Using Cafana to do DUNE-prism fit - Weve been using Cafana for fits - - PowerPoint PPT Presentation

• We’ve been using Cafana for fits so far to demonstrate the power of DUNEprism.
• Moving forward, we will need to do off-axis fit, which means including large

number of off-axis samples with many corrections and systematics.

• Will show what I did using Cafana for previous studies and how to proceed.

Using Cafana to do DUNE-prism fit

• Loading dependent library
• CAF-related and all needed libraries containing necessary classes
• Set up oscillation adjustable
• structure containing oscillation parameters with values, other objects

can take the values from the adjustable. Oscillation values can be set up in any pace in the fitter.

• Spectrum Loader → LoaderForRunPOT(runnumber)
• loader takes run number, the data tree could contain different run

numbers meaning different samples, like numu, nue, NC etc.

• DUNENoExtrpPredictionGenerator (loaders, RecoAxis, cuts) :
• loaders are from above.

Reco Axis and cuts are defined by users. IpredictionGenerator

• Takes loader, axis in reco. and cuts needed to use
• PredictionInterp (syst vec., Osc, PredictionGenerator, syst. shift, weight)
• Set up Prediction with systematics vectors, Prediction Generator,

some specific systematic shifts and weights.

Loading stage 1: preparation

• PredictionGenerator → Generate (loaders, Syst. Shift, weight)
• Pass loaders, reco axis, cuts, Syst. Shift to PredictionNoExtrap
• Syst. Shift can change the event weights/records

depending on the kind of systematics one set up. → PredictionNoExtrp

• Pass loader, reco axis, cut, shift and weight to PredictionExtrap

→ PredictionExtrap

• Passing to TrivialExtrp

→ TrivialExtrp

• Passing loader, reco axis, cut, shift and weights to Oscillatable

spectrum along with selection of neutrino flavor and charge → Oscillatable Spectrum → Reweightable Spectrum

• Takes reco axis building a reco axis vs. true axis 2D hist.

But the histogram is filled later. Also add spectrum to loader.

• Prediction Loader → Go
• Process all the tree branches, Fill in reco vs. true histogram for

each reweightable spectrum.

Loading stage 2 : Generate adjustable prediction

Set up IoscCalculatorAdustable Set up Isyst vector Spectrum Loader → loaderForRunPOT DUNENoExtrpPredictionGenerator (loaders, axis, cut) : IpredictionGenerator IpredictionGenerator::Generate → PredictionNoExtrp → PredictionExtrap → TrivialExtrp → Oscillatable Spectrum (fHist keeps reco vs. true) → Reweightable Spectrum → Add to loader PredictionInterp (syst vec., Osc, PredictionGenerator→Generate , syst shift, weight) Spectrum Loader → Go : Handle File → Syst. Shifts (1,2,3 sigma for systs.) PredictionInterp → SaveTo

Fitting stage (taking histograms) Loading stage (Can handle event-by-event)

Prepare Prediction and Data spectra Single experiment → PredictionInterp + fake spectrum Multiple experiment → single experiment Minimization

(Osc, from, to): Oscillation probability → Weighting spectrum

Oscillation

Full picture

Syst. FD ND Pred Data Pred Data Osc (Extrap)

• Syst. Shifu

(Interp.) Single Exp. Single Exp.

• Multjple. Exp.

Pre-loaded fmux + cross sectjon + user defjned

loading stage fjttjng stage

• The loading stage is event-by-event based.
• When go into fjttjng stage, no more single event informatjon
• > all needed informatjon should be stored in histogram format (all syst.)
• > Oscillatjon is calculated on fmight when fjttjng with probability histograms

true-reco true-reco

Current way Of Cafana

Fill in spectra Fill in spectra Fill in spectra

Syst. FD Data Data Osc (Extrap)

• Syst. Shifu

(Interp.) Single Exp.

Pre-loaded fmux + cross sectjon + user defjned

loading stage fjttjng stage

• All burden gives to predicted FD. Needs pre-calculated stufg at loading stage:
• C with difgerent oscillatjon
• effjciency with difgerent syst., but there are a lot of systs.
• fmux correctjon with difgerent syst. and oscillatjon, lots of variatjons.

Effjciency FD and ND Flux correctjon ND C factor

Off-axis Cafana

Fill in spectra Fill in spectra Fill in spectra Fill in spectra

Off-axis Cafana

• Fitting takes histograms, so we need to implement all ingredients in advance in

Spectrum shift format, such as systematics variations, efficiency corrections (as function of systematics), flux corrections (as function of systematics), c factors (as function of oscillation).

• Moreover, reco vs. true histogram in pre-filled and not change in fitting stage.
• If doing event-by-event fit, one just needs to include weights in single events

containing all necessary factors, like systematics weight, C factor weight, efficiency weight, flux weight etc. → Can we use Double Chooz fitter (I am familiar with) or MaCh3 ?