Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees
arxiv(2024)
摘要
Dusty, distant, massive (M_*≳ 10^11 M_⊙) galaxies are
usually found to show a remarkable star-formation activity, contributing on the
order of 25% of the cosmic star-formation rate density at z≈3–5,
and up to 30% at z∼7 from ALMA observations. Nonetheless, they are
elusive in classical optical surveys, and current near-infrared surveys are
able to detect them only in very small sky areas. Since these objects have low
space densities, deep and wide surveys are necessary to obtain statistically
relevant results about them. Euclid will be potentially capable of delivering
the required information, but, given the lack of spectroscopic features at
these distances within its bands, it is still unclear if it will be possible to
identify and characterize these objects. The goal of this work is to assess the
capability of Euclid, together with ancillary optical and near-infrared data,
to identify these distant, dusty and massive galaxies, based on broadband
photometry. We used a gradient-boosting algorithm to predict both the redshift
and spectral type of objects at high z. To perform such an analysis we make
use of simulated photometric observations derived using the SPRITZ software.
The gradient-boosting algorithm was found to be accurate in predicting both the
redshift and spectral type of objects within the Euclid Deep Survey simulated
catalog at z>2. In particular, we study the analog of HIEROs (i.e. sources
with H-[4.5]>2.25), combining Euclid and Spitzer data at the depth of the
Deep Fields. We found that the dusty population at 3≲ z≲ 7 is
well identified, with a redshift RMS and OLF of only 0.55 and 8.5%
(H_E≤26), respectively. Our findings suggest that with Euclid we will
obtain meaningful insights into the role of massive and dusty galaxies in the
cosmic star-formation rate over time.
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