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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…
The Dark Energy Survey Supernova Program: Cosmological biases from supernova photometric classification
M. Vincenzi, M. Sullivan, A. Möller +81
Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN…
Cosmic Shear in Harmonic Space from the Dark Energy Survey Year 1 Data: Compatibility with Configuration Space Results
H. Camacho, F. Andrade-Oliveira, A. Troja +96
We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spect…
Dark Energy Survey Year 3 results: Cosmology with peaks using an emulator approach
D. Zürcher, J. Fluri, R. Sgier +119
We constrain the matter density and the amplitude of density fluctuations within the CDM cosmological model with shear peak statistics and angular converg…
Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps
M. Gatti, B. Jain, C. Chang +107
We present a cosmological analysis using the second and third moments of the weak lensing mass (convergence) maps from the first three years of data (Y3) data of the Dark Energy Su…