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The Mice at play in the CALIFA survey: A case study of a gas-rich major merger between first passage and coalescence

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arxiv 1405.7814 v1 pith:IKGUN62T submitted 2014-05-30 astro-ph.GA

classification astro-ph.GA
keywords stellargalaxiespassagefirstmergerformationmicengc4676a
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We present optical integral field spectroscopy (IFS) observations of the Mice, a major merger between two massive (>10^11Msol) gas-rich spirals NGC4676A and B, observed between first passage and final coalescence. The spectra provide stellar and gas kinematics, ionised gas properties and stellar population diagnostics, over the full optical extent of both galaxies. The Mice provide a perfect case study highlighting the importance of IFS data for improving our understanding of local galaxies. The impact of first passage on the kinematics of the stars and gas has been significant, with strong bars likely induced in both galaxies. The barred spiral NGC4676B exhibits a strong twist in both its stellar and ionised gas disk. On the other hand, the impact of the merger on the stellar populations has been minimal thus far: star formation induced by the recent close passage has not contributed significantly to the global star formation rate or stellar mass of the galaxies. Both galaxies show bicones of high ionisation gas extending along their minor axes. In NGC4676A the high gas velocity dispersion and Seyfert-like line ratios at large scaleheight indicate a powerful outflow. Fast shocks extend to ~6.6kpc above the disk plane. The measured ram pressure and mass outflow rate (~8-20Msol/yr) are similar to superwinds from local ULIRGs, although NGC4676A has only a moderate infrared luminosity of 3x10^10Lsol. Energy beyond that provided by the mechanical energy of the starburst appears to be required to drive the outflow. We compare the observations to mock kinematic and stellar population maps from a merger simulation. The models show little enhancement in star formation during and following first passage, in agreement with the observations. We highlight areas where IFS data could help further constrain the models.

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