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
-3,614.02
M_2
-2,712.94
M_3
3,908.43
mL1
3,270.84
mL3
2,266.63
mE1
1,011.75
mE3
1,019.96
mQ1
1,629.85
mQ3
3,558.16
mU1
3,152.57
mU3
1,341.92
mD1
2,939.55
mD3
3,699.36
At
-4,215.55
Ab
-2,342.92
Atau
-2,247.09
mu
193.26
mA
3,055.17
tan(beta)
49.56
The truth!
2
M_1
-601.39
M_2
-3,091.51
M_3
2,426.81
mL1
1,012.24
mL3
3,747.08
mE1
2,970.65
mE3
3,578.47
mQ1
1,298.95
mQ3
2,065.89
mU1
1,387.38
mU3
1,606.53
mD1
2,390.57
mD3
491.78
At
3,141.07
Ab
2,105.21
Atau
2,359.90
mu
2,063.80
mA
3,167.15
tan(beta)
32.65
The truth!
3
M_1
-2,517.29
M_2
1,940.15
M_3
1,469.97
mL1
686.61
mL3
2,147.89
mE1
1,277.72
mE3
1,284.80
mQ1
2,729.63
mQ3
3,318.25
mU1
2,907.42
mU3
3,836.80
mD1
1,595.09
mD3
3,709.59
At
2,581.72
Ab
-2,453.66
Atau
-3,510.14
mu
-503.47
mA
1,374.13
tan(beta)
37.17
The truth!
4
M_1
558.50
M_2
-2,723.54
M_3
1,566.80
mL1
3,167.07
mL3
2,315.19
mE1
788.54
mE3
2,829.09
mQ1
1,759.05
mQ3
551.63
mU1
666.71
mU3
2,180.01
mD1
3,162.60
mD3
2,223.46
At
2,653.94
Ab
-708.00
Atau
1,229.03
mu
2,851.06
mA
4,017.52
tan(beta)
58.04
The truth!
5
M_1
-1,160.42
M_2
3,653.26
M_3
1,891.93
mL1
259.65
mL3
3,172.43
mE1
2,017.44
mE3
1,032.51
mQ1
966.01
mQ3
3,717.28
mU1
3,829.22
mU3
3,764.73
mD1
2,721.10
mD3
1,738.46
At
-4,168.46
Ab
-1,180.58
Atau
-3,763.90
mu
-283.06
mA
2,814.93
tan(beta)
56.56
The truth!
6
M_1
-2,935.16
M_2
-2,469.07
M_3
2,071.73
mL1
1,296.90
mL3
1,103.15
mE1
1,822.28
mE3
831.47
mQ1
794.59
mQ3
3,155.19
mU1
2,022.62
mU3
3,264.28
mD1
787.83
mD3
3,312.75
At
-4,843.22
Ab
-2,975.88
Atau
1,638.24
mu
673.50
mA
1,949.49
tan(beta)
26.29
The truth!
7
M_1
-3,746.36
M_2
2,956.82
M_3
660.82
mL1
3,713.86
mL3
1,748.43
mE1
778.23
mE3
2,439.69
mQ1
1,431.60
mQ3
2,281.97
mU1
2,868.52
mU3
3,899.57
mD1
3,025.33
mD3
2,912.35
At
3,694.86
Ab
-3,665.22
Atau
-911.43
mu
-276.89
mA
3,325.52
tan(beta)
11.56
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
-1,060.66
M_2
-2,831.47
M_3
3,062.10
mL1
1,453.25
mL3
3,022.51
mE1
1,841.56
mE3
1,280.47
mQ1
1,922.48
mQ3
2,551.69
mU1
3,413.90
mU3
3,620.31
mD1
860.39
mD3
3,897.88
At
-3,910.11
Ab
-2,900.73
Atau
160.16
mu
2,838.92
mA
3,861.18
tan(beta)
6.41
The truth!
10
M_1
45.68
M_2
-3,387.98
M_3
2,747.03
mL1
1,506.13
mL3
1,165.89
mE1
1,270.77
mE3
3,004.92
mQ1
3,753.11
mQ3
1,383.00
mU1
3,459.24
mU3
2,746.98
mD1
3,139.91
mD3
2,040.13
At
-5,951.37
Ab
-1,993.81
Atau
89.61
mu
163.49
mA
3,944.86
tan(beta)
18.66
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
