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CC0pi/CC-inclusive Data Comparisons Patrick Stowell Introduction - PowerPoint PPT Presentation

CC0pi/CC-inclusive Data Comparisons Patrick Stowell Introduction Learnt from the previous round of NIWG fits that there are tensions within our current models between the external data sets. Work since then has been trying to understand


  1. CC0pi/CC-inclusive Data Comparisons Patrick Stowell

  2. Introduction • Learnt from the previous round of NIWG fits that there are tensions within our current models between the external data sets. • Work since then has been trying to understand what causes some of these problems. • Aim: Find a cross-section model that is capable of explaining a broad range of the published datasets and try to relieve the tensions. - 10/07/2016 2 Patrick Stowell

  3. Updated PGoF Fits • Recap: MiniBooNE and MINERvA joint fits show a disagreement on best fit model parameters. NEUTs model cannot describe both simultaneously. • MINERvA updated their flux which helped a little bit, but there are still issues! MINERvA Flux Update After and Before Joint Fits PGoF • PGOF Results: - 12/07/2016 3 Patrick Stowell

  4. XSecFitter: Generic Fitting Framework • Takes a long time to implement new models into generators, easier to take advantage of what is already setup in generators. • Want to make comparisons/tunings of these different generators in a completely consistent and reliable way. • Fitter Callum initially developed for NIWG NEUT fits provides a framework to allow new dataset comparisons and tunings to be added very quickly. • Restructured the code to turn it into a generic generator fitting package. • Contains a broad range of implemented data/MC comparisons. Name is a work in progress! Suggestions welcome! - 12/07/2016 4 Patrick Stowell

  5. ReWeight Dial Tuning • Fake data study tools. • Multiple inputs: • NEUT • NuWro • GENIE • NUANCE – Coming Soon… • GiBUU – Coming Soon… • Interface with generator reweight utilities to do tuning. • Moving to spline reweighting soon to allow for more rigorous model testing. - 12/07/2016 5 Patrick Stowell

  6. Systematic Analysis • Lots of fitter development ongoing, added options to generate systematic throws from an arbitrary covariance. Ratio NIWGMEC_Norm_Other DATA NIWG 2015 MC stat. 1.8 NIWG2014a_Eb_Pb208 1 NIWG2014a_Eb_Fe56 NIWG2014a_pF_Pb208 NIWG2014a_pF_Fe56 NIWG2012a_ncotherE0 0.8 1.6 NIWG2012a_nccohE0 NIWG2012a_cccohE0 NIWG2012a_cccohE0 NIWG2012a_dismpishp 0.6 NIWG2012a_ccnueE0 1.4 NXSec_BgSclCCRES NXSec_MaNFFRES NXSec_CA5RES 0.4 NIWG2014a_Eb_O16 NIWGMEC_Norm_O16 1.2 NIWG2014a_pF_O16 NIWG2014a_Eb_C12 NIWGMEC_Norm_C12 0.2 NIWG2014a_pF_C12 NXSec_MaCCQE 1 NCasc_FrCExHigh_pi NCasc_FrCExLow_pi 0 NCasc_FrAbs_pi NCasc_FrPiProd_pi NCasc_FrInelHigh_pi 0 0.2 0.4 0.6 0.8 1 1.2 1.4 NCasc_FrInelHigh_pi NCasc_FrInelHigh_pi NCasc_FrInelHigh_pi NCasc_FrPiProd_pi NCasc_FrAbs_pi NCasc_FrCExLow_pi NCasc_FrCExHigh_pi NXSec_MaCCQE NIWG2014a_pF_C12 NIWGMEC_Norm_C12 NIWG2014a_Eb_C12 NIWG2014a_pF_O16 NIWGMEC_Norm_O16 NIWG2014a_Eb_O16 NXSec_CA5RES NXSec_MaNFFRES NXSec_BgSclCCRES NIWG2012a_ccnueE0 NIWG2012a_dismpishp NIWG2012a_cccohE0 NIWG2012a_cccohE0 NIWG2012a_nccohE0 NIWG2012a_ncotherE0 NIWG2014a_pF_Fe56 NIWG2014a_pF_Pb208 NIWG2014a_Eb_Fe56 NIWG2014a_Eb_Pb208 NIWGMEC_Norm_Other Reconstructed Bjorken x Ratio Ratio 1.6 1.4 DATA NIWG 2015 MC stat. NIWG 2015 MC stat. DATA 1.5 1.3 1.4 1.2 1.3 1.1 1.2 1 1.1 0.9 1 0.8 0.9 0 0.2 0.4 0.6 0.8 1 1.2 1.4 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Reconstructed Bjorken x Reconstructed Bjorken x • Should be shown as a standard for any model tuning so users can judge whether the fit parameters are actually appropriate for their analysis. - 11/07/2016 6 Patrick Stowell

  7. Experimental Collaboration • Working to release this as publicly available software soon. • Fitter tools will be freely available to use. • Interested in more direct correspondence with experiments so we can properly test our cross-section models. You get a You get a You all get a comparison! comparison! comparison! - 12/07/2016 7 Patrick Stowell

  8. Using NuWro • Included NuWro as a possible input. This opens up a range of extra models aswell as providing a nicer C++ interface to prototype model changes. • LFG Model • Alternative Form Factors • Marteau MEC • Alternative FSI Model • NC TEM MEC tunings • NuWro reweight module developed to allow systematic studies to be performed. • • Myself, Luke Pickering, and Jan Sobczyk, working to get this released soon! NuWro ReWeight Validation L. Pickering - 10/07/2016 8 Patrick Stowell

