GENIE/Professor framework for neutrino data global ﬁt · Dipole Axial Form Factor - Depending on...

Introduction Genie CC 0π tuning Analysis Conclusion

GENIE/Professor framework for neutrino data global fitA first application: global fit of CC 0π datasets

Marco Roda - [email protected] behalf of GENIE collaboration

University of Liverpool

19 April 2017IPPP/NuStec

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Outline

Introduction

Genie status vs recent datasets

Tuning mechanism

Tuning results

Conclusions

Thanks to

IPPP Associateship award

2 / 38


Outline

Introduction

Genie status vs recent datasets

Tuning mechanism

Tuning results

Conclusions

Thanks to

IPPP Associateship award

3 / 38


Why 0π

Why care about 0π?

We want to study neutrinosflavour and mixingLepton CP violation

Oscillation experimentsT2k, NOvADUNE, HyperKBeam energy ∼ few GeV

CC 0π is the dominant reactionTwo body reaction

Ideal for ν energy estimation ......on free nucleons

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0π puzzle

CC Quasi-Elastic - 0π on single nucleons

Theoretically

understood

Well constrained by

experimental

information

Electron scattering

Neutron β decay

Experiments on

Hydrogen / Deuterium

Neutrinos

[GeV]νE

1−10 1 10

]2cm

-38

CC

QE

[10

µν

0

0.5

1

1.5

2

2003-2017, GENIE - http://www.genie-mc.org

ANL_12FT,1 ANL_12FT,3

BEBC,12 BNL_7FT,3

FNAL_15FT,3 Gargamelle,2

NOMAD,2 SERP_A1,0

SERP_A1,1 SKAT,8

Antineutrinos

[GeV]νE1 10 210

]2cm

-38

CC

QE

[10

µν

0

0.5

1


BNL_7FT,2 Gargamelle,3

Gargamelle,5 NOMAD,3

SERP_A1,2 SKAT,9

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0π puzzle

CC Meson Exchange Current - 0π on heavy nuclei

On higher A nuclei things are complicated

CCQE is not enough to describe dataMiniBooNE

MEC is requirednucleons interactions2p-2hnp-nh

> 20 % effectOn carbon

MiniBooNE data

[Martini et al. PRC 84 055502 (2011)]

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0π puzzle

Effect of MEC on energy reconstruction

CCQE is a 2-body reactionEν depends is just a function oflepton momentum and angle

MEC is not a 2-body reactionlow energy tails in recontructedenergy distributions

MEC also relevant for CPsearches

np-nh is different for ν/ν̄

⇒ MEC is important to achieveprecise measurements

Martini et al.

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0π puzzle

Search for 2p-2h

Characteristic events2 back-to-back nucleons

Nuclear effect can changeobserved topology

migrations in the number ofobserved protons

future LarTPCs (or gas TPCs)important role

Disentangle FSI from MECCC 0π samplesproton multiplicity

Important dataset that will "soon"be available

ArgoNEUT

[Phys.Rev. D90 (2014) 1, 012008]

[Ulrich Mosel]

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MC generators

What can we do as generator people?

Comparing different data and modelsBeing quantitative⇒ highlight tensions

Call for experiments: we need full covariance matrices

feedback for experiments⇒ drive the format of cross section releases⇒ hint toward key measurements

Global fitsModel⇒ Cross sections is not analytic

What is the status of Genie in all of this?

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MC generators







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MC generators







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Models

Genie - Models for 0π

Default - G00_00aNo MECCCQE process is LwlynSmith ModelDipole Axial Form Factor - Depending on MA = 0.99 GeVNuclear model: Fermi Gas Model - Bodek, Ritchie

Default + MEC - G16_01bwith Empirical MECCCQE process is LwlynSmith ModelDipole Axial Form Factor - Depending on MA = 0.99 GeVNuclear model: Fermi Gas Model - Bodek, Ritchie

Nieves, Simo, Vacas Model - G16_02aTheory motivated MECCCQE process is NievesDipole Axial Form Factor - Depending on MA = 0.99 GeVNuclear model: Local Fermi Gas Model

G17_02a (not presented in this talk) - G17_02awith Z-Expansion for Axial form factorGet rid of MA

