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
3,357.77
M_2
325.98
M_3
3,187.74
mL1
3,838.85
mL3
3,641.55
mE1
829.90
mE3
3,642.25
mQ1
530.03
mQ3
2,715.86
mU1
1,552.90
mU3
2,751.11
mD1
3,364.17
mD3
886.77
At
-3,420.70
Ab
1,566.75
Atau
-3,522.93
mu
2,519.34
mA
3,348.45
tan(beta)
40.29
The truth!
2
M_1
-3,113.74
M_2
-532.51
M_3
3,598.36
mL1
3,445.41
mL3
1,372.63
mE1
3,788.02
mE3
696.13
mQ1
967.53
mQ3
3,869.20
mU1
1,579.79
mU3
3,884.81
mD1
1,843.41
mD3
177.16
At
-2,166.91
Ab
-43.73
Atau
1,680.50
mu
1,068.39
mA
2,638.28
tan(beta)
13.37
The truth!
3
M_1
-2,726.42
M_2
2,301.54
M_3
1,798.93
mL1
1,593.91
mL3
3,299.29
mE1
2,376.50
mE3
2,689.09
mQ1
1,337.86
mQ3
3,285.24
mU1
1,058.22
mU3
3,090.55
mD1
3,724.91
mD3
1,403.24
At
4,319.30
Ab
3,374.14
Atau
2,612.17
mu
-987.14
mA
2,352.99
tan(beta)
24.19
The truth!
4
M_1
1,270.04
M_2
185.88
M_3
3,528.71
mL1
3,638.42
mL3
1,564.39
mE1
2,670.22
mE3
620.03
mQ1
3,397.97
mQ3
2,813.77
mU1
1,361.18
mU3
1,210.27
mD1
935.38
mD3
2,586.63
At
-4,760.02
Ab
-3,260.05
Atau
-2,385.15
mu
3,985.47
mA
3,646.01
tan(beta)
29.01
The truth!
5
M_1
-752.80
M_2
-3,798.70
M_3
2,592.46
mL1
2,713.68
mL3
1,047.01
mE1
1,646.64
mE3
2,316.10
mQ1
2,310.10
mQ3
2,099.94
mU1
3,311.04
mU3
995.64
mD1
759.58
mD3
3,717.27
At
2,924.08
Ab
524.34
Atau
2,049.35
mu
-1,133.81
mA
983.96
tan(beta)
28.52
The truth!
6
M_1
-3,745.34
M_2
-935.70
M_3
2,677.37
mL1
3,686.85
mL3
3,405.45
mE1
2,297.23
mE3
1,935.37
mQ1
951.04
mQ3
1,964.23
mU1
1,384.12
mU3
1,833.27
mD1
1,250.72
mD3
1,885.03
At
-3,800.53
Ab
-1,961.93
Atau
1,334.13
mu
2,749.11
mA
2,387.45
tan(beta)
24.63
The truth!
7
M_1
-580.97
M_2
553.03
M_3
1,822.09
mL1
3,893.58
mL3
674.34
mE1
1,437.11
mE3
2,296.76
mQ1
1,726.02
mQ3
3,961.41
mU1
932.29
mU3
3,013.50
mD1
928.16
mD3
3,229.00
At
3,930.58
Ab
274.91
Atau
1,950.69
mu
-1,239.58
mA
1,822.11
tan(beta)
8.06
The truth!
8
M_1
2,628.92
M_2
1,361.91
M_3
1,572.21
mL1
905.85
mL3
3,054.61
mE1
1,754.58
mE3
946.25
mQ1
3,307.38
mQ3
3,670.24
mU1
1,006.46
mU3
1,084.26
mD1
2,251.16
mD3
3,766.33
At
3,115.77
Ab
-178.84
Atau
-2,485.24
mu
-860.06
mA
1,823.58
tan(beta)
16.81
The truth!
9
M_1
-314.55
M_2
-3,833.41
M_3
2,912.21
mL1
1,039.82
mL3
1,582.19
mE1
2,058.46
mE3
962.68
mQ1
2,795.01
mQ3
3,259.71
mU1
1,725.54
mU3
2,938.94
mD1
3,556.45
mD3
2,245.28
At
-3,807.75
Ab
140.70
Atau
2,806.49
mu
3,410.16
mA
969.26
tan(beta)
15.31
The truth!
10
M_1
1,216.83
M_2
1,153.24
M_3
2,042.48
mL1
752.20
mL3
2,458.82
mE1
1,399.66
mE3
3,113.80
mQ1
1,522.47
mQ3
2,159.34
mU1
229.64
mU3
2,888.42
mD1
3,210.56
mD3
282.75
At
3,543.90
Ab
3,535.71
Atau
3,425.16
mu
-440.01
mA
2,190.70
tan(beta)
14.70
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
