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The age of extremely red and massive galaxies at very high redshift

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arxiv 1111.2726 v2 pith:BMUFXO7C submitted 2011-11-11 astro-ph.CO

classification astro-ph.CO
keywords galaxiesobjectserosstellarmassredshiftsveryformed
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Aims. We present a determination of the intrinsic colors and ages of galaxies at very high redshift, in particular old galaxies (OGs) within extremely red objects (EROs). To date, the definition of EROs has been restricted to objects with z<2.5, however, here consider objects with the same properties but shifted to higher redshifts (z>2.5). We therefore, refer to these objects as very high-redshift EROs (Z-EROS, herein). Methods. We analyze 63,550 galaxies selected in the XMM-LSS field. To obtain a reasonably sized sample of EROs, it is essential to consider a very wide area surveys. We identify targets within an area of 0.77 square degrees for which optical to mid-infrared data are available from SUBARU, UKIDSS, and Spitzer. We select Z-EROs based on their colors, and then perform a selection of only OGs. One of our novel innovations is to adapt the traditional method of EROs selection based on the filters I and K, to higher redshifts. Using our method, we identify 20 objects that satisfy the conditions required to be Z-EROs/OGs at redshifts 2.5<z<3.8 within some conservative constraints of errors in the photometric redshifts. For each of these objects, we calculate the corresponding color at rest (B-V), and estimate their average stellar mass and age by comparing this color with a synthesis model. Results. Our selected galaxies have high stellar masses (~10^{11} M_sun) and are older than 1 Gyr, hence their stellar populations were formed at z>~4.7. After including additional galaxies with z<2.5 analyzed in a previous paper, we find that the formation epoch depends significantly on the observed redshift and stellar mass: the higher the stellar mass, the lower the age of the Universe at which it was formed. This result appears to conflict with Lambda-CDM models that claim that the most massive galaxies formed after lower mass.

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Cited by 1 Pith paper

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  1. Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR

    astro-ph.CO 2025-05 reject novelty 4.0 of 10

    A benchmark of CART, MLPR, and SVR on simulated galaxy ages shows SVR has the lowest error and recovers the fiducial Omega_m and w values used to generate the data.

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