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RELICS: A Very Large (θ_(E)sim40") Cluster Lens -- RXC J0032.1+1808

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arxiv 1912.02702 v2 pith:UVS36G4A submitted 2019-12-05 astro-ph.CO astro-ph.GA

RELICS: A Very Large ($\theta_{E}\sim40"$) Cluster Lens -- RXC J0032.1+1808

classification astro-ph.CO astro-ph.GA
keywords clusterarcseclargemodelsrelicstextitthetahubble
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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abstract

Extensive surveys with the \textit{Hubble Space Telescope} (HST) over the past decade, targeting some of the most massive clusters in the sky, have uncovered dozens of galaxy-cluster strong lenses. The massive cluster strong-lens scale is typically $\theta_{E}\sim10\arcsec$ to $\sim30-35\arcsec$, with only a handful of clusters known with Einstein radii $\theta_{E}\sim40\arcsec$ or above (for $z_{source}=2$, nominally). Here we report another very large cluster lens, RXC J0032.1+1808 ($z=0.3956$), the second richest cluster in the redMapper cluster catalog and the 85th most massive cluster in the Planck Sunyaev-Zel'dovich catalog. With our Light-Traces-Mass and fully parametric (dPIEeNFW) approaches, we construct strong lensing models based on 18 multiple images of 5 background galaxies newly identified in the \textit{Hubble} data mainly from the \textit{Reionization Lensing Cluster Survey} (RELICS), in addition to a known sextuply imaged system in this cluster. Furthermore, we compare these models to Lenstool and GLAFIC models that were produced independently as part of the RELICS program. All models reveal a large effective Einstein radius of $\theta_{E}\simeq40\arcsec$ ($z_{source}=2$), owing to the obvious concentration of substructures near the cluster center. Although RXC J0032.1+1808 has a very large critical area and high lensing strength, only three magnified high-redshift candidates are found within the field targeted by RELICS. Nevertheless, we expect many more high-redshift candidates will be seen in wider and deeper observations with \textit{Hubble} or \emph{JWST}. Finally, the comparison between several algorithms demonstrates that the total error budget is largely dominated by systematic uncertainties.

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