S. Caron, J.S. Kim, K. Rolbiecki, R. Ruiz de Austri and B. Stienen, The BSM-AI project: SUSY-AI - Generalizing LHC limits on Supersymmetry with Machine Learning [arXiv:1605.02797]
SUSY-AI is a machine learning tool that is able to provide in a fraction of a second the exclusion of a pMSSM (sub)model point. This website provides a simple online interface for quick determination of exclusion of a model point using the results of ATLAS Run-I (8TeV) and ATLAS Run-II (13TeV). The papers associated with this data can be found here.
The full version of SUSY-AI is faster and can provide predicions for multiple modelpoints at the same time. It is under continuing active development and can be downloaded from the hepforge project page.
Classify alongside SUSY-AI and see how good a classifier you are
Below you'll find 10 points in the 19-dimensional pMSSM, defined by their coordinates. Based on these coordinates you could be able to classify each of them as excluded or allowed. You could... but are you able to this correctly for the 13TeV results? And are you able to beat the machine in doing so? Start classifying to find out!
P.S. Every refresh of this page gives you new points to predict!
1
M_1
-2,322.20
M_2
-250.20
M_3
3,007.28
mL1
2,698.42
mL3
1,865.42
mE1
2,557.22
mE3
877.33
mQ1
2,506.06
mQ3
3,461.29
mU1
3,710.54
mU3
3,831.23
mD1
996.81
mD3
2,346.49
At
972.94
Ab
2,994.65
Atau
-817.94
mu
-171.44
mA
2,921.50
tan(beta)
52.39
The truth!
2
M_1
1,990.45
M_2
-3,137.93
M_3
2,619.71
mL1
2,252.27
mL3
562.59
mE1
3,390.20
mE3
2,160.68
mQ1
2,530.23
mQ3
3,458.20
mU1
1,598.16
mU3
1,545.99
mD1
906.08
mD3
2,504.97
At
2,857.13
Ab
1,805.77
Atau
225.47
mu
232.34
mA
3,576.24
tan(beta)
59.04
The truth!
3
M_1
-346.77
M_2
-2,322.39
M_3
2,396.43
mL1
2,877.09
mL3
3,035.84
mE1
268.56
mE3
1,263.50
mQ1
417.12
mQ3
3,347.18
mU1
1,705.46
mU3
3,094.32
mD1
1,675.13
mD3
3,864.59
At
-5,192.75
Ab
2,142.56
Atau
3,230.45
mu
900.14
mA
2,286.05
tan(beta)
9.58
The truth!
4
M_1
444.69
M_2
-422.71
M_3
3,117.93
mL1
2,221.98
mL3
3,483.39
mE1
2,120.56
mE3
3,063.50
mQ1
1,358.24
mQ3
3,690.72
mU1
1,772.13
mU3
2,751.19
mD1
3,003.89
mD3
2,072.17
At
2,700.14
Ab
953.76
Atau
3,059.05
mu
924.30
mA
3,445.66
tan(beta)
32.79
The truth!
5
M_1
1,500.31
M_2
-3,434.11
M_3
728.58
mL1
3,057.19
mL3
368.61
mE1
3,711.62
mE3
3,425.41
mQ1
1,140.07
mQ3
1,167.28
mU1
1,586.38
mU3
3,877.74
mD1
3,541.26
mD3
980.04
At
3,630.09
Ab
2,907.41
Atau
3,594.97
mu
-148.19
mA
2,532.13
tan(beta)
17.89
The truth!
6
M_1
841.88
M_2
976.05
M_3
2,137.70
mL1
3,037.01
mL3
3,287.60
mE1
3,322.95
mE3
1,135.67
mQ1
3,825.02
mQ3
3,786.49
mU1
989.68
mU3
3,540.23
mD1
3,804.74
mD3
2,906.06
At
-4,013.70
Ab
2,376.52
Atau
-3,226.18
mu
845.13
mA
2,110.73
tan(beta)
57.56
The truth!
7
M_1
-1,807.43
M_2
-473.61
M_3
2,442.44
mL1
817.29
mL3
2,963.82
mE1
449.27
mE3
1,128.87
mQ1
3,955.53
mQ3
3,406.93
mU1
2,279.33
mU3
1,430.97
mD1
556.20
mD3
1,095.32
At
-3,582.78
Ab
-3,715.71
Atau
-1,072.99
mu
490.75
mA
1,661.49
tan(beta)
38.15
The truth!
8
M_1
-210.93
M_2
2,653.15
M_3
3,636.84
mL1
2,774.83
mL3
1,833.50
mE1
998.40
mE3
2,939.88
mQ1
1,820.23
mQ3
2,695.95
mU1
3,673.46
mU3
1,510.83
mD1
723.86
mD3
913.58
At
-3,548.09
Ab
-2,317.19
Atau
-3,649.71
mu
240.73
mA
3,252.58
tan(beta)
20.83
The truth!
9
M_1
3,507.14
M_2
3,995.40
M_3
725.93
mL1
697.84
mL3
2,874.61
mE1
2,782.52
mE3
3,654.38
mQ1
554.02
mQ3
529.21
mU1
619.05
mU3
3,248.31
mD1
1,944.47
mD3
395.96
At
-3,554.75
Ab
247.76
Atau
593.32
mu
198.60
mA
2,910.71
tan(beta)
18.42
The truth!
10
M_1
291.98
M_2
-2,324.79
M_3
745.63
mL1
2,837.74
mL3
908.44
mE1
1,933.60
mE3
3,913.16
mQ1
830.85
mQ3
2,009.67
mU1
912.58
mU3
3,490.29
mD1
234.61
mD3
115.65
At
-4,046.39
Ab
-1,018.93
Atau
677.97
mu
2,331.06
mA
1,554.90
tan(beta)
6.10
The truth!
SUSY-AI and SUSY-AI Online were developed by S. Caron, J.S. Kim, K. Rolbiecki, R. Ruiz de Austri and B. Stienen. If you encounter any problems, don't hesitate to contact us! SUSY-AI and SUSY-AI Online (c) 2017
