SIREN: An open-source neutrino injection toolkit

Abstract

Modeling of rare neutrino processes often relies on either simple approximations or expensive detector simulations. The former is often not sufficient for interactions with complex morphologies, while the latter is too time-intensive for phenomenological studies. We present SIREN (Sampling and Injection for Rare EveNts), a new tool for neutrino phenomenology and experimental searches alike that enables accurate interaction and detector geometry modeling without the overhead of detailed detector response simulations. SIREN handles the injection of rare process final states and the associated weighting calculations with the speed needed for phenomenological investigations and the detail necessary for dedicated experimental searches. The extensible design of SIREN allows it to support a wide range of experimental designs and Beyond Standard Model neutrino interactions. Users need only specify the physical process, detector geometry, and initial neutrino flux under consideration before they can accurately simulate a model in their detector of choice. We demonstrate the capability of SIREN through two examples: (1) Standard Model ${\nu }_{\mu }$ deep inelastic scattering in IceCube, DUNE, and ATLAS; and (2) heavy neutral lepton interactions in MiniBooNE, MINERνA, and CCM. A variety of detector geometry descriptions, interaction cross sections, and neutrino fluxes are also provided for users to get started with immediately.

Program summary

Program Title: SIREN

CPC Library link to program files: https://doi.org/10.17632/j8mftngm5m.1

Developer's repository link: https://github.com/Harvard-Neutrino/SIREN

Licensing provisions: GNU Lesser General Public License, v3

Programming Language: C++17, Python

External Routines: Boost, HDF5, pybind11, Photospline, SuiteSparse, DarkNews

Nature of problem: Injection and reweighting of neutrinos and rare-processes across diverse experiments and models.

Solution method: An extensible framework for injection and weighting of rare processes with detailed material and geometry modeling and built-in support for a variety of experiments and models.