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CCQE

MiniBooNE CCQE

Both ν and ν̄

Double differential cross section

flux integrated

No correlations

Preferred model is Nieves Model(G16_02a)

excellent agreement for νχ2 = 101/137 DoF

worse for ν̄χ2 = 176/78 DoF

0

1

2

µθCos1− 0.5− 0 0.5 1

[GeV

]µT

0.5

1

1.5

2

µθCos1− 0.5− 0 0.5 1

[GeV

]µT

0.5

1

1.5

2

0

1

2


/GeV/n]2cm-38[10µT∂/µθCos∂)/πCC 0µν(σ2∂

Data: miniboone_nuccqe_2010

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CCQE

MiniBooNE CCQE

Both ν and ν̄


flux integrated

No correlations

Preferred model is Nieves Model(G16_02a)

excellent agreement for νχ2 = 101/137 DoF

worse for ν̄χ2 = 176/78 DoF

µθCos

1− 0.5− 0 0.5 1

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

0.5

1

1.5

2

miniboone_nuccqe_2010

= 40.6/17 DoF2χtrunk:G00_00a:miniboone_fhc

= 64.8/17 DoF2χtrunk:G16_01b:miniboone_fhc

= 14.3/17 DoF2χtrunk:G16_02a:miniboone_fhc

[0.4; 0.5 ] GeV∈µT

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CCQE

T2K ND280 0π


flux integrated

Fully correlated

Tensions between datasetsPreferred model is G16_01b

χ2 = 135/67 DoF

all models look reasonable "By eye"estimation

correlation is complicatedWe can’t ignore it!

0

0.5

1

µθCos1− 0.5− 0 0.5 1

[GeV

]µP

0

2

4

6

µθCos1− 0.5− 0 0.5 1

[GeV

]µP

0

2

4

6

0

0.5

1


/GeV/n]2cm-38[10µP∂/µθCos∂/σ2∂

Data: t2k_nd280_numucc0pi_2015

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CCQE

T2K ND280 0π


flux integrated

Fully correlated

Tensions between datasetsPreferred model is G16_01b

χ2 = 135/67 DoF

all models look reasonable "By eye"estimation

correlation is complicatedWe can’t ignore it!

= 0.9 GeVµ

= 0.875 Pµ

θCos

= 1.25 GeVµ

= 0.875 Pµ

θCos

= 15.75 GeVµ

= 0.875 Pµ

θCos

= 0.2 GeVµ

= 0.92 Pµ

θCos

= 0.45 GeVµ

= 0.92 Pµ

θCos

= 0.55 GeVµ

= 0.92 Pµ

θCos

/GeV

/n]

2cm

-38

[10

µP

∂/ µθC

os∂/σ2 ∂ 0

0.5

1

t2k_nd280_numucc0pi_2015= 11.5/6 DoF2χtrunk:G00_00a:t2k_nd280_numu_fhc= 3.43/6 DoF2χtrunk:G16_01b:t2k_nd280_numu_fhc= 28.1/6 DoF2χtrunk:G16_02a:t2k_nd280_numu_fhc

[ 36; 41 ]∈Bin

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Genie status

GENIE

New Models

MEC modelsEmpiricalNieves Simo Vacas

Better CCQE modelNieves...

Nuclear models

Multiple combinationsNeed to check the balance between eachcomponent

will have a tuning!

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Genie status

GENIE

New Models

MEC modelsEmpiricalNieves Simo Vacas

Better CCQE modelNieves...

Nuclear models

Multiple combinationsNeed to check the balance between eachcomponent

will have a tuning!

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Comparisons

The Comparisons

The GENIE suite contains a package devoted to comparing GENIEpredictions against publicly released datasets.

Crucial technology for new GENIE global fit to neutrino scattering data

Provides the opportunity to improve and develop GENIE models

All sorts of dataModern Neutrino Cross Section measurement

nuclear targetstypically flux-integrated differential cross-sectionsMiniBooNE, T2K, MINERvA

Historical Neutrino Cross Section MeasurementBubble chamber experiment

Measurements of neutrino-induced hadronic system characteristics

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Professor

Professor

http://professor.hepforge.org

Numerical assistant

Developed for ATLAS experimentI(p) used instead of a full MC

1 MC runs subset of param space2 sample bin’s behaviour3 Parametrization I(p)

Polinomial interpolation

Repeat for each bin

a parameterization Ij (p) for each bin

Minimize according to~I(p)

