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
1,163.97
M_2
527.60
M_3
3,853.06
mL1
1,115.06
mL3
3,379.02
mE1
2,593.99
mE3
1,839.14
mQ1
3,985.87
mQ3
2,883.42
mU1
1,329.27
mU3
2,634.85
mD1
1,386.05
mD3
801.54
At
-4,094.10
Ab
1,273.48
Atau
2,727.78
mu
977.38
mA
2,399.00
tan(beta)
27.37
The truth!
2
M_1
141.96
M_2
-3,175.17
M_3
1,166.53
mL1
3,972.03
mL3
2,419.00
mE1
138.36
mE3
532.39
mQ1
2,480.84
mQ3
2,758.50
mU1
567.79
mU3
3,923.25
mD1
2,773.24
mD3
3,430.97
At
-5,009.81
Ab
3,319.99
Atau
1,156.38
mu
2,167.14
mA
1,952.99
tan(beta)
12.41
The truth!
3
M_1
-2,272.07
M_2
1,491.37
M_3
2,878.65
mL1
2,678.89
mL3
3,902.54
mE1
1,966.74
mE3
3,126.01
mQ1
2,426.81
mQ3
3,275.50
mU1
2,287.69
mU3
3,332.62
mD1
380.45
mD3
2,640.90
At
-3,706.55
Ab
3,866.22
Atau
590.57
mu
-540.91
mA
2,408.46
tan(beta)
49.26
The truth!
4
M_1
-1,779.39
M_2
136.97
M_3
2,258.70
mL1
3,528.61
mL3
851.48
mE1
1,523.68
mE3
1,501.65
mQ1
2,662.31
mQ3
3,834.33
mU1
1,354.91
mU3
3,359.29
mD1
1,147.54
mD3
2,738.35
At
3,714.59
Ab
1,117.08
Atau
-263.07
mu
-673.92
mA
1,733.71
tan(beta)
32.83
The truth!
5
M_1
329.40
M_2
-317.14
M_3
1,816.32
mL1
2,192.20
mL3
1,521.28
mE1
3,194.58
mE3
2,809.50
mQ1
3,439.54
mQ3
2,882.80
mU1
771.66
mU3
3,327.90
mD1
526.84
mD3
1,754.96
At
-4,478.90
Ab
-1,744.72
Atau
1,989.48
mu
3,948.56
mA
3,439.16
tan(beta)
57.90
The truth!
6
M_1
-3,375.11
M_2
-1,047.39
M_3
2,079.69
mL1
1,675.91
mL3
876.08
mE1
2,049.66
mE3
3,812.91
mQ1
3,126.35
mQ3
3,935.84
mU1
1,628.56
mU3
3,896.73
mD1
1,903.76
mD3
1,316.54
At
-3,066.38
Ab
1,972.92
Atau
-2,845.34
mu
663.55
mA
2,576.99
tan(beta)
46.99
The truth!
7
M_1
916.90
M_2
901.71
M_3
3,572.66
mL1
1,225.94
mL3
3,633.52
mE1
3,763.47
mE3
2,957.09
mQ1
3,839.98
mQ3
3,796.68
mU1
2,842.90
mU3
3,036.21
mD1
2,452.63
mD3
860.31
At
2,353.16
Ab
2,105.14
Atau
-3,746.52
mu
-1,024.10
mA
2,204.14
tan(beta)
20.44
The truth!
8
M_1
-1,261.17
M_2
857.87
M_3
2,748.89
mL1
1,935.87
mL3
2,777.66
mE1
3,873.57
mE3
3,520.28
mQ1
3,766.33
mQ3
785.92
mU1
744.89
mU3
2,643.06
mD1
1,025.75
mD3
2,050.22
At
2,600.48
Ab
2,803.11
Atau
-1,574.40
mu
-241.59
mA
3,201.24
tan(beta)
29.41
The truth!
9
M_1
-159.46
M_2
-3,449.53
M_3
662.61
mL1
549.14
mL3
2,683.64
mE1
2,604.12
mE3
2,547.79
mQ1
2,583.28
mQ3
3,191.11
mU1
986.39
mU3
3,653.14
mD1
521.02
mD3
823.55
At
-3,601.90
Ab
70.58
Atau
3,703.97
mu
163.62
mA
1,042.50
tan(beta)
59.46
The truth!
10
M_1
-2,580.45
M_2
-1,568.21
M_3
2,493.29
mL1
3,165.24
mL3
1,406.59
mE1
2,280.18
mE3
926.53
mQ1
3,459.81
mQ3
2,362.37
mU1
2,653.21
mU3
2,631.05
mD1
3,221.43
mD3
377.29
At
-3,040.27
Ab
-3,455.96
Atau
2,764.26
mu
-141.47
mA
3,125.71
tan(beta)
32.37
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
