Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

earth and planetary sciences

The e-MERGE Survey (e-MERLIN Galaxy Evolution Survey): Overview and survey description

Monthly Notices of the Royal Astronomical Society, Volume 495, No. 1, Year 2020

We present an overview and description of the e-MERGE Survey (e-MERLIN Galaxy Evolution Survey) Data Release 1 (DR1), a large program of high-resolution 1.5-GHz radio observations of the GOODS-N field comprising ∼140 h of observations with enhanced-Multi-Element Remotely Linked Interferometer Network (e-MERLIN) and ∼40 h with the Very Large Array (VLA). We combine the long baselines of e-MERLIN (providing high angular resolution) with the relatively closely packed antennas of the VLA (providing excellent surface brightness sensitivity) to produce a deep 1.5-GHz radio survey with the sensitivity (∼1.5 μ Jy beam−1), angular resolution (0.2–0.7 arcsec) and field-of-view (∼15 × 15 arcmin2) to detect and spatially resolve star-forming galaxies and active galactic nucleus (AGN) at z ≳ 1. The goal of e-MERGE is to provide new constraints on the deep, sub-arcsecond radio sky which will be surveyed by SKA1-mid. In this initial publication, we discuss our data analysis techniques, including steps taken to model in-beam source variability over an ∼20-yr baseline and the development of new point spread function/primary beam models to seamlessly merge e-MERLIN and VLA data in the uv plane. We present early science results, including measurements of the luminosities and/or linear sizes of ∼500 galaxies selected at 1.5 GHz. In combination with deep Hubble Space Telescope observations, we measure a mean radio-to-optical size ratio of re-MERGE/rHST ∼ 1.02 ± 0.03, suggesting that in most high-redshift galaxies, the ∼GHz continuum emission traces the stellar light seen in optical imaging. This is the first in a series of papers that will explore the ∼kpc-scale radio properties of star-forming galaxies and AGN in the GOODS-N field observed by e-MERGE DR1.

Statistics
Citations: 40
Authors: 40
Affiliations: 28
Identifiers
Research Areas
Environmental
Study Design
Cross Sectional Study
Study Approach
Quantitative