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
869.50
M_2
-1,667.38
M_3
3,620.83
mL1
939.03
mL3
1,361.91
mE1
3,556.33
mE3
1,202.76
mQ1
3,505.46
mQ3
1,536.08
mU1
1,394.05
mU3
3,744.48
mD1
3,508.74
mD3
1,211.95
At
3,920.92
Ab
-1,477.78
Atau
1,305.31
mu
176.65
mA
1,148.94
tan(beta)
9.58
The truth!
2
M_1
1,320.05
M_2
3,138.17
M_3
1,759.92
mL1
583.29
mL3
2,525.59
mE1
3,641.97
mE3
3,956.58
mQ1
283.95
mQ3
973.75
mU1
2,036.12
mU3
2,774.86
mD1
3,509.96
mD3
3,140.05
At
2,659.51
Ab
-3,449.83
Atau
1,292.33
mu
-383.01
mA
1,154.86
tan(beta)
32.94
The truth!
3
M_1
1,134.70
M_2
2,413.30
M_3
866.80
mL1
1,382.57
mL3
3,686.84
mE1
2,313.77
mE3
1,486.44
mQ1
2,887.81
mQ3
2,162.36
mU1
2,593.13
mU3
1,536.68
mD1
335.62
mD3
2,063.88
At
2,944.77
Ab
3,710.08
Atau
2,579.99
mu
-279.93
mA
1,400.00
tan(beta)
10.08
The truth!
4
M_1
370.57
M_2
2,549.35
M_3
341.47
mL1
3,067.90
mL3
702.85
mE1
3,944.66
mE3
3,211.03
mQ1
2,591.50
mQ3
295.97
mU1
1,977.40
mU3
2,825.50
mD1
1,699.73
mD3
555.58
At
-2,578.07
Ab
-3,125.17
Atau
-353.12
mu
919.79
mA
1,887.97
tan(beta)
18.69
The truth!
5
M_1
553.86
M_2
3,728.93
M_3
1,294.34
mL1
1,888.45
mL3
3,204.86
mE1
1,383.10
mE3
837.02
mQ1
735.69
mQ3
2,154.20
mU1
404.31
mU3
3,245.12
mD1
1,191.78
mD3
1,749.18
At
-4,779.16
Ab
-3,894.66
Atau
-212.02
mu
4,041.48
mA
1,069.10
tan(beta)
22.15
The truth!
6
M_1
147.18
M_2
622.95
M_3
1,512.02
mL1
2,757.74
mL3
1,032.83
mE1
664.24
mE3
3,266.68
mQ1
366.68
mQ3
3,373.16
mU1
2,504.84
mU3
3,305.62
mD1
2,938.84
mD3
1,329.66
At
4,451.93
Ab
1,057.22
Atau
-2,428.35
mu
-171.39
mA
2,196.60
tan(beta)
11.80
The truth!
7
M_1
-836.19
M_2
176.63
M_3
2,368.62
mL1
2,164.10
mL3
381.59
mE1
338.08
mE3
1,167.52
mQ1
2,306.21
mQ3
1,193.36
mU1
1,504.29
mU3
3,658.57
mD1
1,370.13
mD3
1,557.87
At
-3,078.54
Ab
-661.77
Atau
1,072.51
mu
601.78
mA
2,759.35
tan(beta)
9.55
The truth!
8
M_1
-1,858.52
M_2
-2,432.99
M_3
3,530.48
mL1
507.44
mL3
2,269.51
mE1
1,851.22
mE3
2,522.07
mQ1
925.91
mQ3
2,927.80
mU1
3,559.60
mU3
2,719.27
mD1
3,959.14
mD3
3,311.93
At
3,142.30
Ab
551.54
Atau
-3,104.32
mu
-471.89
mA
2,987.24
tan(beta)
23.35
The truth!
9
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!
10
M_1
-2,256.98
M_2
-3,119.93
M_3
2,227.81
mL1
1,898.90
mL3
508.76
mE1
2,097.45
mE3
3,105.23
mQ1
3,042.07
mQ3
3,086.33
mU1
399.92
mU3
1,134.21
mD1
1,064.84
mD3
3,570.29
At
3,406.45
Ab
2,793.40
Atau
-175.86
mu
-315.42
mA
1,689.83
tan(beta)
18.78
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
