Published October 27, 2023 | Version 1.0 as presented in the paper

Data products of the surface brightness modelling of the confirmed and candidates lenses in Borsato et al. 2023.

  • 1. ROR icon University of Padua
  • 2. ROR icon University of Cape Town
  • 3. ROR icon Cardiff University

Description

This repository contains the data products for the surface brightness analysis of strongly lensed candidates presented in Borsato et al. 2023. This repository is organized as follows.

The folder `cutouts' contains the cutouts (20x20 arcsec) of all the HST snapshots.

The folder `SB_models' includes the A and B folders containing the confirmed lenses and candidate lenses (A and B classes in the paper). Each of these folders contains a set of subfolders including the image cutouts, surface brightness models, residuals, noise maps, and PSFs of the confirmed lenses. 

Files

DataProducts_Borsato2023.zip

Files (320.3 MB)

Name Size
md5:959900d72247467750d3d6fb773e6f13
320.3 MB Preview Download
md5:380999ff2b755f11230744788be8c301
2.5 kB Download

Additional details

Dates

Issued
2023-10-27