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Event Reweighting Tools

Event Reweighting Tools. Contents: Goals Reweighting Packages Usage & Reweight Friendly Packages Validation Caveats. Goals. Event reweighting provides a quick way to understand some of systematics present in an analysis due to uncertainties in physics models

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Event Reweighting Tools

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  1. Event Reweighting Tools Contents: • Goals • Reweighting Packages • Usage & Reweight Friendly Packages • Validation • Caveats

  2. Goals • Event reweighting provides a quick way to understand some of systematics present in an analysis due to uncertainties in physics models • The goal of this work was to provide a user-friendly package allowing people to study the effects of changing a range of model parameters • The package was developed to meet the needs of the MDC, however, it can easily be extended to incorporate new reweighting schemes

  3. Reweighting Packages • MCReweight (design advice: Costas) • Calculates total reweight factor given event & adjusted params • NeugenInterface (Hugh, Costas) • Contains classes which interface to fortran code • GnumiInterface • Correlates neutrino parent information with each event in the ntuples • BMPT classes (fortran from Mark M.) • Calculate cross-sections according to the BMPT model using neutrino parent kinematics

  4. Usage + Friendly Packages • Need a range of event variables: • For Neugen: • Neutrino 4-mom • Target 4-mom • Interaction type: nu-type, CC/NC, process • Initial State, Hadronic final state • For BMPT • Neutrino parent 4-mom • Parent ID • Examples of how to extract event quantities from the standard ntuples can be found in minossoft: • Mad • AnalysisNtuples

  5. Usage + Friendly packages • Both Neugen and BMPT models have a range of parameters that can be varied • 30 Neugen Parameters • Details: http://minos.phy.tufts.edu/gallag/meetings/02_01_05/weighting.html • 39 BMPT Parameters • Details: http://www.hep.caltech.edu/~smith/numu/Feb05/ • Therefore essential to only vary parameters in a meaningful way • Tools such as NuValidator can be employed for this An example of how to use MCReweight to vary the parameters can be found in the macros directory of the package

  6. Neugen Validation • Hugh produced two samples of events: • One with standard neugen parameters • One with a number of parameters varied • He showed that with NeugenInterface he could reproduce standard event distributions by reweighting the non-standard event set • This was then repeated in the MCReweight framework to validate the reweighting procedure

  7. Neugen Validation • Top: Em, Ehad; Bottom: x,y; Colours: Std, Non-Std, Rwt

  8. BMPT Validation • Attempted to reproduce the pion and kaon cross-sections as shown in the original paper • Pion cross-sections reproduced well

  9. BMPT Validation • Kaons however are slightly off • Kinematic variable used in code is not the same as that used in the paper • However, fortran code used to generate MDC files has the same feature....

  10. Caveats, etc. • General Caveat: • It is impossible to use reweighting to study previously unpopulated regions of phase space • Sounds obvious now... • Would be useful to produce flat distributions so that reweight studies are not statistically limited (or impossible) • If reweighting become more widely used, it will be essential to keep track of parameters used to generate event samples • e.g. MC header block to hold neugen parameters • BMPT specific caveats: • Not currently keeping track of whether a neutrino is from a primary, secondary or tertiary interaction • However for MDC any model that can describe ND data can still be used to predict FD at some level

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