Spitzer Imaging of Strongly-Lensed Herschel-Selected Dusty Star Forming Galaxies
Brian Ma, Asantha Cooray, J. A. Calanog, H. Nayyeri, N. Timmons, C., Casey, M. Baes, S. Chapman, H. Dannerbauer, E. L. Da Cunha, G. De Zotti, L., Dunne, D. Farrah, Hai Fu, J. Gonzalez-Nuevo, G. Magdis, M. J. Michalowski, I., Oteo, D. A. Riechers, D. Scott, M. W. L. Smith

TL;DR
This study analyzes six Herschel-selected gravitationally lensed dusty star-forming galaxies at redshifts 1-3, using multi-wavelength data to determine their stellar masses, star formation rates, and dust properties, revealing merger-driven star formation activity.
Contribution
The paper presents a method to disentangle foreground lens and background source fluxes in IRAC imaging using high-resolution data, enabling accurate SED modeling of lensed DSFGs.
Findings
Stellar masses range from 8x10^10 to 4x10^11 Msun.
Star formation rates are around 100 Msun/yr.
Systems are above the typical SFR-M* relation, indicating merger-driven star formation.
Abstract
We present the rest-frame optical spectral energy distribution and stellar masses of six Herschel- selected gravitationally lensed dusty, star-forming galaxies (DSFGs) at 1 < z < 3. These galaxies were first identified with Herschel/SPIRE imaging data from the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) and the Herschel Multi-tiered Extragalactic Survey (HerMES). The targets were observed with Spitzer/IRAC at 3.6 and 4.5um. Due to the spatial resolution of the IRAC observations at the level of 2 arcseconds, the lensing features of a background DSFG in the near-infrared are blended with the flux from the foreground lensing galaxy in the IRAC imaging data. We make use of higher resolution Hubble/WFC3 or Keck/NIRC2 Adaptive Optics imaging data to fit light profiles of the foreground lensing galaxy (or galaxies) as a way to model the foreground components, in order to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
