in PPP and PPV are related for supersonic gas but not for subsonic. We also explore the effects of smoothing, thermal broadening, and velocity resolution on the dendrograms in order to make our study more applicable to observational data. These results all point to hierarchical tree diagrams as being a promising additional tool for studying ISM turbulence and star forming regions for obtaining information on the degree of self-gravity, the Mach numbers and the complicated relationship between PPV and PPP data.

One of the key problems in star formation research is to determine the role of magnetic fields. Starting from the atomic intercloud medium which has density (n_H \sim \ 1 \ cm^{–3}), gas must accumulate from a volume several hundred pc across in order to form a typical molecular cloud. Star formation usually occurs in cloud cores, which have linear sizes below 1 pc and densities (n_{H2} > 10^5 \ cm^{–3}). With current technologies, it is hard to probe magnetic fields at scales lying between the accumulation length and the size of cloud cores, a range corresponds to many levels of turbulent eddy cascade, and many orders of magnitude of density amplification. For field directions detected from the two extremes, however, we show here that a significant correlation is found. Comparing this result with molecular cloud simulations, only the sub-Alfvénic cases result in field orientations consistent with our observations.

We present a study on the impact of molecular outflows in the Perseus molecular cloud complex using the COMPLETE Survey large-scale (^{12}CO(1-0)) and (^{13}CO(1-0)) maps. We used three-dimensional isosurface models generated in right ascension-declination-velocity space to visualize the maps. This rendering of the molecular line data allowed for a rapid and efficient way to search for molecular outflows over a large ((\sim16 deg^2)) area. Our outflow-searching technique detected previously known molecular outflows as well as new candidate outflows. Most of these new outflow-related high-velocity features lie in regions that have been poorly studied before. These new outflow candidates more than double the amount of outflow mass, momentum, and kinetic energy in the Perseus cloud complex. Our results indicate that outflows have significant impact on the environment immediately surrounding localized regions of active star formation, but lack the energy needed to feed the observed turbulence in the entire Perseus complex. This implies that other energy sources, in addition to protostellar outflows, are responsible for turbulence on a global cloud scale in Perseus. We studied the impact of outflows in six regions with active star formation within Perseus of sizes in the range of 1-4 pc. We find that outflows have enough power to maintain the turbulence in these regions and enough momentum to disperse and unbind some mass from them. We found no correlation between outflow strength and star formation efficiency (SFE) for the six different regions we studied, contrary to results of recent numerical simulations. The low fraction of gas that potentially could be ejected due to outflows suggests that additional mechanisms other than cloud dispersal by outflows are needed to explain low SFEs in clusters.