From the 2 of 18 linked papers with an AI index.
18 papers
Improved Approximations for Collective Neutrino Oscillations
Matthew Riccio, A. B. Balantekin
The paper develops algebraic techniques and a BBGKY hierarchy truncation to improve approximations for collective neutrino oscillations, offering a systematic method to go beyond m…
Estimating amplitude of matter density fluctuations in solar and supernova models using neutrino flavor evolution
Caroline Laber-Smith, Hansen Torres, Lily Newkirk +3
The paper uses statistical data assimilation to infer the amplitude of matter density fluctuations along neutrino paths in simplified solar and core‑collapse supernova models, show…
Gamma Backgrounds for Experiments at the High Flux Isotope Reactor
M. Andriamirado, A. B. Balantekin, C. Baldenegro +53
This article describes the deployment of a germanium detector at Oak Ridge National Lab's High Flux Isotope Reactor (HFIR) for the purpose of understanding the energy and spatial d…
Probing Long-Lived Particle Production in Muon Decays at the SNS with a Highly Capable Hydrocarbon Detector
M. Andriamirado, A. B. Balantekin, C. D. Bass +43
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is a prolific muon producer, making it an ideal location for studying dark sector particles produced in…
Three-flavor supernova neutrino simulation using a hybrid quantum-classical algorithm with qutrits
Daniel J. Heimsoth, A. Baha Balantekin, Pooja Siwach
We simulate a self-interacting three-flavor neutrino system within a core-collapse supernova using a hybrid classical-quantum algorithm on a qutrit computer. Based on the Dirac-Fre…
New Deep Learning Data Analysis Method for PROSPECT using GAPE: Genetic Algorithm Powered Evolution
M. Adriamirado, A. B. Balantekin, C. Bass +40
We propose a genetic algorithm powered evolution (GAPE) method to create deep learning solutions for energy and position estimation for reactor antineutrino interactions in the Pre…