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
213.07
M_2
-1,418.19
M_3
1,585.08
mL1
467.40
mL3
1,494.79
mE1
3,042.67
mE3
3,367.06
mQ1
2,632.94
mQ3
2,804.88
mU1
927.19
mU3
1,922.80
mD1
3,674.79
mD3
1,179.05
At
-3,884.65
Ab
-3,617.49
Atau
-2,226.48
mu
-208.07
mA
981.34
tan(beta)
6.62
The truth!
2
M_1
-3,858.71
M_2
-3,782.89
M_3
3,510.27
mL1
1,248.28
mL3
1,878.51
mE1
2,398.42
mE3
3,697.76
mQ1
3,363.71
mQ3
2,331.97
mU1
3,371.82
mU3
2,868.49
mD1
1,904.62
mD3
1,414.78
At
-4,918.16
Ab
-600.07
Atau
-1,263.81
mu
-346.97
mA
2,460.34
tan(beta)
6.40
The truth!
3
M_1
636.67
M_2
-1,338.95
M_3
1,131.03
mL1
952.16
mL3
2,259.32
mE1
2,582.26
mE3
3,683.93
mQ1
747.56
mQ3
3,686.18
mU1
1,029.63
mU3
2,741.83
mD1
3,982.27
mD3
2,578.70
At
3,668.92
Ab
3,536.60
Atau
651.89
mu
-273.17
mA
3,056.02
tan(beta)
21.37
The truth!
4
M_1
-1,262.19
M_2
-3,064.49
M_3
647.31
mL1
207.16
mL3
2,590.81
mE1
706.11
mE3
3,564.93
mQ1
1,453.91
mQ3
3,758.29
mU1
3,840.44
mU3
3,326.33
mD1
1,904.24
mD3
1,615.73
At
4,516.67
Ab
-2,725.89
Atau
945.87
mu
-342.38
mA
3,442.65
tan(beta)
14.85
The truth!
5
M_1
-3,291.65
M_2
1,843.60
M_3
2,981.57
mL1
897.31
mL3
1,549.15
mE1
3,956.01
mE3
762.89
mQ1
2,534.79
mQ3
2,633.99
mU1
3,283.61
mU3
2,907.34
mD1
3,626.45
mD3
279.05
At
-3,172.41
Ab
-2,413.95
Atau
2,442.61
mu
527.39
mA
3,704.87
tan(beta)
31.41
The truth!
6
M_1
3,590.60
M_2
3,884.58
M_3
1,921.42
mL1
3,437.79
mL3
1,904.92
mE1
3,776.89
mE3
833.59
mQ1
521.15
mQ3
2,925.74
mU1
2,685.76
mU3
2,334.24
mD1
1,698.72
mD3
266.90
At
-3,588.99
Ab
-3,302.83
Atau
3,447.94
mu
393.08
mA
1,209.84
tan(beta)
34.61
The truth!
7
M_1
-955.81
M_2
2,561.53
M_3
1,950.63
mL1
1,646.76
mL3
3,937.67
mE1
1,845.18
mE3
3,849.16
mQ1
1,004.48
mQ3
2,175.85
mU1
800.90
mU3
3,001.77
mD1
2,056.06
mD3
1,123.82
At
-3,692.00
Ab
-1,768.29
Atau
946.52
mu
-1,715.61
mA
3,656.98
tan(beta)
12.00
The truth!
8
M_1
2,507.41
M_2
1,884.95
M_3
2,821.25
mL1
972.05
mL3
542.27
mE1
3,098.04
mE3
212.18
mQ1
1,682.53
mQ3
2,114.21
mU1
1,718.17
mU3
3,299.45
mD1
1,142.02
mD3
3,623.82
At
2,773.58
Ab
-390.51
Atau
-1,852.48
mu
-221.12
mA
2,636.01
tan(beta)
30.72
The truth!
9
M_1
2,811.37
M_2
773.54
M_3
2,728.84
mL1
1,560.17
mL3
835.53
mE1
2,324.12
mE3
3,026.70
mQ1
2,514.27
mQ3
3,390.47
mU1
1,420.00
mU3
2,066.82
mD1
3,775.42
mD3
3,911.05
At
-3,368.05
Ab
1,661.07
Atau
-3,881.75
mu
-668.35
mA
3,232.88
tan(beta)
58.77
The truth!
10
M_1
140.60
M_2
-2,371.23
M_3
839.76
mL1
2,135.60
mL3
3,991.96
mE1
1,023.51
mE3
3,146.79
mQ1
329.13
mQ3
3,261.38
mU1
965.77
mU3
3,418.26
mD1
1,796.88
mD3
3,807.84
At
4,293.80
Ab
-3,866.17
Atau
649.41
mu
140.10
mA
2,141.49
tan(beta)
26.80
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
