The Astrophysical Journal (Jan 2024)

CANUCS: An Updated Mass and Magnification Model of A370 with JWST

  • Rachel Gledhill,
  • Victoria Strait,
  • Guillaume Desprez,
  • Gregor Rihtaršič,
  • Maruša Bradač,
  • Gabriel Brammer,
  • Chris J. Willott,
  • Nicholas Martis,
  • Marcin Sawicki,
  • Gaël Noirot,
  • Ghassan T. E. Sarrouh,
  • Adam Muzzin

DOI
https://doi.org/10.3847/1538-4357/ad684a
Journal volume & issue
Vol. 973, no. 2
p. 77

Abstract

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We present an updated mass and magnification model of galaxy cluster A370 using new NIRCam, NIRISS, and NIRSpec data from the Canadian NIRISS Unbiased Cluster Survey (CANUCS). Using Lenstool and a combination of archival Hubble Space Telescope (HST) and MUSE data with new JWST data as constraints, we derive an improved gravitational lensing model and extract magnifications of background galaxies with uncertainties. Using our best fit model, we perform a search for new multiply imaged systems via predicted positions. We report no new multiply imaged systems with identifiable redshifts, likely due to already very deep HST and Spitzer data but confirm a z ∼ 8 multiply imaged system by measuring its redshift with NIRISS and NIRSpec spectra. We find that the overall shape of the critical curve for a source at z = 9.0 is similar to previous models of A370, with small changes. We investigate the z ∼ 8 galaxy with two images observable with an apparent magnitude in the F125W band of 26.0 ± 0.2 and 25.6 ± 0.1. After correcting for the magnifications of the images, ${7.4}_{-0.3}^{+0.5}$ and ${9.4}_{-0.4}^{+0.5}$ , we use spectral energy distribution fitting to find an intrinsic stellar mass of log( M ^* / M _⊙ ) = ${7.49}_{-0.05}^{+0.04}$ , intrinsic star formation rate of ${2.8}_{-0.3}^{+0.4}$ M _⊙ yr ^−1 , and M _UV of −21.3 ${}_{-0.2}^{+0.2}$ , which is close to the knee of the luminosity function at that redshift. Our model, and corresponding magnification, shear, and convergence maps are available on request and will be made publicly available on MAST in a CANUCS data release (doi:10.17909/ph4n-6n76).

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