Cosmic Muon Induced EM Showers in NO v A Detector Nitin Yadav - - PowerPoint PPT Presentation

cosmic muon induced em showers in no v a detector
SMART_READER_LITE
LIVE PREVIEW

Cosmic Muon Induced EM Showers in NO v A Detector Nitin Yadav - - PowerPoint PPT Presentation

Cosmic Muon Induced EM Showers in NO v A Detector Nitin Yadav Indian Institute of Technology Guwahati 1 Supervisor: Peter Shanahan , Bipul Bhuyan. 2 2 In collaboration with Hongyue Duyang and Sanjib Mishra New Perspectives 2015 June


slide-1
SLIDE 1

Cosmic Muon Induced EM Showers in NOvA Detector

Nitin Yadav Indian Institute of Technology Guwahati

Supervisor: Peter Shanahan , Bipul Bhuyan. In collaboration with Hongyue Duyang and Sanjib Mishra Fermilab, University of South Carolina.

1 2 2 1 2 ϯ ϯ New Perspectives 2015 June 8 1

slide-2
SLIDE 2

NOvA (NuMI Off-Axis v𝑓 Appearance)

  • NOvA is a long baseline

neutrino oscillation experiment, near detector at Fermi Lab and the far detector at Ash River with a baseline of 810 km.

  • Two functionally identical

detectors differ in size.

  • Uses a 2 GeV vμ beam of

intensity 450 kW currently.

  • Looks for oscillations in

v𝑓 appearance and vμ disappearance mode.

14mrad

New Perspectives 2015 June 8 2

slide-3
SLIDE 3

NOvA Detectors

Far Detector 14kton, 15.6 m x 15.6 m x 59.8 m Near Detector 300ton, 4.2 m x 4.2 m x 15.8 m 100 m underground

To 1 APD pixel W D

typical charged particle path

L To 1 APD pixel W D

typical charged particle path

L New Perspectives 2015 June 8 3

slide-4
SLIDE 4

NOvA Detector’s capability

New Perspectives 2015 June 8 To 1 APD pixel W D

typical charged particle path

L To 1 APD pixel W D

typical charged particle path

L

Fine-grained, low-Z, highly-active tracking calorimeter allows for differences between “tracky” muons, “showery” electrons, and “gappy” π0′s to be seen.

NOνA detectors are finely segmented (1 plane ~0.15 X0), which makes it well optimized for electromagnetic shower reconstruction.

4

slide-5
SLIDE 5

Event Topologies at NOvA

μ

p+

e-

Gap from γ

v

New Perspectives 2015 June 8 5

slide-6
SLIDE 6

Event Topologies at NOvA

μ

p+

e-

Gap from γ

EM shower, signal in v𝑓 appearance mode

v

New Perspectives 2015 June 8 6

slide-7
SLIDE 7

Particle Identifications at NOvA

New Perspectives 2015 June 8

  • Distribution
  • f

Artificial Neural Network (ANN) to identify v𝑓 CC events.

  • This method uses

shower-shape based likelihoods for particle hypotheses calculated from longitudinal and transverse dE/dx information.

LID : Longitudinal Identification We use data driven technique to benchmark PID algorithms and simulation of EM shower at NOvA

7

slide-8
SLIDE 8

Using Cosmic Rays to Study Electron Selection

 Cosmic-ray induced showers:  Why Cosmic Brem Shower:

  • Bremsstrahlung(Brem) shower : Energetic muon looses energy via EM

interaction in media.

  • Plenty of Cosmic EM shower in

Nova FD detector, 72kHz

  • EM shower can mimic signal in

the v𝑓 appearance mode.

  • Provide statistically rich test

samples of pure EM showers.

  • Check the multivariate v𝑓 PID

algorithm including:

  • Efficiency.
  • Fiducial cut.
  • Monitor detector for EM

shower reconstruction.

New Perspectives 2015 June 8

A 500μ sec cosmic trigger event display

8

slide-9
SLIDE 9

Shower finding and extraction

New Perspectives 2015 June 8

  • A muon with brem shower
  • We developed a criteria based on

energy deposition in planes along the muon track.

