Transcript ppt

GLAST LAT
Gamma-ray Large
Area Space
Telescope
Bkg Rejection Italy
Background Rejection Activities
in Italy
Francesco Longo
University and INFN, Trieste, Italy
[email protected]
On behalf of the “North-East” INFN group
thanks in particular to R.Rando, O.Tibolla, Y.Lei,
G.Busetto and P.Azzi (University and INFN Padova)
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GLAST LAT
Bkg Rejection Italy
Bkg Rejection activity
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Starting from “simple cuts”
Collection of Bkg Rejection documentation
Understanding IM cuts (DC1 variables and cuts)
Classification Trees in R
New recent developments
Ready for new data
More Info: http://sirad.pd.infn.it/glast/ground_sw/dc2.html
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GLAST LAT
Bkg Rejection Italy
“By hands” cuts
• First iteration using already suggested cuts
• Look into Merit Tuple to find efficiency of rejection and gamma
acceptance
• Reference docs (Atwood):
– “Instrument response studies”
– “Post rome background rejection”
• Datasets:
– DC1 prep background ntuples
– DC1 prep gamma Merit nutple
• Divide events in particle type: gamma(signal), gamma(bkg),
electron+positron, protons
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GLAST LAT
Bkg Rejection Italy
Calorimeter categories
• Definitions:
– No cal:
– Low Cal:
– Med Cal:
– High Cal:
CalEnergySum<5.
|| CalTotRLn≤2
CalEnergySum>5.
&& CalTotRLn>2
CalEnergySum>350. && CalTotRLn>2
CalEnergySum<3500. && CalTotRLn>2
– “Good Energy” events:
“good_energy” = (EvtEnergySumOpt-MCEnergy)/MCEnergy
|”good_energy”| ≤ 35%
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GLAST LAT
Bkg Rejection Italy
Signal events split
ALL
Total
No
Low
Med
High
g(all)
722594
314226
(43.4%)
122081
(17%)
114224
(15.8%)
172063
(23.8%)
81139
(66.4%)
94869
(83%)
142082
(83%)
g (good)
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GLAST LAT
Bkg Rejection Italy
Background events split
ALL
Total
No
Low
Med
High
e
746232
649293
(87%)
93933
(13%)
1139
(0.2%)
1867
(0.3%)
p
1165277
608568
(52%)
284425
(24%)
178084
(15%)
94200
(8%)
g
288491
276358
(96%)
10066
(3.5%)
1227
(0.4%)
840
(0.3%)
GOOD
Low
Med
High
e
60093 (64%)
854 (75%)
1365 (73%)
p
35407 (12%)
10914 (5.7%)
21033 (22%)
g
5185 (51.5%)
797 (65%)
459 (55%)
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Gamma
Low Cal
ALL
GOOD
BAD
High Cal
ALL
GOOD
BAD
MCEnergy
GLAST LAT
Bkg Rejection Italy
“Tree” cuts
• Using IM xml file in classification
• Develop a “Node” structure parsing the xml IM output
• Check of cuts
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GLAST LAT
Bkg Rejection Italy
CT approach
ID
predicate
ID
0/1
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predicate
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GLAST LAT
Bkg Rejection Italy
Signal events split
All
Total
No
Lo
Med
Hi
g(all)
722,594
314,226
122,081
114,224
172,063
64,110
(20.4%)
86,190
(70.6%)
90,201
(79.0%)
138,793
(80.7%)
g(good)
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GLAST LAT
Bkg Rejection Italy
Good Cal E
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GLAST LAT
Bkg Rejection Italy
Starting with Classification Trees
• Use of R program – rpart (recursive partitioning)
• Searching to optimize “goodCal”
• For each step rpart reports the cost-complexity of the tree, the
number of splits, the relative error and finally the error that it
obtains from a process of cross validation, with the
corresponding sigma.
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GLAST LAT
Bkg Rejection Italy
Classification Trees with rpart
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GLAST LAT
Bkg Rejection Italy
Classification Trees with rpart
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GLAST LAT
Bkg Rejection Italy
Classification Trees with rpart
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GLAST LAT
Bkg Rejection Italy
Classification Trees with rpart
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GLAST LAT
Bkg Rejection Italy
One Tree per E bin
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GLAST LAT
Bkg Rejection Italy
One Tree per E bin
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GLAST LAT
Bkg Rejection Italy
One Tree per E bin
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GLAST LAT
Bkg Rejection Italy
Classification Trees with R
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GLAST LAT
Bkg Rejection Italy
rpart Classification
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GLAST LAT
Bkg Rejection Italy
rpart Classification
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GLAST LAT
Bkg Rejection Italy
Error costs
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GLAST LAT
Bkg Rejection Italy
Error Costs
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GLAST LAT
Bkg Rejection Italy
Error Costs
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GLAST LAT
Bkg Rejection Italy
Random Forest
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GLAST LAT
Bkg Rejection Italy
Random Forests
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GLAST LAT
Bkg Rejection Italy
Random Forests
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GLAST LAT
Bkg Rejection Italy
Random Forests
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GLAST LAT
Bkg Rejection Italy
rForest package
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GLAST LAT
Bkg Rejection Italy
Conclusions
• Work is progressing…
• Work on new variables started
• More results will come…
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