246 citations · 2.7k across the 36 of their papers we have counts for
37 papers
Narrowing down the Hubble constant value by exploiting the extended surface brightness of the supernova Refsdal host galaxy
S. Schuldt, C. Grillo, S. H. Suyu +7
We present the first inference of the Hubble constant and matter density parameter from a strongly lensed supernova by exploiting the mass model of a galaxy cluster enhanced by an…
HOLISMOKES XX. Lens models of binary lens galaxies with five images of Supernova Winny
L. R. Ecker, A. G. Schweinfurth, R. Saglia +13
Strongly lensed supernovae (SNe) provide a powerful way to study cosmology, SNe and galaxies. Modelling the lens system is key to extracting astrophysical and cosmological informat…
Cosmology with supernova Encore in the strong lensing cluster MACS J0138-2155: Lens model comparison and H0 measurement
S. H. Suyu, A. Acebron, C. Grillo +28
MACS J0138-2155 is the only known cluster to strongly lens two supernovae (SNe), Requiem and Encore, from the same host galaxy at z=1.949. We present seven independent mass models…
GPU-Accelerated Gravitational Lensing & Dynamical (GLaD) Modeling for Cosmology and Galaxies
Han Wang, Sherry H. Suyu, Aymeric Galan +4
Time-delay distance measurements from strongly lensed quasars provide a robust, independent method for determining the Hubble constant (). This approach cross-checks est…
Cosmology with supernova Encore in the strong lensing cluster MACS J01382155: photometry, cluster members, and lens mass model
S. Ertl, S. H. Suyu, S. Schuldt +23
The strongly lensed Supernova (SN) Encore at a redshift of , discovered behind the galaxy cluster MACS J01382155 at , provides a rare opportunity for time-de…
The missing quasar image in the gravitationally lensed quasar HE02302130: Implications for the cored lens mass distribution and dark satellites
S. Ertl, S. Schuldt, S. H. Suyu +3
Strongly lensed systems with peculiar configurations allow us to probe the local properties of the deflecting lens mass while simultaneously testing general profile assumptions. Th…