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The Two States of Star Forming Clouds

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arxiv 1202.2594 v1 pith:JQAFHZJO submitted 2012-02-13 astro-ph.SR

classification astro-ph.SR
keywords densityfieldhighmagneticsimulationsstatecloudsdistribution
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We examine the effects of self-gravity and magnetic fields on supersonic turbulence in isothermal molecular clouds with high resolution simulations and adaptive mesh refinement. These simulations use large root grids (512^3) to capture turbulence and four levels of refinement to capture high density, for an effective resolution of 8,196^3. Three Mach 9 simulations are performed, two super-Alfv\'enic and one trans-Alfv\'enic. We find that gravity splits the clouds into two populations, one low density turbulent state and one high density collapsing state. The low density state exhibits properties similar to non-self-gravitating in this regime, and we examine the effects of varied magnetic field strength on statistical properties: the density probability distribution function is approximately lognormal; velocity power spectral slopes decrease with field strength; alignment between velocity and magnetic field increases with field; the magnetic field probability distribution can be fit to a stretched exponential. The high density state is characterized by self-similar spheres; the density PDF is a power-law; collapse rate decreases with increasing mean field; density power spectra have positive slopes, P({\rho},k) \propto k; thermal-to-magnetic pressure ratios are unity for all simulations; dynamic-to-magnetic pressure ratios are larger than unity for all simulations; magnetic field distribution is a power-law. The high Alfv\'en Mach numbers in collapsing regions explain recent observations of magnetic influence decreasing with density. We also find that the high density state is found in filaments formed by converging flows, consistent with recent Herschel observations. Possible modifications to existing star formation theories are explored.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Revealing hidden correlations from complex spatial distributions: Adjacent Correlation Analysis

    physics.comp-ph 2025-06 conditional novelty 6.0 of 10

    A new method, adjacent correlation analysis, extracts local correlations between two measured quantities from spatial gradients and visualizes them as vector fields in phase space.

  2. Mapping correlations and coherence: adjacency-based approach to data visualization and regularity discovery

    physics.comp-ph 2025-06 reject novelty 2.0 of 10

    The proposed 'adjacent correlation map' is a restatement of the gradient structure tensor and produces spatial maps of a local correlation angle and degree.

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