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Goals
- The long term goal is to make a regression CNN to
reconstruct energy and vertex of electrons for ProtoDUNE
- To Prepare for this, we start by doing checks on the basic
variables, and compare between MC and data
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Priming for a Regression CNN for Energy and Vertex of Electrons Ben - - PowerPoint PPT Presentation
Priming for a Regression CNN for Energy and Vertex of Electrons Ben - - PowerPoint PPT Presentation
Priming for a Regression CNN for Energy and Vertex of Electrons Ben Jargowsky University of California, Irvine Goals The long term goal is to make a regression CNN to reconstruct energy and vertex of electrons for ProtoDUNE To Prepare
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Checking Basic Variables
- We look at 1 GeV data, from run 5809, and 1 GeV
MC (SAM definition “PDSPProd2_MC_1GeV_reco_sce_datadriven”)
- Use dunetpc module “ProtoDUNEelectronAnaTree”
- Make cuts for electrons, complete showers, and
reconstructed beam momentum
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SLIDE 4
Cutting For Complete Showers...
- We apply a cut on
number of hits per shower to remove incomplete showers
- We apply this at 200
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Checking Basic Variables
- Now we can look at
- ur basic variables.
- Red is MC, blue is
data
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Checking Basic Variables
- This is charge per hit
(of primary, complete showers in collection plane)
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SLIDE 7
Checking Basic Variables
- Data sees higher peaks
than MC for total dE/dx
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SLIDE 8
Checking Basic Variables
- We may also want to
consider dE/dx in the beginning of the shower
- We look at distance of
calorimetry entries from shower start
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SLIDE 9
Checking Basic Variables
- We may also want to
consider dE/dx in the beginning of the shower
- We look at distance of
calorimetry entries from shower start
- We keep only entries
under 14cm
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SLIDE 10
Checking Basic Variables
- Now we can see
dE/dx at the start
- f the shower
agrees a little less than total dE/dx
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SLIDE 11
Checking Basic Variables
- X and Y vertices are in reasonable agreement, while
Z is questionable
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SLIDE 12
Next Steps
- Continue checks on basic variables (understand the
differences we see)
- Perform checks on charge distributions over ADC and
TDC
- Convert ROOT files of MC to pixelmaps in HDF5 format
suitable for input to a CNN
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SLIDE 13
Architecture for Energy
- CNN Architectures for
energy and vertex reconstruction designed for DUNE can be adapted for ProtoDUNE
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Architecture for Vertex
- For vertex, a
2 stage network is used
- First stage
feeds cropped pixelmap to second stage
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SLIDE 15
Conclusions
- I have began a check of calibration, lifetime
corrections, etc to validate basic variables
- After a satisfactory conclusion of this, we can began
converting MC to pixelmap data to train CNNs adapted from existing, proven CNN architectures
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The End
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