Progress towards the extraction of exclusive - 40 Ar CCQElike - - PowerPoint PPT Presentation

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Progress towards the extraction of exclusive - 40 Ar CCQElike - - PowerPoint PPT Presentation

Progress towards the extraction of exclusive - 40 Ar CCQElike crosssections using the MicroBooNE LArTPC detector A.Papadopoulou On behalf of the MicroBooNE Collaboration June 10, 2019 Motivation C harged C urrent Q uasi E lastic


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Progress towards the extraction of exclusive νµ-40Ar CCQE–like cross–sections using the MicroBooNE LArTPC detector

A.Papadopoulou On behalf of the MicroBooNE Collaboration June 10, 2019

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Motivation

Charged Current Quasi–Elastic (CCQE) Interaction Channel

MicroBooNE incoming flux range

  • Dominant interaction at low energies
  • Studies of neutrino energy reconstruction
  • Allows high precision oscillation studies
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Existing Data

  • Extracted cross–sections on 12C, 16O, 56Fe, 208Pb
  • None on 40Ar (heavy asymmetric nucleus,

building nucleus of LArTPC detectors)

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Objective

First extraction

  • f exclusive νµ-40Ar CCQE–like differential cross–sections

using the MicroBooNE detector

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Signal Definition

Vertex of 2 tracks

  • 1 muon (≥ 100 MeV/c)
  • 1 proton (≥ 300 MeV/c)
  • No π0, no π± (≥ 70 MeV/c)

p µ *We allow any number of e, γ, n and charged hadrons below these thresholds, which can be further lowered

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Cosmic Background Rejection

  • MicroBooNE is a surface detector dominated by cosmics

◮ 1 ν interaction in ∼ 500 events ◮ After trigger application, 1 ν interaction in ∼ 10 events Development of cosmic rejection machinery using detector and kinematics–based cuts ◮ arXiv:1812.05679

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Cosmic Background Rejection

Broken Track

Detector–based cuts ◮ Energy deposition profile ◮ Track length ◮ Scintillation light ◮ Collinearity

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Cosmic Background Rejection

Kinematics–based cuts ◮ Vertex activity ◮ Coplanarity ◮ Transverse imbalance P⊥

miss = (

Pµ + Pp)⊥

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Statistics

Purity: 78.7 ± 1.1 % Efficiency: 15.5 ± 0.2 %

  • # events measured: 462.0 ± (stat) 21.5*
  • # events expected: 486.4 ± (stat) 5.0

Though low statistics, first indication of consistency between data and simulation * Using ∼ 1 / 20 of the available data–sample

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Cross–Section Extraction

  • Select events in data sample
  • Subtract cosmic related background
  • Subtract MC beam related background

( dσ

dpµ)n = Non

n −No f f n

−Bn η µ

n·Φν·Ntargets·∆µ n

*Same for the proton and other kinematic variables

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Cross–Section Extraction

Non – # of events in beam-on data No f f – # of events in beam-off data

          

DATA

( dσ

dpµ)n = Non

n −No f f n

−Bn η µ

n·Φν·Ntargets·∆µ n

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Cross–Section Extraction

η – effective detection efficiency (efficiencies & bin migration) B – background processes

                  

MC

( dσ

dpµ)n = Non

n −No f f n

−Bn η µ

n·Φν·Ntargets·∆µ n

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Cross–Section Extraction

Φν – neutrino integrated flux Ntargets – number of nuclei ∆ – bin width

                

Constants

( dσ

dpµ)n = Non

n −No f f n

−Bn η µ

n·Φν·Ntargets·∆µ n

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Differential Cross–Sections

Work In Progress Muons Protons

0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8 1.0 cos( ) 2 4 6 8 10

d dcos( ) [10 38cm2]

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 cos(

p)

2 4 6 8 10

d dcos(

p) [10

38cm2]

data MC

*Only statistical errors included Non–negligible differencies

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Differential Cross–Sections

Work In Progress Muons Protons*

0.2 0.4 0.6 0.8 1.0 1.2 1.4 p [GeV/c] 2 4 6 8 10

d dp [10 38 cm2 GeV/c]

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 pp [GeV/c] 2 4 6 8 10

d dpp [10 38 cm2 GeV/c]

data MC

Non–negligible discrepancies *First attempt to extract proton differential cross–sections at such low momenta

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Differential Cross–Sections

Work In Progress Muons Protons

150 100 50 50 100 150 [deg.] 0.000 0.005 0.010 0.015 0.020

d d

[10

38 cm2

  • deg. ]

150 100 50 50 100 150

p [deg.]

0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016

d d

p [10

38 cm2

  • deg. ]

data MC

Sanity check Uniform distributions in polar angle

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Wrap Up & Future

  • ✓ Progress towards first extraction of

exclusive νµ-40Ar CCQE–like differential cross–sections using data from the MicroBooNE LArTPC detector

  • ✓ Finalizing systematical studies

*Paper published in the near future

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Thank you!

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Backup Slides

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The MicroBooNE Experiment

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The MicroBooNE Detector

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Pre–Selection

Hardware and Software Triggers ◮ 1 ν interaction in ∼ 1000 triggered events ◮ PMT trigger enriches this ratio to 1 ν interaction in ∼ 10 events Collection of track pairs at close proximity ◮ arXiv:1812.05679

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Pre–Selection

  • Pairs of tracks at close proximity:

distance < 11 cm between any two edges (start-start, start-end, end-start, end-end) S S E E

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Statistics

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Migration Matrices

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Effective Efficiency

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Background

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Systematics

  • ✓ Event selection cuts
  • ✓ Beam flux
  • ✓ POT
  • ✓ Efficiencies due to correlations
  • ✗ Detector modeling
  • ✗ Event generator