2016
DOI: 10.1093/mnras/stw2126
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SDSS IV MaNGA: the global and local stellar mass assemby histories of galaxies

Abstract: By means of the fossil record method implemented through Pipe3D, we reconstruct the global and radial stellar mass growth histories (MGHs) of an unprecedentedly large sample of galaxies, ranging from dwarf to giant objects, from the "Mapping Nearby Galaxies at the Apache Point Observatory" survey. We confirm that the main driver of the global MGHs is mass, with more massive galaxies assembling their masses earlier (downsizing), though for a given mass, the global MGHs segregate by color, specific star formatio… Show more

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Cited by 124 publications
(220 citation statements)
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“…Ibarra -Medel et al (2016) meanwhile infer spatially resolved stellar mass assembly histories for the MaNGA galaxies, extending previously known relations between galaxy type and assembly history to a larger mass range. Their findings are consistent with blue/star-forming/late-type galaxies assembling, on average, from inside to out.…”
Section: Stellar Populationssupporting
confidence: 59%
“…Ibarra -Medel et al (2016) meanwhile infer spatially resolved stellar mass assembly histories for the MaNGA galaxies, extending previously known relations between galaxy type and assembly history to a larger mass range. Their findings are consistent with blue/star-forming/late-type galaxies assembling, on average, from inside to out.…”
Section: Stellar Populationssupporting
confidence: 59%
“…Moreover, galaxies may be rejuvenated if there is fresh gas accreted when experiencing minor mergers or galaxy interactions (Thomas et al 2010;Haines et al 2015;Lacerna et al 2016) and hence may not evolve monotonically with a decreasing global sSFR. Detailed stellar population analyses regarding the star formation and stellar mass assembling histories (e.g., Ibarra-Medel et al 2016) together with resolved gas observations for a larger sample of green valley galaxies is required to confirm the picture presented in this work.…”
Section: Discussionmentioning
confidence: 70%
“…PIPE3D is an IFU-focused analysis pipeline that calculates intermediate data products and is able to obtain both the stellar population and the ionized gas properties extracted from the data cubes in an automatic way. This pipeline is based on FIT3D, the details of which are presented in Sánchez et al (2016aSánchez et al ( , 2016b, which show some examples based on CALIFA (Cano-Díaz et al 2016;Sánchez-Menguiano et al 2016;Sánchez et al 2017b) and MaNGA/P-MaNGA (BarreraBallesteros et al 2016;Ibarra-Medel et al 2016;BarreraBallesteros et al 2017;Lin et al 2017) data sets. The MaNGA data products provided by Pipe3D are presented in Sánchez et al (2017a).…”
Section: Manga Vacsmentioning
confidence: 99%