∼ 15 parameters

Special thanks to H. Schulzbased here in Durham

p

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Professor

Professor


Numerical assistant




Repeat for each bin



∼ 15 parameters


p

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Professor

Professor


Numerical assistant




Repeat for each bin



∼ 15 parameters


p

interpolated value

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Professor

Professor


Numerical assistant




Repeat for each bin



∼ 15 parameters


p

interpolated value

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Professor

Professor


Numerical assistant




Repeat for each bin



∼ 15 parameters


p

interpolated value

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Professor

Advantages

Highly parallelizableindependent from the minimization

All kind of parameters can be tunedNot only reweight-able

Advanced systemTake into account correlations

weights specific for each bin and/or datasetProper treatment while handling multiple datasetsRestrict the fit to particular subsets

Nuisance parameters can be insertedproper treatment for datasets without correlations (MiniBooNE)

Reliable minimization algorithmbased on Minuit

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Inputs

Datasets - 298 data points

MiniBooNE νµ CCQE

2D histogram137 points

MiniBooNE ν̄µ CCQE


T2K ND280 0π (2015)

irregular 2D histogram67 points

MINERvA νµ CCQE


MINERvA ν̄µ CCQE


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

Data

bin0 50 100 150 200 250

bin

0

50

100

150

200

250

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Data Covariance

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Inputs

Model and parameters

Default + Empirical MEC

G16_01b in the new naming scheme

Parameters:QEL-MA ∈ [0.7; 1.8] GeV - Default value is 0.99 GeVQEL-CC-XSecScale ∈ [0.8; 1.2] - Default value is 1RES-CC-XSecScale ∈ [0.5; 1.5] - Default value is 1MEC-FracCCQE ∈ [0; 1] - Default value is 0.45FSI-PionMFP-Scale ∈ [0.6; 1.4] - Default value is 1FSI-PionAbs-Scale ∈ [0.4; 1.6] - Default value is 1

No priors on the parametersConsidering on MA

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Outputs

Professor Output

Parameters best fit0 MA1 QEL-CC-XSecScale2 RES-CC-XSecScale3 MEC-FracCCQE4 FSI-PionMFP-Scale5 FSI-PionAbs-Scale

Prediction covariancedue to the propagation of theparam. covarianceSo far not used

Tool to propagate systematicsparameters

Parameter Covariance

0 1 2 3 4 5

0

1

2

3

4

5

0

0.001

0.002

0.003

0.004

0.005

Prediction Covariance

0 50 100 150 200 2500

50

100

150

200

250

0.001−

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

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Outputs

Sheer results

Parameter Best fit NominalMA (GeV/c2) 1.21± 0.02 0.99

QEL-CC-XSecScale 0.95± 0.02 1RES-CC-XSecScale 1.02± 0.05 1

MEC-FracCCQE 0.53± 0.08 0.45FSI-PionMFP-Scale 0.75± 0.04 1FSI-PionAbs-Scale 0.87± 0.07 1

MA is reasonably low

Scaling factors for single processes are compatible with nominal values

You can find the complete comparisons plots in the indico page

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Single datasets

Single datasets

Datasets were fitted separately

Parameter Neutrino fit Anti-neutrino fit Global fitMA (GeV/c2) 1.17 ± 0.02 1.26 ± 0.03 1.21 ± 0.02

QEL-CC-XSecScale 0.93 ± 0.01 0.97 ± 0.02 0.95 ± 0.02RES-CC-XSecScale 0.86 ± 0.05 0.98 ± 0.09 1.02 ± 0.05

MEC-FracCCQE 0.85 ± 0.03 0.7 ± 0.1 0.53 ± 0.08FSI-PionMFP-Scale 0.87 ± 0.02 1.39 ± 0.03 0.75 ± 0.04FSI-PionAbs-Scale 1.51 ± 0.03 0.7 ± 0.1 0.87 ± 0.07

Fit Results Neutrino fit Anti-neutrino fit Global fit Nominal ValuesMiniboone νµ χ2 152 / 137 171 / 137 138 / 137 441 / 137MiniBooNE ν̄µ χ2 60 / 78 32.4 / 78 36.2 / 78 50.4 / 78

T2K χ2 237 / 67 276 / 67 252 / 67 135 / 67MINERvA νµ χ2 6.11 / 8 8.07 / 8 7.79 / 8 17.5 / 8MINERvA ν̄µ χ2 8.19 / 8 11.5 / 8 5.7 / 8 6.23 / 8Global dataset χ2 463 / 292 499 / 292 440 / 292 650 / 298

MA and cross section scale factors are in good agreement

FSI parameters are notThe agreement with data is reasonable

Better than original model

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Single datasets

T2K effect on the fit

T2K ND280 data are complicatedTensionsCorrelations⇒ anti-intuitive

T2K ND280 data can not even be fitted by their ownwith the current model

⇒ χ2 = 127/61

T2K fit results are not compatible with other dataset

⇒ χ2 = 1023/137 vs MiniBooNE νµ CCQE

⇒ χ2 = 1567/292 vs whole fitted dataset

global fit can suffer from this

Effect is cleardiscrepancy in low momentum muons

Tµ < 400 MeV

No reason to remove this dataset from the fitTheir effort on the error estimation should be praised

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Single datasets

T2K effect on the fit

T2K ND280 data are complicatedTensionsCorrelations⇒ anti-intuitive

T2K ND280 data can not even be fitted by their ownwith the current model

⇒ χ2 = 127/61

T2K fit results are not compatible with other dataset

⇒ χ2 = 1023/137 vs MiniBooNE νµ CCQE

⇒ χ2 = 1567/292 vs whole fitted dataset

global fit can suffer from this

Effect is cleardiscrepancy in low momentum muons

Tµ < 400 MeV

No reason to remove this dataset from the fitTheir effort on the error estimation should be praised

µθCos

1− 0.5− 0 0.5 1

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

0.5

1


= 156/20 DoF2χtrunk:G16_01b:miniboone_fhc

= 31.4/20 DoF2χtrunk:GlobalFit:miniboone_fhc

[0.2; 0.3 ] GeV∈µT

µθCos

1− 0.5− 0 0.5 1

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

0.5

1

1.5




[0.3; 0.4 ] GeV∈µT

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Best fit plots

Best fit - MiniBooNE νµ CCQE

[GeV]µT0.5 1 1.5 2

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

1

2




[0.8; 0.9 ]∈µθCos

[GeV]µT0.5 1 1.5 2

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

1

2




[0.9; 1 ]∈µθCos

Fit has a big impact

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Best fit plots

Best fit - MiniBooNE ν̄µ CCQE

[GeV]µT0.5 1 1.5 2

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

0.1

0.2

0.3

0.4

miniboone_nubarccqe_2013

= 6.28/8 DoF2χtrunk:G16_01b:miniboone_rhc

= 2.37/8 DoF2χtrunk:GlobalFit:miniboone_rhc

[0.6; 0.7 ]∈µθCos

[GeV]µT0.5 1 1.5 2

/GeV

/n]

2cm

-38

[10

µT∂/

µθC

os∂)/π

CC

0µ

ν(σ2 ∂ 0

0.2

0.4

0.6

miniboone_nubarccqe_2013

= 9.62/9 DoF2χtrunk:G16_01b:miniboone_rhc

= 3.22/9 DoF2χtrunk:GlobalFit:miniboone_rhc

[0.7; 0.8 ]∈µθCos

Improvement not really necessary in this case

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Best fit plots

Best fit - MINERvANeutrinos

]2[GeVQE2Q

0 0.5 1 1.5 2

/neu

tron

]2

/GeV

2cm

-38

[10

QE

2/d

Qσd 0

0.5

1

1.5


MINERvAExDataCCQEQ2

= 17.5/8 DoF2χtrunk:G16_01b:minerva_numu_2013

= 7.79/8 DoF2χtrunk:GlobalFit:minerva_numu_2013

Antineutrinos

]2[GeVQE2Q

0 0.5 1 1.5 2/p

roto

n]2

/GeV

2cm

-38

[10

QE

2/d

Qσd 0

0.5

1


MINERvAExDataCCQEQ2

= 6.23/8 DoF2χtrunk:G16_01b:numubar_2013

= 5.7/8 DoF2χtrunk:GlobalFit:numubar_2013

⇒ "Eye evaluation" would prefer default model35 / 38


Best fit plots

Best fit - T2K ND280

agreement with t2k has worsened

not surprising

⇒ it happened also with models

χ2: 135→ 252 / 67 DoF

= 0.45 GeVµ

= 0.96 Pµ

θCos

= 0.55 GeVµ

= 0.96 Pµ

θCos

= 0.65 GeVµ

= 0.96 Pµ

θCos

= 0.75 GeVµ

= 0.96 Pµ

θCos

= 0.9 GeVµ

= 0.96 Pµ

θCos

= 1.125 GeVµ

= 0.96 Pµ

θCos

/GeV

/n]

2cm

-38

[10

µP

∂/ µθC

os∂/σ2 ∂ 0

0.5

1

t2k_nd280_numucc0pi_2015= 5.47/6 DoF2χtrunk:G16_01b:t2k_nd280_numu_fhc = 8.1/6 DoF2χtrunk:GlobalFit:t2k_nd280_numu_fhc

