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
-2,315.11
M_2
2,630.28
M_3
1,821.32
mL1
2,192.57
mL3
540.04
mE1
3,974.27
mE3
3,655.48
mQ1
3,109.47
mQ3
2,479.29
mU1
2,433.33
mU3
2,570.52
mD1
2,903.29
mD3
2,529.35
At
-4,017.91
Ab
1,635.99
Atau
1,540.74
mu
-313.13
mA
2,417.74
tan(beta)
58.28
The truth!
2
M_1
175.91
M_2
-669.92
M_3
500.80
mL1
1,333.33
mL3
2,325.52
mE1
2,934.54
mE3
1,900.32
mQ1
3,703.95
mQ3
2,757.76
mU1
2,987.63
mU3
1,831.31
mD1
2,511.98
mD3
2,774.83
At
2,912.98
Ab
1,183.93
Atau
2,828.35
mu
-194.59
mA
1,823.04
tan(beta)
33.11
The truth!
3
M_1
-3,942.36
M_2
-3,151.34
M_3
814.56
mL1
1,299.97
mL3
729.06
mE1
1,561.89
mE3
803.90
mQ1
1,951.99
mQ3
3,307.69
mU1
2,017.56
mU3
3,861.56
mD1
3,457.54
mD3
3,764.49
At
2,688.27
Ab
2,384.38
Atau
3,360.69
mu
460.59
mA
2,926.29
tan(beta)
52.56
The truth!
4
M_1
-777.53
M_2
2,741.49
M_3
2,984.92
mL1
999.10
mL3
3,351.05
mE1
2,972.68
mE3
3,311.90
mQ1
2,398.66
mQ3
3,692.15
mU1
834.83
mU3
692.07
mD1
1,632.25
mD3
1,905.37
At
-4,334.40
Ab
2,562.52
Atau
-1,433.66
mu
2,807.53
mA
1,951.79
tan(beta)
18.71
The truth!
5
M_1
1,600.45
M_2
3,957.56
M_3
2,993.45
mL1
3,122.17
mL3
1,959.11
mE1
1,195.59
mE3
1,501.64
mQ1
1,314.28
mQ3
3,219.42
mU1
288.82
mU3
2,023.48
mD1
866.24
mD3
3,664.67
At
4,284.74
Ab
1,574.15
Atau
688.07
mu
486.72
mA
3,968.21
tan(beta)
52.20
The truth!
6
M_1
2,826.46
M_2
-1,481.76
M_3
959.64
mL1
3,742.50
mL3
3,406.27
mE1
3,559.50
mE3
740.82
mQ1
1,343.61
mQ3
1,201.05
mU1
1,356.51
mU3
3,706.42
mD1
836.04
mD3
2,762.95
At
3,354.31
Ab
-219.08
Atau
2,025.98
mu
-230.39
mA
3,102.35
tan(beta)
35.43
The truth!
7
M_1
-494.13
M_2
1,361.78
M_3
2,219.23
mL1
1,220.45
mL3
3,673.02
mE1
1,696.28
mE3
1,768.07
mQ1
1,289.86
mQ3
1,167.81
mU1
2,486.38
mU3
624.97
mD1
1,633.49
mD3
3,339.16
At
1,477.87
Ab
2,859.85
Atau
-287.89
mu
-1,157.57
mA
2,974.26
tan(beta)
15.74
The truth!
8
M_1
365.64
M_2
-3,748.38
M_3
294.91
mL1
439.39
mL3
3,584.75
mE1
916.55
mE3
1,215.43
mQ1
3,726.41
mQ3
1,417.25
mU1
3,152.59
mU3
3,632.50
mD1
1,599.01
mD3
3,900.94
At
-2,943.52
Ab
270.55
Atau
1,017.38
mu
-399.90
mA
3,798.54
tan(beta)
29.33
The truth!
9
M_1
2,281.23
M_2
-325.60
M_3
2,235.05
mL1
655.90
mL3
1,428.11
mE1
3,856.16
mE3
1,244.11
mQ1
3,217.78
mQ3
3,802.42
mU1
660.28
mU3
593.25
mD1
2,949.92
mD3
929.21
At
-3,176.73
Ab
3,705.16
Atau
-1,133.23
mu
3,220.67
mA
3,371.08
tan(beta)
7.57
The truth!
10
M_1
2,530.47
M_2
-1,865.81
M_3
1,067.55
mL1
840.16
mL3
3,691.75
mE1
1,857.53
mE3
1,403.08
mQ1
1,866.51
mQ3
3,765.66
mU1
2,848.67
mU3
3,115.35
mD1
3,191.01
mD3
2,415.25
At
-4,091.04
Ab
-3,231.61
Atau
-3,730.75
mu
266.92
mA
3,432.88
tan(beta)
43.08
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
