6 papers
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…
Improving Neutrino Oscillation Measurements through Event Classification
Sebastian A. R. Ellis, Daniel C. Hackett, Shirley Weishi Li +2
Precise neutrino energy reconstruction is essential for next-generation long-baseline oscillation experiments, yet current methods remain limited by large uncertainties in neutrino…
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.…
Machine Learning Neutrino-Nucleus Cross Sections
Daniel C. Hackett, Joshua Isaacson, Shirley Weishi Li +2
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections rema…
Simulation-based inference for neutrino interaction model parameter tuning
Karla Tame-Narvaez, Aleksandra ÄiprijanoviÄ, Steven Gardiner +1
High-energy physics experiments studying neutrinos rely heavily on simulations of their interactions with atomic nuclei. Limitations in the theoretical understanding of these inter…
Leveraging intermediate resonances to probe CP violation at colliders
Innes Bigaran, Joshua Isaacson, Taegyun Kim +1
We explore the phenomenological impact of interference in tree-level contributions to three-body final states in scattering processes. This work introduces a novel search…