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
3,411.74
M_2
-2,224.44
M_3
1,180.62
mL1
3,518.39
mL3
2,228.97
mE1
948.16
mE3
2,901.13
mQ1
2,069.77
mQ3
2,132.22
mU1
3,840.80
mU3
2,635.90
mD1
2,374.53
mD3
256.38
At
2,866.02
Ab
-3,558.96
Atau
-3,997.30
mu
262.12
mA
2,682.52
tan(beta)
23.03
The truth!
2
M_1
3,401.44
M_2
-3,235.58
M_3
962.30
mL1
1,394.01
mL3
820.66
mE1
806.68
mE3
2,208.46
mQ1
3,739.45
mQ3
960.76
mU1
332.74
mU3
3,413.10
mD1
1,980.78
mD3
2,968.10
At
-2,701.74
Ab
-257.64
Atau
-1,577.22
mu
-416.46
mA
3,436.80
tan(beta)
56.40
The truth!
3
M_1
1,216.00
M_2
3,947.79
M_3
1,078.50
mL1
2,218.86
mL3
1,852.87
mE1
1,289.46
mE3
2,631.46
mQ1
3,419.04
mQ3
1,977.89
mU1
3,286.83
mU3
3,651.91
mD1
1,202.76
mD3
2,869.74
At
-3,505.84
Ab
-2,593.10
Atau
613.48
mu
459.65
mA
2,360.89
tan(beta)
29.82
The truth!
4
M_1
311.07
M_2
-1,697.60
M_3
262.76
mL1
2,757.23
mL3
658.86
mE1
3,021.67
mE3
2,260.32
mQ1
3,140.40
mQ3
903.55
mU1
3,771.31
mU3
3,406.99
mD1
2,291.59
mD3
2,104.39
At
-2,981.92
Ab
2,062.32
Atau
3,552.09
mu
3,108.82
mA
2,835.88
tan(beta)
44.16
The truth!
5
M_1
-2,484.08
M_2
-1,081.29
M_3
1,809.98
mL1
911.64
mL3
3,880.67
mE1
893.68
mE3
1,192.43
mQ1
2,889.55
mQ3
3,069.99
mU1
3,412.04
mU3
2,841.35
mD1
3,966.45
mD3
997.14
At
-3,909.24
Ab
-3,298.65
Atau
2,534.38
mu
410.10
mA
1,146.96
tan(beta)
44.92
The truth!
6
M_1
853.27
M_2
-817.02
M_3
3,266.59
mL1
2,847.28
mL3
2,524.18
mE1
3,859.60
mE3
3,063.43
mQ1
3,643.46
mQ3
2,716.63
mU1
1,858.35
mU3
1,454.94
mD1
1,239.27
mD3
2,740.79
At
-3,903.78
Ab
3,917.23
Atau
649.76
mu
2,690.89
mA
3,450.15
tan(beta)
34.33
The truth!
7
M_1
-1,894.40
M_2
-3,713.20
M_3
3,607.66
mL1
1,725.58
mL3
3,109.44
mE1
2,336.25
mE3
1,556.47
mQ1
702.60
mQ3
2,649.70
mU1
1,527.57
mU3
3,220.60
mD1
1,964.58
mD3
2,996.35
At
-4,619.87
Ab
-3,210.59
Atau
2,837.47
mu
218.60
mA
1,478.49
tan(beta)
26.59
The truth!
8
M_1
-2,456.28
M_2
3,319.81
M_3
2,091.59
mL1
933.63
mL3
1,605.02
mE1
2,947.71
mE3
2,871.35
mQ1
2,032.68
mQ3
3,080.70
mU1
408.95
mU3
3,160.48
mD1
575.48
mD3
414.38
At
-4,266.83
Ab
-917.33
Atau
-1,682.60
mu
-249.68
mA
3,904.99
tan(beta)
30.80
The truth!
9
M_1
3,468.92
M_2
905.59
M_3
2,398.43
mL1
3,182.49
mL3
1,366.97
mE1
1,664.56
mE3
1,048.63
mQ1
3,907.29
mQ3
2,816.39
mU1
2,524.13
mU3
2,508.75
mD1
2,441.34
mD3
295.43
At
-3,678.76
Ab
2,217.03
Atau
474.78
mu
-482.29
mA
2,158.07
tan(beta)
52.94
The truth!
10
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!
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
