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Machine Learning Neutrino-Nucleus Cross Sections II: More Leptons
Daniel C. Hackett, Joshua Isaacson, Shirley Weishi Li +2
Neutrino-nucleus cross sections are essential inputs for long-baseline neutrino oscillation experiments, yet remain challenging to model with high precision. Recent work demonstrat…
Direct calculation of parton distributions in momentum space from lattice QCD
Anthony V. Grebe, Daniel C. Hackett, Michael L. Wagman +2
Coulomb-gauge quasi-parton distributions can be computed directly in momentum space on a finite lattice, enabled by the commutativity of their renormalization and Fourier transform…
Learning the generating functional for variance reduction in lattice QCD
Ryan Abbott, Yang Fu, Daniel C. Hackett +3
The generating functional in quantum field theory provides the natural framework for constructing correlation functions as derivatives with respect to source operators. We present…
Variance reduction in lattice QCD observables via normalizing flows
Ryan Abbott, Denis Boyda, Yang Fu +5
Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a derivative with respect to action parame…
Excited-state uncertainties in lattice-QCD calculations of hadron masses and scattering phase shifts
William Detmold, Anthony V. Grebe, Daniel C. Hackett +4
Lattice QCD has historically produced energy results interpretable as either estimates relying on implicit assumptions about asymptotic behavior or one-sided upper bounds. New Lanc…
Excited-state uncertainties in lattice-QCD calculations of multi-hadron systems
William Detmold, Anthony V. Grebe, Daniel C. Hackett +4
Excited-state effects lead to hard-to-quantify systematic uncertainties in lattice quantum chromodynamics (LQCD) spectroscopy calculations when computationally accessible imaginary…