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
809.62
M_2
-3,905.06
M_3
1,966.74
mL1
1,160.08
mL3
1,201.50
mE1
1,459.64
mE3
2,651.10
mQ1
3,142.48
mQ3
3,298.08
mU1
565.01
mU3
3,617.66
mD1
1,961.42
mD3
2,450.73
At
-3,985.71
Ab
-3,948.36
Atau
-3,080.63
mu
2,966.39
mA
2,151.20
tan(beta)
12.00
The truth!
2
M_1
885.23
M_2
-146.93
M_3
1,015.47
mL1
624.43
mL3
925.51
mE1
1,781.39
mE3
2,910.48
mQ1
708.71
mQ3
3,987.14
mU1
2,013.19
mU3
1,798.75
mD1
3,738.43
mD3
1,341.79
At
3,340.06
Ab
-2,739.47
Atau
1,992.36
mu
-3,646.61
mA
2,536.06
tan(beta)
7.82
The truth!
3
M_1
158.07
M_2
-2,024.54
M_3
2,918.44
mL1
941.09
mL3
902.95
mE1
3,486.50
mE3
3,966.86
mQ1
1,967.86
mQ3
1,630.29
mU1
3,754.98
mU3
2,863.66
mD1
3,775.91
mD3
1,161.30
At
-3,530.95
Ab
2,223.83
Atau
-3,331.14
mu
-163.70
mA
2,024.57
tan(beta)
39.65
The truth!
4
M_1
1,034.60
M_2
727.06
M_3
3,802.57
mL1
3,449.25
mL3
2,699.90
mE1
2,007.11
mE3
1,742.21
mQ1
1,932.62
mQ3
3,946.68
mU1
1,200.93
mU3
2,356.88
mD1
2,827.54
mD3
3,012.45
At
-3,562.97
Ab
1,098.82
Atau
934.88
mu
2,297.34
mA
1,417.35
tan(beta)
32.14
The truth!
5
M_1
705.42
M_2
-2,215.42
M_3
2,491.14
mL1
3,150.57
mL3
1,509.72
mE1
1,966.00
mE3
1,594.10
mQ1
3,505.60
mQ3
2,620.91
mU1
2,648.72
mU3
1,007.87
mD1
1,632.82
mD3
663.24
At
-3,469.16
Ab
-1,871.42
Atau
3,273.29
mu
1,588.56
mA
2,883.61
tan(beta)
21.65
The truth!
6
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!
7
M_1
3,610.61
M_2
-127.60
M_3
489.22
mL1
3,670.53
mL3
2,248.12
mE1
1,831.92
mE3
3,283.26
mQ1
2,607.10
mQ3
2,721.25
mU1
2,157.81
mU3
2,464.95
mD1
1,813.76
mD3
2,181.26
At
-2,280.69
Ab
-282.02
Atau
-1,345.95
mu
-1,395.55
mA
3,839.87
tan(beta)
36.50
The truth!
8
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!
9
M_1
-1,453.50
M_2
256.81
M_3
1,663.94
mL1
2,465.96
mL3
3,702.24
mE1
3,973.65
mE3
853.92
mQ1
1,531.38
mQ3
1,190.27
mU1
2,533.03
mU3
1,979.35
mD1
2,133.35
mD3
2,519.05
At
3,518.39
Ab
3,932.36
Atau
3,936.27
mu
1,401.94
mA
2,297.98
tan(beta)
4.25
The truth!
10
M_1
-611.25
M_2
-902.58
M_3
1,941.25
mL1
2,216.88
mL3
640.49
mE1
2,904.00
mE3
2,676.87
mQ1
1,210.42
mQ3
3,340.36
mU1
3,761.30
mU3
3,756.29
mD1
1,952.46
mD3
3,729.66
At
-3,073.76
Ab
-2,065.12
Atau
2,238.93
mu
612.30
mA
1,551.50
tan(beta)
35.13
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
