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
-2,908.36
M_2
240.13
M_3
933.15
mL1
3,304.04
mL3
1,584.41
mE1
2,939.52
mE3
1,304.87
mQ1
1,124.80
mQ3
3,998.20
mU1
357.47
mU3
3,627.36
mD1
3,651.92
mD3
3,201.24
At
6,201.89
Ab
1,706.02
Atau
623.31
mu
1,964.44
mA
2,806.83
tan(beta)
4.91
The truth!
2
M_1
-340.50
M_2
322.97
M_3
1,770.74
mL1
3,454.94
mL3
3,620.93
mE1
2,965.92
mE3
942.46
mQ1
3,572.20
mQ3
3,907.79
mU1
1,636.72
mU3
3,875.79
mD1
1,919.04
mD3
2,690.93
At
-4,552.70
Ab
2,350.92
Atau
2,567.85
mu
2,785.39
mA
3,206.39
tan(beta)
11.68
The truth!
3
M_1
766.60
M_2
2,037.12
M_3
3,952.93
mL1
3,832.78
mL3
1,685.86
mE1
881.26
mE3
808.60
mQ1
3,972.75
mQ3
2,282.38
mU1
3,696.43
mU3
2,758.98
mD1
2,980.08
mD3
577.20
At
-3,665.16
Ab
466.60
Atau
3,840.07
mu
-112.54
mA
2,570.24
tan(beta)
9.19
The truth!
4
M_1
2,840.94
M_2
-945.55
M_3
3,860.65
mL1
2,414.38
mL3
1,582.22
mE1
1,365.66
mE3
2,735.28
mQ1
3,066.76
mQ3
1,555.79
mU1
1,047.85
mU3
3,401.22
mD1
2,422.50
mD3
720.46
At
-4,257.77
Ab
-2,646.23
Atau
-1,340.83
mu
-580.43
mA
2,598.14
tan(beta)
12.70
The truth!
5
M_1
-580.97
M_2
553.03
M_3
1,822.09
mL1
3,893.58
mL3
674.34
mE1
1,437.11
mE3
2,296.76
mQ1
1,726.02
mQ3
3,961.41
mU1
932.29
mU3
3,013.50
mD1
928.16
mD3
3,229.00
At
3,930.58
Ab
274.91
Atau
1,950.69
mu
-1,239.58
mA
1,822.11
tan(beta)
8.06
The truth!
6
M_1
1,054.61
M_2
-809.59
M_3
1,452.17
mL1
3,206.39
mL3
2,922.68
mE1
2,485.98
mE3
1,399.54
mQ1
2,820.99
mQ3
1,951.09
mU1
2,054.00
mU3
2,900.65
mD1
3,354.05
mD3
3,295.65
At
2,628.06
Ab
692.50
Atau
-2,622.10
mu
-3,596.28
mA
2,572.14
tan(beta)
17.31
The truth!
7
M_1
-2,433.54
M_2
-1,983.24
M_3
2,732.02
mL1
1,201.69
mL3
1,500.60
mE1
541.38
mE3
1,542.99
mQ1
720.65
mQ3
2,765.78
mU1
3,158.19
mU3
3,387.72
mD1
2,493.54
mD3
1,994.32
At
-4,201.41
Ab
348.83
Atau
2,157.87
mu
466.32
mA
1,026.98
tan(beta)
28.57
The truth!
8
M_1
430.38
M_2
2,567.94
M_3
2,311.69
mL1
3,734.74
mL3
495.21
mE1
2,356.97
mE3
682.27
mQ1
1,375.90
mQ3
2,135.67
mU1
337.75
mU3
1,339.62
mD1
783.15
mD3
3,594.33
At
-3,740.90
Ab
2,440.62
Atau
1,653.37
mu
1,744.56
mA
3,220.57
tan(beta)
45.29
The truth!
9
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!
10
M_1
-2,460.61
M_2
275.09
M_3
3,991.84
mL1
1,876.85
mL3
769.24
mE1
2,152.91
mE3
3,836.62
mQ1
710.37
mQ3
3,611.46
mU1
3,528.05
mU3
3,704.03
mD1
1,669.39
mD3
1,271.26
At
-4,785.37
Ab
-711.83
Atau
385.81
mu
1,649.86
mA
2,350.86
tan(beta)
52.30
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