  • Find shower on basis of energy

deposition in planes.

  • Define a shower regions:
  • Shower start.
  • Shower end.
  • Remove all the hits out of the

shower regions.

  • Remove only muon mip in the

shower region.

Brem Shower

  • Muon removal:

9

slide-10
SLIDE 10

Brem shower example

Event display of hits of a cosmic muon candidate with Electromagnetic (EM) Bremsstrahlung (Brem) Shower.

New Perspectives 2015 June 8 10

slide-11
SLIDE 11

Brem Shower hits extracted

Event display of hits of the EM shower after the removal of hits associated with the muon track from NOvA simulations.

New Perspectives 2015 June 8 11

slide-12
SLIDE 12

Extracted Brem Shower’s variables

  • Data and MC comparison of

shower energy after

  • reconstruction. Good agreement

between Data and MC.

New Perspectives 2015 June 8

  • Data and MC comparison of

shower angle. Good agreement between Data and MC.

12

slide-13
SLIDE 13

Shower variables vs v𝑓

  • Data

and MC comparison

  • f

shower energy after

  • reconstruction. Good agreement

between Data and MC.

  • Brem

shower energy in comparison with v𝑓 MC events. Brems are less energetic to v𝑓 events.

New Perspectives 2015 June 8

  • Brem

shower angle in comparison with v𝑓 MC events. Brems are more perpendicular to direction

  • f

beam than v𝑓 events.

13

slide-14
SLIDE 14

Shower reweighted to v𝑓

New Perspectives 2015 June 8

  • A

2D reweighting matrix is constructed and used to reweight Brem shower energy and angle to v𝑓 CC events to make for these differences.

  • Most of the difference in Brem

events and v𝑓 events comes from difference in energy and angle distributions.

14

slide-15
SLIDE 15

Particle Identification ANN (LID)

  • Data and MC comparison of

electron identification ANN (LID) . Good agreement between data and MC. Most of the Brem are identified as v𝑓 like.

New Perspectives 2015 June 8

  • Brems identification in comparison

to v𝑓 events.

15

slide-16
SLIDE 16

LID after reweight

  • Most of the Brems are identified

as v𝑓 like. But to benchmark the PID and simulations Brem should reasonably be similar to v𝑓 . We achieved this by reweighting.

New Perspectives 2015 June 8

  • After reweighting Brem energy

and angle to v𝑓 events, Brems do look more like v𝑓 events. This convinces us that Brem can be used as data driven benchmark for testing PIDs and EM shower simulations at NOvA

16

slide-17
SLIDE 17

PID Efficiency X, Y and Z in detector.

  • PID efficiencies as a

function of vertex X , Y and Z direction in NOvA. Efficiencies are reasonably flat and data and MC agreement is well within 5 %. The rest of the difference will be considered as a source of systematic uncertainty.

New Perspectives 2015 June 8 17

slide-18
SLIDE 18

Conclusion

 Using Muon Removal algorithm we find and isolate EM Shower from cosmic data and MC.  A good agreement between data and MC.  v𝑓 reweight method has been developed to make cosmic EM showers resemble beam events.  A data-driven technique to benchmark the particle identifications and simulations of EM showers using Brem sample.  PID efficiencies as a function of positions across the detector are pretty uniform, indicating calibration effects are well controlled.

New Perspectives 2015 June 8 18

slide-19
SLIDE 19

Backup

New Perspectives 2015 June 8 19

slide-20
SLIDE 20

Brem Shower example

Event display of raw hits of a cosmic track candidate with Electromagnetic (EM) Bremsstrahlung (Brem) Shower from NOvA simulation.

New Perspectives 2015 June 8 20

slide-21
SLIDE 21

Brem Shower extracted

Event display of hits of the EM shower after the removal of hits associated with the muon track from NOA simulation. What left are hits of Brem shower.

New Perspectives 2015 June 8 21

slide-22
SLIDE 22

Thank you!

New Perspectives 2015 June 8 22