9 papers
Strong Lensing Cosmology with Population-level Calibrated Neural Ratio Estimation
Sreevani Jarugula, Brian D. Nord, Aleksandra Ćiprijanović +1
Strong gravitational lensing contains key information about cosmic acceleration. Modern and next-generation galaxy imaging surveys are expected to provide high-quality data on $\ma…
Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model
Karla Tame-Narvaez, Aleksandra ÄiprijanoviÄ, Shubhendu Trivedi
Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galaxy property estimation. However…
Prospects for Astrobiology and Technosignature Searches with the Vera C. Rubin Observatory Legacy Survey of Space and Time
Andjelka B Kovacevic, Nigel J. Mason, Aleksandra Ciprijanovic +4
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will map sources in multiband colour--variability space. We present a prototype coherence-based framework for a…
First Estimation of Model Parameters for Neutrino-Induced Nucleon Knockout Using Simulation-Based Inference
Karla Tame-Narvaez, Steven Gardiner, Aleksandra ÄiprijanoviÄ +1
To enable an accurate determination of oscillation parameters, accelerator-based neutrino experiments require detailed simulations of nuclear interaction physics in the GeV regime.…
SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks
Sneh Pandya, Purvik Patel, Brian D. Nord +2
Modern neural networks (NNs) often do not generalize well in the presence of a "covariate shift"; that is, in situations where the training and test data distributions differ, but…
Deep inference of simulated strong lenses in ground-based surveys
Jason Poh, Ashwin Samudre, Aleksandra ÄiprijanoviÄ +3
The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dar…