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GENIE NUISCOMP

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The NUISANCE minimizer application can be used to tune MC models by directly comparing with published scattering data and using ROOT's minimizer libraries to find a best fit parameter set.

Wiki content

1. Page BUILD Built
2. GENIE NUISCOMP
3. PAGE BEING BUILT
   1. Running NUISMIN
   2. Running a GENIE Minimization
      1. Preparing Event Samples
      2. Choosing our samples
      3. Setting up our reweight dials
      4. Running the minimiser (Migrad)
      5. Analysing the output
   3. Alternative Fitting Routines
      1. Running GSL Minimiser Routines
      2. Fixing dials at limits
      3. Running a 1D likelihood scan
      4. Running a 2D likelihood scan
      5. Running a Contour Scan
      6. Generating Post-fit Error Bands
   4. Running a fake data fit

Running NUISMIN

Author: Patrick Stowell

Date: June 2017

Versions: NUISANCE v2r0, GENIE 2.12.6

The following example details how to run NUISANCE and tune a simple model to MiniBooNE_CCQE_XSec_1DQ2_nu data, with additional examples on how to include penalty terms and perform fake data fits.

Each generator requires very slightly different ways to handle NUISANCE, therefore multiple versions of this tutorial have been provided. Please use the following links to choose what generator you would like to use.

• I want to use GENIE

Running a GENIE Minimization

Preparing Event Samples

Choosing our samples

Setting up our reweight dials

Defining Free dials

Checking dial response

Specifying fixed dials

Running the minimiser (Migrad)

How Migrad works

Signal Reconfigures

Saving Nominal Prediction

Analysing the output

Data/MC Comparisons

Iteration Tree

Parameter Tuning Plots

Alternative Fitting Routines

Running GSL Minimiser Routines

Fixing dials at limits

Running a 1D likelihood scan

Running a 2D likelihood scan

Running a Contour Scan

Generating Post-fit Error Bands

Running a fake data fit