Predictions for all-energy neutrino structure functions
Project description
NNSFν
NNSFν is a python module that provides predictions for neutrino structure functions. It relies on YADISM for the large-Q region while the low-Q regime is modelled in terms of a Neural Network (NN). The NNSFν determination is also made available in terms of fast interpolation LHAPDF grids that can be accessed through an independent driver code and directly interfaced to the GENIE Monte Carlo neutrino event generators.
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Citation
To refer to NNSFν in a scientific publication, please use the following:
@article {reference_id,
author = {A. Candido, A. Garcia, G. Magni, T. R. Rabemananjara, J. Rojo, R. Stegeman},
title = {Neutrino Structure Functions from GeV to EeV Energies},
year = {2023},
doi = {10.1101/2020.07.15.204701},
eprint = {https://arxiv.org/list/hep-ph/},
journal = {aRxiv}
}
And if NNSFν proved to be useful in your work, consider also to reference the codes:
@article {reference_id,
author = {A. Candido, A. Garcia, G. Magni, T. R. Rabemananjara, J. Rojo, R. Stegeman},
title = {Neutrino Structure Functions from GeV to EeV Energies},
year = {2023},
doi = {10.1101/2020.07.15.204701},
}
Project details
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