NUISANCE aims to provide a coherent framework for comparing neutrino generators to external data. NUISANCE can also tune cross-section parameters to available data.
Latest validated release : v1r0
Authors: Luke Pickering, Patrick Stowell, Callum Wilkinson, Clarence Wret
Developer mailing list: firstname.lastname@example.org
Documentation on the NUISANCE installation procedure is available here.
Multiple Generator Inputs
NUISANCE can currently handle inputs from the following generators:
Raw Generator Comparisons
The structure of the NUISANCE core classes promotes consistent comparison of different generators by converting each format into a common NUISANCE event format. Tools are included to convert these events into simple 'flat tree' formats that can be analysed with ROOT alone.
(left) Shape comparison. (right) Normalised cross-section comparison.
The NUISANCE tool "nuiscomp" can be used to generate comparisons of any of the different generators supported and any dataset class already implemented into the framework.
(left) MiniBooNE CCQE numu. (right) MINERvA CC1pi numu.
Automated Parameter Tuning
Generator ReWeight dials can be provided to NUISANCE to produce modified cross-section predictions. The "nuismin" application interfaces these reweight dials with ROOT's minimizer libraries to support automated model parameter tuning using various possible parameter estimation routines.
(left) Likelihood Scan. (right) Enu ANL Cross-section Data.
Cross-section Systematic Tools
The NUISANCE tool "nuissyst" is provided to support the study of cross-section systematics for neutrino experiments. Different routines are implemented to validate reweight parameter responses and generate systematic error bands from arbritrary covariance matrices for those parameters.
(left) Example 1-sigma reweight dial variations. (right) Likelihood distribution for all toy throws.
(left) Muon Momentum. (right) Muon Angle.