15 citations · 30 across the 12 of their papers we have counts for
6 papers · 1 filter
Fundamental Microscopic Properties as Predictors of Large-Scale Quantities of Interest: Validation through Grain Boundary Energy Trends
Benjamin A. Jasperson, Ilia Nikiforov, Amit Samanta +3
Correlations between fundamental microscopic properties computable from first principles, which we term canonical properties, and complex large-scale quantities of interest (QoIs)…
High-Precision Excited-State Nuclear Recoil Spectroscopy with Superconducting Sensors
C. Bray, S. Fretwell, L. A. Zepeda-Ruiz +30
Superconducting sensors doped with rare isotopes have recently demonstrated powerful sensing performance for sub-keV radiation from nuclear decay. Here, we report the first high-re…
Signal processing and spectral modeling for the BeEST experiment
Inwook Kim, Connor Bray, Andrew Marino +35
The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay…
Cross-scale covariance for material property prediction
Benjamin A. Jasperson, Ilia Nikiforov, Amit Samanta +4
A simulation can stand its ground against experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of predicti…
Direct Experimental Constraints on the Spatial Extent of a Neutrino Wavepacket
Joseph Smolsky, Kyle G Leach, Ryan Abells +35
Despite their high relative abundance in our Universe, neutrinos are the least understood fundamental particles of nature. They also provide a unique system to study quantum cohere…
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields
Joshua A. Vita, Amit Samanta, Fei Zhou +1
Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computatio…