What controls the ionized gas turbulent motions in dwarf galaxies?

Using 3D spectroscopy with a scanning Fabry-Perot interferometer, we study the ionized gas kinematics in 59 nearby dwarf galaxies. Combining our results with data from literature, we provide a global relation between the gas velocity dispersion (sigma) and the star formation rate (SFR) and Halpha luminosity for galaxies in a very broad range of star formation rates SFR=0.001-300 Msun/yr. We find that the SFR-sigma relation for the combined sample of dwarf galaxies, star forming, local luminous, and ultra-luminous infrared galaxies can be fitted as sigma~ SFR^(5.3+-0.2). This implies that the slope of the L-sigma relation inferred from the sample of rotation supported disc galaxies (including mergers) is similar to the L-sigma relation of individual giant HII regions. We present arguments that the velocity dispersion of the ionized gas does not reflect the virial motions in the gravitational potential of dwarf galaxies, and instead is mainly determined by the energy injected into the interstellar medium by the ongoing star formation.

The ART of Cosmological Simulations

We describe the basic ideas of MPI parallelization of the N-body Adaptive Refinement Tree (ART) code. The code uses self-adaptive domain decomposition where boundaries of the domains (parallelepipeds) constantly move -- with many degrees of freedom -- in the search of the minimum of CPU time. The actual CPU time spent by each MPI task on previous time-step is used to adjust boundaries for the next time-step. For a typical decomposition of 5^3 domains, the number of possible changes in boundaries is 3^{84}. We describe two algorithms of finding minimum of CPU time for configurations with a large number of domains. Each MPI task in our code solves the N-body problem where the large-scale distribution of matter outside of the boundaries of a domain is represented by relatively few temporary large particles created by other domains. At the beginning of a zero-level time-step, domains create and exchange large particles. Then each domain advances all its particles for many small time-steps. At the end of the large step, the domains decide where to place new boundaries and re-distribute particles. The scheme requires little communications between processors and is very efficient for large cosmological simulations.