  9. NuWro LFG Fits • Want to see whether the fitter inflating M A and reducing MEC normalization is just a result of the stitched together RFG+Nieves model in NEUT. • Compare 3 models: • NEUT RFG + RPA + Nieves • NuWro LFG + RPA + Nieves Found to be the best fit to MINERvA • NuWro RFG + TEM CCQE data in original data release. • In each model fit 2 free parameters: • Axial Mass Removed pF dial as NuWro RW • MEC Normalisation doesn’t have this yet. - 12/07/2016 9 Patrick Stowell

  10. Fit Results MINERvA NUMU MINERvA NUMUBAR 39 − × 10 − 39 × 10 ) 2 20 ) Data 16 /GeV 2 Data /GeV 18 MC NuWro LFG+RPA+Nieves 14 MC NuWro LFG+RPA+Nieves 16 2 (cm 2 MC NuWro RFG+TEM (cm MC NuWro RFG+TEM 12 14 MC NEUT RFG+RPA+Nieves MC NEUT RFG+RPA+Nieves QE 10 12 QE 2 2 /dQ /dQ Area Normalized Area Normalized 10 8 σ σ 8 d d 6 6 4 4 2 2 0 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2 2 Q (GeV ) 2 2 Q (GeV ) QE QE -1.0<cos θ <0.0 0.0<cos θ <0.3 0.3<cos θ <0.6 -1.0<cos θ <0.0 0.0<cos θ <0.3 0.3<cos θ <0.6 MB NUMU − 39 − 39 − 39 MB NUMUBAR − 42 − 39 − 39 × 10 × 10 × 10 × 10 × 10 × 10 /GeV) /GeV) /GeV) /GeV) /GeV) /GeV) 6 4.5 80 1 1 0.5 4 2 2 2 2 70 2 2 5 (cm (cm (cm (cm (cm (cm Data Data 3.5 0.8 0.8 60 0.4 µ µ µ µ µ µ θ θ θ 4 θ θ θ 3 dcos dcos dcos dcos dcos dcos 50 MC NuWro LFG+RPA+Nieves MC NuWro LFG+RPA+Nieves 0.6 2.5 0.6 0.3 µ µ µ 3 µ µ µ 40 /dT /dT /dT /dT /dT /dT 2 MC NuWro RFG+TEM MC NuWro RFG+TEM σ 0.4 σ σ σ 30 σ 0.2 σ 0.4 2 2 2 1.5 2 2 2 2 d d d d d d 20 1 0.2 0.1 0.2 MC NEUT RFG+RPA+Nieves 1 MC NEUT RFG+RPA+Nieves 10 0.5 0 0 0 0 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) µ µ µ µ µ µ 0.6<cos θ <0.7 0.7<cos θ <0.8 0.8<cos θ <0.9 0.9<cos θ <1.0 0.6<cos θ <0.7 0.7<cos θ <0.8 0.8<cos θ <0.9 0.9<cos θ <1.0 − 39 − 39 − 39 − 39 − 39 − 39 − 39 − 39 × 10 × 10 × 10 × 10 × 10 × 10 × 10 × 10 /GeV) /GeV) /GeV) /GeV) /GeV) /GeV) /GeV) /GeV) 25 4 6 22 22 20 9 12 20 20 18 3.5 2 2 2 2 2 2 2 2 8 (cm (cm (cm (cm (cm (cm 5 (cm (cm 18 18 20 16 10 3 7 16 16 µ µ µ µ µ µ µ µ θ 14 θ θ θ θ θ θ θ 4 dcos dcos dcos dcos dcos dcos dcos 6 dcos 14 14 2.5 8 15 12 12 12 5 µ µ µ µ µ 2 µ 3 µ µ 10 /dT /dT /dT /dT /dT /dT /dT /dT 6 10 10 4 10 8 σ σ σ σ σ 1.5 σ σ σ 8 8 2 2 2 2 2 2 2 2 2 3 d d d d d d d d 4 6 6 6 1 2 4 5 4 4 1 2 0.5 1 2 2 2 0 0 0 0 0 0 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) T (GeV) µ µ µ µ µ µ µ µ - 10/07/2016 10 Patrick Stowell

  11. NuWro LFG Fits NuWro LFG Nieves Correlations Correlation Pars Covariance 1 M A MEC 0.95 0.58 1.00 kNuwro_MECNorm 0.582366 1.01511 0.9 • Fit results from NuWro with an LFG are quite 0.85 0.8 similar to NEUT RFG model. 0.75 0.7 1.00 0.58 kNuwro_Ma_CCQE 1.00043 0.582366 0.65 0.6 • Still have problem where M A is being inflated kNuwro_Ma_CCQE kNuwro_MECNorm Pars NEUT RFG Nieves Correlations and MEC normalization is being driven down. Correlation Pars 1 Covariance 0.95 0.62 1.00 MECTwkDial_Norm_C12 M A MEC 0.622241 1.00743 0.9 • MEC and the Axial Mass are positively 0.85 0.8 correlated at the best fit point. 0.75 1.00 0.62 MaCCQE 1.00519 0.622241 0.7 0.65 MaCCQE MECTwkDial_Norm_C12 M A MEC Pars - 10/07/2016 11 Patrick Stowell

  12. Is our High Q 2 Error Appropriate? • Deuterium bubble chamber data can be used to place a constraint on the free nucleon cross-section. Data is statistically limited at high Q 2 . • If the model has a limited shape, like the simple dipole, the uncertainty on the bare CCQE cross-section can be underestimated in this region. • Evaluating the free nucleon cross-section uncertainties also very recently done in: Phys. Rev. D 93, 113015 (2016) • They use Z-expanstion formalism for F A. - 12/07/2016 12 Patrick Stowell

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