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DeepZipper: A Novel Deep Learning Architecture for Lensed Supernovae Identification
Robert Morgan, B. Nord, K. Bechtol +48
Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectro…
Lensing Without Borders. I. A Blind Comparison of the Amplitude of Galaxy-Galaxy Lensing Between Independent Imaging Surveys
A. Leauthaud, A. Amon, S. Singh +104
Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals () across different data-sets and to carry out end-to…
Finding quadruply imaged quasars with machine learning. I. Methods
A. Akhazhanov, A. More, A. Amini +68
Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique inform…
Accuracy of environmental tracers and consequence for determining the Type Ia Supernovae magnitude step
M. Briday, M. Rigault, R. Graziani +12
Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential ast…
Out of One, Many: Distinguishing Time Delays from Lensed Supernovae
Mikhail Denissenya, Satadru Bag, Alex G. Kim +2
Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images a…
The Observed Evolution of the Stellar Mass - Halo Mass Relation for Brightest Central Galaxies
Jesse B. Golden-Marx, C. J. Miller, Y. Zhang +73
We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $…