Measuring the NuMI Beam Flux for MINERvA Melissa Jerkins University of Texas at Austin NUINT 2011: Dehradun, Uttarakhand.

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Measuring the NuMI Beam Flux for MINERvA Melissa Jerkins University of Texas at Austin NUINT 2011: Dehradun, Uttarakhand

Measuring Flux: Introduction CERN PS: In situ measurement using  Mons increased predicted flux by 50% MiniBooNE and SciBooNE data appear to conflict with NOMAD results at higher energy Knowing your flux is difficult, and crosschecks are helpful CERN PS particle production expt. J.V. Allaby, et al., Phys. Lett. 29B 48 (1969) 2

Neutrino-nucleus interaction experiment in the NuMI beamline at Fermilab MINERvA will utilize three methods to understand its flux: Measuring Flux: Introduction Low energy (<10 GeV) precision cross section measurements 1. External data (ab initio) 2. Flexible beam design for in situ measurements 3. Muon monitors (in situ) 1. External data (ab initio) 2. Flexible beam design for in situ measurements 3. Muon monitors (in situ) 3 Target Horns Decay Pipe Absorber Muon Monitors Rock μ+μ+ π+π+ 10 m 30 m 675 m 5 m 12 m 18 m figure courtesy Ž. Pavlović Hadron Monitor νμνμ

Z. Pavlovic, “A Measurement of Muon Neutrino Disappearance in the NuMI Beam,” PhD Thesis, UT Austin 2008 Measuring Flux: Focusing Uncertainties Focusing uncertainties are smaller and easier to model than hadron production uncertainties i i X i 4

Model  p T  (GeV/c) GFLUKA0.37 Sanf.-Wang0.42 CKP0.44 Malensek0.50 MARS – v MARS – v Fluka Fluka Fluka2001 Fluka2005 MARS–v.14 MARS–v.15 Measuring Flux: Hadron Production Z. Pavlović Relying on Monte Carlo models alone isn’t a good option 5

Measuring Flux: Hadron Production Can’t modern data sets solve our problems? Sadly … no. Production data ≠ Flux Thick target effects: Experiments are mostly on thin targets NuMI target is is ~2 int lengths Reinteractions are 20-30% effect In situ temporal variations of flux: Target changes Focusing changes Downstream interactions: Interactions in horns, windows, shielding, ect. 6

We want an in situ measurement of  (x F,p T ) Measuring Flux: Hadron Production Allows us to correct the MC model for parent hadron x F and p T off the target 7 Focusing and decay kinematics imply: flux  hadron production Shape in p T and x F impact flux via focusing channel acceptance LE BEAM ME BEAM Pz (GeV/c) HE BEAM Pz (GeV/c)

“High” Energy target Horn 1 Horn 2 Deconvolve systematics: Neutrino beam focusing  /K production off target Neutrino cross sections “Low” Energy proton Horn 1 Horn 2 target π + p T =300 MeV/c and: p=5 GeV/c p=10 GeV/c p=20 GeV/c Measuring Flux: Variable Beam Moving target in/out of 1st horn varies which pions are focused 8 Z. Pavlović K+K+ π+π+ K+K+ π+π+

LE010/185kA LE010/0kA LE010/170kA LE010/200kA LE100/200kALE250/200kA Measuring Flux: Variable Beam We can vary: Horn current (p T kick supplied to pions) Target position (x F of focused particles, where x F = p z /p o ) 9 LE = pME = pHE =

Measuring Flux: Hadron Production 1 st in situ flux measurement tool: Tune MC parameterization of hadron production off the target so that it matches MINERvA Detector Data across several beam configurations 10

Each (x F,p T ) bin contributes with different weight in each beam configuration LE010/185kA LE100/200kA LE250/200kA LE010/185kA LE100/200kA LE250/200kA LE010/185kA LE100/200kALE250/200kA Measuring Flux: Fitting to Data Flexible beam configurations permit tuning hadron production yields to match data. 11

MINERvA’s “standard candle” data set will be QEL events of moderate Q 2 Measuring Flux: Fitting to Data 12 QEL cross section on nucleons is a function of Q 2, independent of neutrino energy (even for extreme values of M A ) Low Q 2 events are excluded because of uncertainties due to nuclear effects High Q 2 events are excluded because of reconstruction difficulties Use inclusive CC sample above ~20GeV and compare to CCFR, CCFRR, and CDHSW data sets to fix the absolute normalization Ratio of QE cross section 0.2<Q 2 <0.9 (assuming a fixed high energy cross section) Reference M A =1.1 Range of test M A : 0.9, 1.3, 1.5 Ratio of cross section of test M A to reference M A vs. E ν

Result of fit = set of weights in (x F,p T ) plane that should be applied to  /K yields Measuring Flux: Fitting to Data MINOS utilized such fits: Flux uncertainty at far detector reduced (2-10)%  (1-4)% Phys. Rev. D77, (2008). 13 MINOS used inclusive event sample for its fits: Fine for Far/Near ratio … but not for xsec measurements QEL events provide a well- known process for MINERvA

Measuring Flux: Fitting to Data *Includes: Beam focusing uncertainties MC differences in π + production off target 5% yield uncertainty for π + production off target 14 What kind of flux errors can MINERvA expect? Before fit LE010 Blue error band = estimation of flux uncertainty based on “current knowledge”* Effort is underway to estimate our post-fit errors by warping the hadron production of Geant4 Monte Carlo to bring simulated Geant4 “data” (across many beam configurations) into agreement with simulated Fluka “data.”

