191 citations
- University of ChicagoUS5 papers
- University of Wisconsin–MadisonUS5 papers
- Fermi National Accelerator LaboratoryUS4 papers
- SLAC National Accelerator LaboratoryUS4 papers
- Stanford UniversityUS4 papers
- University College LondonGB4 papers
- University of Illinois Urbana-ChampaignUS4 papers
- Kavli Institute for Particle Astrophysics and CosmologyUS3 papers
- Ludwig-Maximilians-Universität MünchenDE3 papers
- National Center for Supercomputing ApplicationsUS3 papers
- The University of QueenslandAU3 papers
- Universidad Autónoma de MadridES3 papers
5 papers · 1 filter
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…
SOAR/Goodman Spectroscopic Assessment of Candidate Counterparts of the LIGO-Virgo Event GW190814
Douglas Tucker, Matthew Wiesner, Sahar Allam +140
On 2019 August 14 at 21:10:39 UTC, the LIGO/Virgo Collaboration (LVC) detected a possible neutron star-black hole merger (NSBH), the first ever identified. An extensive search for…
lenstronomy II: A gravitational lensing software ecosystem
Simon Birrer, Anowar J. Shajib, Daniel Gilman +18
lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the li…
Expediting DECam Multimessenger Counterpart Searches with Convolutional Neural Networks
Adam Shandonay, Robert Morgan, Keith Bechtol +11
Searches for counterparts to multimessenger events with optical imagers use difference imaging to detect new transient sources. However, even with existing artifact detection algor…
deeplenstronomy: A dataset simulation package for strong gravitational lensing
Robert Morgan, Brian Nord, Simon Birrer +2
Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more exa…