Status of QEL Analysis ● QEL-like Event Selection and Sample ● ND Flux Extraction ● Fitting for MINOS Collaboration Meeting FNAL, 7 th -10 th December '06 Mark Dorman UCL / RAL

QEL-like Event Selection – W (or ) Cut Apply cut at W<1.3 ● Large data excesses compared to MC and slight shift to higher in data. ● Cedar and Daikon are an improvement here but cannot resolve the differences.

QEL-like Event Selection – = 0 ● Much more pure QEL sample than including events with small showers. ● Shape improvements with Daikon for muon angle distribution.

PDF-Based Selection with Cedar and Daikon ● Make PID for different MC settings. ● Select events from independent sample with each of these PIDs to compare.

Flux Extraction Methodology ● come from NEUGEN. ● are the selection efficiencies estimated with MC. ● is the number of NC events at neutrino energy E where refers to the MC flux. ● There is a partial energy unfolding as the equation is utilized in bins of reconstructed energy but the denominators in the efficiencies are are equal to the numbers of events generated in true energy bins. ● It is impossible to remove the MC flux from this equation and so the next step is to iterate until some convergence criterion for is met.

Current Status of Flux Measurement ● Have not yet repeated the flux analysis with Cedar/Daikon but will do as more statistics become available. ● Changes in the energy spectrum translate into changes in the extracted flux so can get some idea of implications of Cedar/Daikon from these.

and the QEL Cross Section ● A, B and C depend on (amongst other things) the axial vector form factor of the nucleon which can be written as: ● The quasi-elastic axial vector mass can be treated as the one free parameter of this differential cross section and so the QEL-like sample distribution can be used to fit this constant. known from neutron decay experiments MINOS nominal value is 1.032, K2K recently fitted to get 1.2

'Fitting' for ● I have reweighted a MC sample for various different values: ● I then take an independent sample weighted to a different value and use the ROOT - test to map out the v.s. space. ● I then fit the minimum with a quadratic to extract a best fit. W<1.3 Selection

'Fitting' for ● Mock data set – Cedar/Carrot, *1.057 ● Fit returns: From looking for ∆ = 1 ● Mock data set – Cedar/Daikon, ● Fit returns: ● Slightly low, expected(?) with updated form factors (+ other changes) in Daikon.

'Fitting' for ● This is only a preliminary step and there are many things to consider for further work such as: ● The main goal here is to try to combine fits for cross section parameters that affect the shape and normalization of the QEL-like sample into the iterative flux extraction. ● For flux extraction need to know:, ● Also need to factor in INTRANUKE reweighting... ● Fitting distributions in bins of and comparing/combining results. ● Which QEL sample selection to use (statistics v.s. purity v.s....). ● Adding other cross section parameters to affect the non-QEL events such as or the KNO parameters. ● More rigorous approach constructing # event predictions based on cross section formula, flux, sample efficiencies/purities, conversion from:

Summary ● Data/MC QEL-like sample discrepancies remain in Cedar/Daikon. So far detector/instrumentation effects have been ruled out as a possible solution – still some to do however... ● Starting to play with cross-section parameter fitting for the QEL-like sample although this is only very preliminary. ● Will re-extract ND flux using Cedar/Daikon as statistics increase. Need to implement iterative flux extraction and possibly incorporate fitting for cross-section parameters into this method. ● Different INTRANUKE samples were interesting for Birch/Carrot and had a big effect on the QEL-like sample and extracted flux. Will redo studies in Cedar/Daikon with new reweighting scheme.