HerMES: Candidate Gravitationally Lensed Galaxies and Lensing Statistics at Submillimeter Wavelengths
Julie L. Wardlow, Asantha Cooray, Francesco De Bernardis, A. Amblard,, V. Arumugam, H. Aussel, A. J. Baker, M. B\'ethermin, R. Blundell, J. Bock, A., Boselli, C. Bridge, V. Buat, D. Burgarella, R. S. Bussmann, A., Cabrera-Lavers, J. Calanog, J. M. Carpenter, C. M. Casey, N.

TL;DR
This paper identifies and analyzes candidate gravitationally lensed submillimeter galaxies from Herschel survey data, providing statistical estimates of lensing rates, magnification factors, and implications for studying distant dusty galaxies.
Contribution
It presents a new catalog of 13 confirmed and 29 candidate lensed SMGs, along with a statistical model predicting lensing rates and magnifications, advancing understanding of high-redshift galaxy populations.
Findings
70% of candidates confirmed as lensed by follow-up observations
Model predicts 32-74% of candidates are strongly lensed
Lensed galaxies are magnified by factors around 9 on average
Abstract
We present a list of 13 candidate gravitationally lensed submillimeter galaxies (SMGs) from 95 square degrees of the Herschel Multi-tiered Extragalactic Survey, a surface density of 0.14\pm0.04deg^{-2}. The selected sources have 500um flux densities (S_500) greater than 100mJy. Gravitational lensing is confirmed by follow-up observations in 9 of the 13 systems (70%), and the lensing status of the four remaining sources is undetermined. We also present a supplementary sample of 29 (0.31\pm0.06deg^{-2}) gravitationally lensed SMG candidates with S_500=80--100mJy, which are expected to contain a higher fraction of interlopers than the primary candidates. The number counts of the candidate lensed galaxies are consistent with a simple statistical model of the lensing rate, which uses a foreground matter distribution, the intrinsic SMG number counts, and an assumed SMG redshift distribution.…
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.
