How to add a sample in NUISANCE

This is an informal step-by-step guide on how to add samples into the NUISANCE framework.

Using: NUISANCE v1r0, NEUT 5.3.6

For this tutorial I'll be adding the T2K CC1pi+ H2O data. The data comes from ​the T2K site and ​arxiv. The data is supplied both in a ROOT file and a number of .csv files; I'll be using the ROOT file here.

Examining the data and choosing distributions

Finding the neutrino flux and generating events

The first issue at hand is to find the flux for the experiment. If we don't have this (or its very difficult to find), there is simply no way to reproduce the results (unless the measurement is a total cross-section without any phase space cuts).

A quick search through the document finds it is documented in reference [12]. You could also find it in our flux list.

I then generate NEUT 5.3.6 events with a suitable card-file (see our NEUT guide), making sure I've chosen the correct target (water) and flux, and that I've made the model selections I want (e.g. Rein-Sehgal or Berger-Sehgal coherent model).

I normally generate around 1M events with all interaction modes turned on. This way I'll make sure to get all interaction modes into the topological cross-section (e.g. I'll get a small amount of CCQE events which excite a pion from a secondary nucleon interaction, leading to a CCQE+1pi ~ CC1pi+ final state, which is signal)

Choosing a distribution

The T2K CC1pi+ H2O data release contains various distributions in FIG 4. In this tutorial I'll look at adding one kinematic distribution and one derived distribution: p_mu and E^{rec}_nu.

Generally speaking, we try to add all available distributions in a publication. However some distributions will have detector effects "folded" into them (i.e. they will be raw detector-level data). We can only use these if there is some method (e.g. a smearing matrix) which bring detector-level variables (e.g. p_mu seen in the detector) to truth-level variable (e.g. p_mu seen after correcting for the detector effects).