A boosted decision tree reweights neutrino Monte Carlo events in high-dimensional detector observables to match a target generator's distributions and efficiency for MINERvA charged-current quasielastic-like measurements.
NUISANCE: a neutrino cross-section generator tuning and comparison framework
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
NUISANCE is an open source C++ framework which facilitates detailed studies of neutrino interaction cross-section models implemented in Monte Carlo neutrino event generators. It provides a host of automated methods to perform comparisons of multiple generators to published cross-section measurements and each other. External reweighting libraries are used to allow the end-user to evaluate the impact of model parameters variations in the generators with data, or to tune the generator predictions to arbitrary dataset combinations. The design is modular and focusses on ease-of-use to allow new datasets and more generators to be added without requiring detailed understanding of the entire NUISANCE package. We discuss the motivation for the NUISANCE framework and suggested usage cases, alongside a description of its core structure.
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MINERvA measures antineutrino cross sections on multiple nuclei versus transverse momentum and finds significant model discrepancies indicating missing nuclear effects.
Adding two-body currents and updated axial form factors to a relativistic spectral function model increases predicted cross sections for neutrino-carbon scattering, with the LQCD+MINERvA fit overestimating data while the MINERvA-only fit gives a moderate rise and no configuration fits all datasets.
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
citing papers explorer
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Boosted decision tree reweighting of simulated neutrino interactions for $O(1)$ GeV neutrino cross section measurements
A boosted decision tree reweights neutrino Monte Carlo events in high-dimensional detector observables to match a target generator's distributions and efficiency for MINERvA charged-current quasielastic-like measurements.
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Measurement of Inclusive Charged-Current $\bar{\nu}_{\mu}$ Scattering on C, CH, Fe, and Pb at $\langle E_{\bar{\nu}}\rangle \sim$ 6 GeV with MINERvA
MINERvA measures antineutrino cross sections on multiple nuclei versus transverse momentum and finds significant model discrepancies indicating missing nuclear effects.
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Two-body current and axial form factor effects in charged-current quasielastic neutrino-nucleus scattering within the NEUT event generator
Adding two-body currents and updated axial form factors to a relativistic spectral function model increases predicted cross sections for neutrino-carbon scattering, with the LQCD+MINERvA fit overestimating data while the MINERvA-only fit gives a moderate rise and no configuration fits all datasets.
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Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.