[ 48; 53 ] ∈Bin

= 1.375 GeVµ

= 0.96 Pµ

θCos

= 1.75 GeVµ

= 0.96 Pµ

θCos

= 2.5 GeVµ

= 0.96 Pµ

θCos

= 16.5 GeVµ

= 0.96 Pµ

θCos

= 0.25 GeVµ

= 0.99 Pµ

θCos

= 0.55 GeVµ

= 0.99 Pµ

θCos

/GeV

/n]

2cm

-38

[10

µP

∂/ µθC

os∂/σ2 ∂ 0

0.1

0.2

0.3

t2k_nd280_numucc0pi_2015= 6.66/6 DoF2χtrunk:G16_01b:t2k_nd280_numu_fhc = 12.3/6 DoF2χtrunk:GlobalFit:t2k_nd280_numu_fhc

[ 54; 59 ] ∈Bin

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Possible improvements

Next steps

More datasets:Bubble chamber CCQE data

Why not fitting MA all together?Data are in our database (see introduction)

inclusive cross sectionsavoid fit results to go in not physical regions

Fit of new modelsFull Nieves Model - G16_02b...

Find a way to estimate correlations for MiniBooNENuisance parameters

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Conclusions

Conclusion

We are renewing Genienew modelsEasy comparisons with Cross section Data⇒ Quantitative

Deployed in Genie v3 and v4

We have a very powerful fitting machineryProved to workThis is not an exercise

We hope that these tools will improvetheory / experiments collaboration

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Single datasets

Advertisment

New Position in LiverpoolJoin a big neutrino group

Position has to be filled in 10 days

Big data scienceSBNDArgon Tune for GENIE

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Single datasets

Backup slides

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Single datasets

MiniBooNE

Single datasets - MiniBooNE

Parameter Miniboone νµ fit MiniBooNE ν̄µ MiniBooNE Global fitMA (GeV/c2) 1.10 ± 0.03 1.25 ± 0.03 1.17 ± 0.02



Fit Results Miniboone νµ fit MiniBooNE ν̄µ fit MiniBooNE Global fitGlobal χ2

Miniboone νµ χ2 121 / 131 153 / 137 124 / 137MiniBooNE ν̄µ χ2 60.4 / 78 29 / 72 40.3 / 78

T2K χ2 298 / 67 279 / 67 271 / 67MINERvA νµ χ2 11.4 / 8 10.6 / 8 9.17 / 8MINERvA ν̄µ χ2 16.3 / 8 11.7 / 8 10.4 / 8Global dataset χ2 507 / 292 483 / 292 455 / 292

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Single datasets

T2K

Single datasets - T2K ND280 νµ 0π

Parameter T2K fit T2K fit - no corr T2K fit with priorsMA (GeV/c2) 0.75 ± 0.04 1.03 ± 0.13

QEL-CC-XSecScale 0.90 ± 0.02 1.11 ± 0.04RES-CC-XSecScale 1.2 ± 0.1 1.500 ± 0.001

MEC-FracCCQE 0.36 ± 0.09 0.3 ± 0.1FSI-PionMFP-Scale 0.81 ± 0.05 1.1 ± 0.1FSI-PionAbs-Scale 1.1 ± 0.1 1.54 ± 0.08

Fit Results T2K fit T2K fit - no corrMiniboone νµ χ2 1023 / 137 / 137MiniBooNE ν̄µ χ2 367 / 78 / 72

T2K χ2 127 / 61 / 61MINERvA νµ χ2 26.1 / 8 / 8MINERvA ν̄µ χ2 23.5 / 8 / 8Global dataset χ2 1567 / 292 / 292

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Single datasets

MINERvA

Single datasets - MINERvA

Parameter MINERvA νµ fit MINERvA ν̄µ MINERvA Global fitMA (GeV/c2) 1.16 ± 0.10 1.2 ± 0.1 1.20 ± 0.08



Fit Results MINERvA νµ fit MINERvA ν̄µ fit MINERvA Global fitMiniboone νµ χ2 / 131 / 137 220 / 137MiniBooNE ν̄µ χ2 / 78 / 72 97.2 / 78

T2K χ2 / 67 / 67 184 / 67MINERvA νµ χ2 / 2 / 8 6.49 / 8MINERvA ν̄µ χ2 / 8 / 2 3.26 / 8Global dataset χ2 / 292 / 292 511 / 292

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GENIE/Professor framework for neutrino data global ﬁt · Dipole Axial Form Factor - Depending on...

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