Measuring Flux: Muon Monitors 2 nd in situ flux measurement tool: Tune MC parameterization of hadron production off the target so that it matches Muon Monitor Data across several beam configurations 15

Measuring Flux: Muon Monitors Muon thresholds translate into ν thresholds Allows sampling of different energy regions of the flux 3 alcoves = poor granularity per measurement … but NuMI’s flexible beam offers data from many (I horn,Z target ) combinations 16

Measuring Flux: Muon Monitors 3 arrays of ionization chambers (2m x 2m) Plans to install a 4 th chamber Beam μ’s ionize He gas Signal = ionized electrons Sampling μ flux = hadrons off target = sampling ν flux Technique proven at CCFR, CERN-PS, CERN-SPS 17

Measuring Flux: Fitting to μMon We can fit muon monitor data to obtain (x F,p T ) in the same way we fit MINERvA data 18

DataMonte CarloTuned Monte Carlo Empirical parameterization for hadron production Warp p T and p z to tune MC to μMon data Allow π + parameters to float Fix π + /π - ratio to NA49 and fix K/π ratio to MC Measuring Flux: Fitting to μMon Successfully tuned MC to match μMon data 19

μMonitor Threshold Largest sources of error: Delta-rays Scaling pC/μ by ± 10% Other sources of error: Bethe-Block energy deposition by μ in He Scaling K/π ratio by ± 10% Fixing π + /π - ratio to MC value Scale non-linearity correction in data ± 1σ Scale dump backgrounds ± 1σ Due to large uncertainties, the flux was normalized to MINOS data for E ν > 25 GeV. Obtained a flux shape measurement from its μMonitors How can MINERvA reduce those uncertainties? L. Loiacono, “Measurement of the Muon Neutrino Inclusive Charged Current Cross Section on Iron Using the MINOS Detector,” PhD Thesis, UT Austin 2010 Measuring Flux: Fitting to μMon 20

Measuring Flux: Fitting to μMon Significant backgrounds must be included in the μMon MC 21 δ-Rays: Muons can create knock-on electrons while traveling through the rock, air, ect. MC indicates δ-rays can be as much as ~30% of the monitor signal

Experiment to correct MC δ-ray production by comparing it to data in which we deliberately introduced more δ-rays Placed “absorbers” (plates of aluminum) in front of the μMonitors to increase δ-rays Al blocks 15 x 15 x 2.5 cm 2 absorbers/curtains (set of 45 blocks): located 24 cm and 42 cm in front of monitor Measuring Flux: Fitting to μMon 22 δ rays increase with absorber thickness and decrease with separation between absorber and monitor

MINERvA has multiple tools available to understand its flux: Measuring Flux: Summary In situ measurements provide checks against external hadron production measurements NuMI’s flexible beam design allows us to map out hadron production in (xF,pT), and we can measure our flux in situ using two techniques: 1.Fits to QEL data in MINERvA 2.Fits to muon monitor yields MINERvA will augment and upgrade our muon monitor system to provide more constraints MINERvA’s initial estimated flux uncertainty is ~30%, and by performing these studies we can reduce it to 5-10% 23

The entire MINERvA collaboration thanks NuInt and its organizers for the opportunity to give these presentations.

Refereces S. Kopp, “Accelerator Neutrino Beams,” Phys. Rep. 439, 101 (2007) M. Kostin et al, “Proposal for continuously-variable neutrino beam energy for the NuMI facility,” Fermilab-TM-2353 (2001). Proc. Informal Workshops on Neutrino Beams: CERN-63-37, CERN-65-32, CERN S. Kopp et al, “The Secondary Beam Monitoring System for the NuMI Facility at FNAL,” accepted in Nucl. Instr. Meth. Z. Pavlovic, PhD Thesis, University of Texas, 2008 L. Loiacono, PhD Thesis, University of Texas,

Backup slides

Each data point is the integral of a flux plot from a given beam configuration. Data needs various corrections: Ambient pressure and temperature corrections Correction for chamber non-linearity with muon flux intensity Relative correction for helium gas quality Geant4 Monte Carlo needs various corrections: Overall scale factor from pC/μ, which can vary 5-10% due to even 20 ppm O 2 contamination of He gas Backgrounds need to be estimated Measuring Flux: Fitting to μMon 18

Use empirical form similar to BMPT to parameterize Geant4: Tune parameters of the fit to match data in multiple different beam configurations Measuring Flux: Hadron Production Flexible beam configurations permit tuning hadron production yields