1. Mark Dorman UCL/RAL MINOS WITW June 05 An Update on Using QE Events to Estimate the Neutrino Flux and Some Preliminary Data/MC Comparisons for a QE Enriched Sample ● Review of motivation ● Update on QE sample selection ● Results for a high statistics MC set ● Data/MC comparisons

2. Mark Dorman UCL/RAL MINOS WITW June 05 Motivation ● The x-sec for DIS events is fairly well known at high energies (~20GeV) and it is easy to select a sample of DIS events at this energy. The DIS x-sec can be 'divided out' of such a sample to give an estimate of the neutrino flux at this energy. ● The shape of the QE x-sec is well known and is flat down to ~1GeV but the normalization of this x-sec is not so well known. The DIS flux estimate can be used to 'pin' the normalization of the QE x-sec. ● Using the flat shape of the QE x-sec the neutrino flux can be estimated as a function of energy by again 'dividing out' the x-sec from samples of QE events in a series of reconstructed energy bins.

3. Mark Dorman UCL/RAL MINOS WITW June 05 QE Sample Selection Shape for all events reflects total interaction x-sec Asymmetric binning to reflect energy resolution and ensure adequate numbers of events in each bin to make pdfs ● I am using a method of maximum likelihood in a series of reconstructed neutrino energy bins from 0-20GeV to identify QE events. ● The following plots briefly recap the variables that go into the ML analysis. They correspond to a MC sample that was generated with a flat energy spectrum:

4. Mark Dorman UCL/RAL MINOS WITW June 05 QE Sample Selection ● The first two variables that go into the likelihood analysis are just the numbers of reconstructed tracks and showers – generally events with no tracks are likely not to be QE and events with no showers are likely to be QE. ● I also use the reconstructed invariant mass squared: Large numbers of DIS events due to large flux out to 20GeV and dominance of DIS x-sec (black=QE, blue=RES and red=DIS) ● Now want to consider event topology and PH distributions near to the vertex to try to distinguish between QE (proton), RES (proton+pion) and DIS (pions) events.

5. Mark Dorman UCL/RAL MINOS WITW June 05 QE Sample Selection ● I remove the main muon track from an event (if there was one) as well as hits that occur more than 2m in z from the vertex (protons and pions will not travel further than this) and 'crosstalk-like' hits (defined as having PH<1.5pe). ● I then define several variables: ➢ The number of high PH hits (>20pe) remaining ➢ The total PH of the remaining hits ➢ Total remaining PH as a fraction of total event PH (similar to y)

6. Mark Dorman UCL/RAL MINOS WITW June 05 QE Sample Selection ● Black = QE ● Blue = RES ● Red = DIS ● These two variables are highly correlated and so I combined them into a single 1D pdf using a toy principal components analysis.

7. Mark Dorman UCL/RAL MINOS WITW June 05 ● In each case the low energy events are the hardest to discriminate between. ● For all energy ranges the RES events are much harder to remove than the DIS events. ● The final variable I am using for a pdf is obtained by performing a Hough transform on the remaining hits and taking the height of the peak.

8. Mark Dorman UCL/RAL MINOS WITW June 05 PID Results ● I then form a QE PID parameter for each energy bin based on the probabilities outputted from the ML analysis in that bin. ● Using the first half of the MC events to make the pdfs and running the second half through the analysis gives the following:

9. Mark Dorman UCL/RAL MINOS WITW June 05 Further Work ● There are several unfolding methods that could be used to get a flux estimate from a QE sample – these have not been looked into fully yet. Data/MC Comparisons for a QE Enriched Sample ● I have run samples of pME data and MC (R1.16) through the MLPID analysis in order to take a first look at some physics distributions for a QE enriched sample. ● In what follows all distributions have been normalized using POTs: ➢ Data – 1.21e18 POTs from May after 'good beam' cuts: abs(hornI)>0.1 -2.0<hpos2<0.0 -1.0<vpos2<2.0 closest spill <2.0 ➢ MC – 0.90e18 POTs

10. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s MC ● First I used half of the pME MC to construct my pdfs and then ran the remaining half through the MLPID analysis to see what sort of purities to expect: Due to flux and x-sec I only had enough statistics to look in the 2-10 GeV range The resulting efficiencies (black) and purities (red) look worse than those for my previous flat energy spectrum sample – am not sure yet why this is the case. ● The following sample of QE-like events using the MC for pdfs and running the data through the analysis should be ~60% QE events.

11. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s Data ● Reconstructed neutrino energy: MC seems to be shifted by ~0.5GeV above data. Black = data, Red = MC

12. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s Data ● Reconstructed muon energy: MC seems to be shifted by ~0.5GeV above data. Black = data, Red = MC

13. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s Data ● Reconstructed shower energy: MC seems to be shifted by ~0.1GeV below data. Black = data, Red = MC

14. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s Data ● Reconstructed y: MC seems to be shifted towards slightly lower y. Black = data, Red = MC

15. Mark Dorman UCL/RAL MINOS WITW June 05 pME MC v.s Data ● Reconstructed Q^2: MC seems to be shifted towards slightly lower Q^2. Black = data, Red = MC