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arxiv: 1512.01235 · v2 · pith:X5B6U3UJnew · submitted 2015-12-03 · 🌌 astro-ph.GA

Breathing FIRE: How Stellar Feedback Drives Radial Migration, Rapid Size Fluctuations, and Population Gradients in Low-Mass Galaxies

classification 🌌 astro-ph.GA
keywords stellarfeedbackgalaxiesradialeffectsmigrationstarfluctuations
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We examine the effects of stellar feedback and bursty star formation on low-mass galaxies ($M_{\rm star}=2\times10^6-5\times10^{10}{\rm M_{\odot}}$) using the FIRE (Feedback in Realistic Environments) simulations. While previous studies emphasized the impact of feedback on dark matter profiles, we investigate the impact on the stellar component: kinematics, radial migration, size evolution, and population gradients. Feedback-driven outflows/inflows drive significant radial stellar migration over both short and long timescales via two processes: (1) outflowing/infalling gas can remain star-forming, producing young stars that migrate $\sim1{\rm\,kpc}$ within their first $100 {\rm\,Myr}$, and (2) gas outflows/inflows drive strong fluctuations in the global potential, transferring energy to all stars. These processes produce several dramatic effects. First, galaxies' effective radii can fluctuate by factors of $>2$ over $\sim200 {\rm\,Myr}$, and these rapid size fluctuations can account for much of the observed scatter in radius at fixed $M_{\rm star}.$ Second, the cumulative effects of many outflow/infall episodes steadily heat stellar orbits, causing old stars to migrate outward most strongly. This age-dependent radial migration mixes---and even inverts---intrinsic age and metallicity gradients. Thus, the galactic-archaeology approach of calculating radial star-formation histories from stellar populations at $z=0$ can be severely biased. These effects are strongest at $M_{\rm star}\approx10^{7-9.6}{\rm M_{\odot}}$, the same regime where feedback most efficiently cores galaxies. Thus, detailed measurements of stellar kinematics in low-mass galaxies can strongly constrain feedback models and test baryonic solutions to small-scale problems in $\Lambda$CDM.

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