A Virtual Sky with Extragalactic HI and CO Lines for the SKA and ALMA

Details A Virtual Sky with Extragalactic HI and CO Lines for the SKA and ALMA A Virtual Sky with Extragalactic HI and CO Lines for the SKA and ALMA

2009-08-07

arxiv.org/abs/0908.0983v2

ApJ 703, 1890-1903 (2009)

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

16 pages, 9 figures, 1 table

Scientific paper

10.1088/0004-637X/703/2/1890

We present a sky simulation of the atomic HI emission line and the first ten CO rotational emission lines of molecular gas in galaxies beyond the Milky Way. The simulated sky field has a comoving diameter of 500/h Mpc, hence the actual field-of-view depends on the (user-defined) maximal redshift zmax; e.g. for zmax=10, the field of view yields ~4x4 sqdeg. For all galaxies, we estimate the line fluxes, line profiles, and angular sizes of the HI and CO emission lines. The galaxy sample is complete for galaxies with cold hydrogen masses above 10^8 Msun. This sky simulation builds on a semi-analytic model of the cosmic evolution of galaxies in a Lambda-cold dark matter (LCDM) cosmology. The evolving CDM-distribution was adopted from the Millennium Simulation, an N-body CDM-simulation in a cubic box with a side length of 500/h Mpc. This side length limits the coherence scale of our sky simulation: it is long enough to allow the extraction of the baryon acoustic oscillations (BAOs) in the galaxy power spectrum, yet the position and amplitude of the first acoustic peak will be imperfectly defined. This sky simulation is a tangible aid to the design and operation of future telescopes, such the SKA, the LMT, and ALMA. The results presented in this paper have been restricted to a graphical representation of the simulated sky and fundamental dN/dz-analyzes for peak flux density limited and total flux limited surveys of HI and CO. A key prediction is that HI will be harder to detect at redshifts z>2 than predicted by a no-evolution model. The future verification or falsification of this prediction will allow us to qualify the semi-analytic models.

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