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
879.31
M_2
-1,405.79
M_3
767.42
mL1
2,180.58
mL3
2,913.66
mE1
2,103.29
mE3
3,263.79
mQ1
2,617.14
mQ3
3,725.08
mU1
2,178.39
mU3
2,312.35
mD1
3,294.29
mD3
3,196.96
At
-3,469.89
Ab
1,493.88
Atau
-1,841.11
mu
823.06
mA
2,806.88
tan(beta)
22.09
The truth!
2
M_1
-3,786.61
M_2
1,880.05
M_3
1,308.88
mL1
3,683.39
mL3
2,484.22
mE1
1,356.25
mE3
611.77
mQ1
2,648.20
mQ3
2,921.94
mU1
1,129.84
mU3
3,989.60
mD1
595.14
mD3
3,240.94
At
4,244.88
Ab
-816.02
Atau
2,331.26
mu
-364.79
mA
1,610.99
tan(beta)
20.88
The truth!
3
M_1
370.57
M_2
2,549.35
M_3
341.47
mL1
3,067.90
mL3
702.85
mE1
3,944.66
mE3
3,211.03
mQ1
2,591.50
mQ3
295.97
mU1
1,977.40
mU3
2,825.50
mD1
1,699.73
mD3
555.58
At
-2,578.07
Ab
-3,125.17
Atau
-353.12
mu
919.79
mA
1,887.97
tan(beta)
18.69
The truth!
4
M_1
1,556.66
M_2
-1,519.92
M_3
3,459.34
mL1
2,817.50
mL3
3,938.08
mE1
966.52
mE3
474.60
mQ1
3,510.80
mQ3
1,797.24
mU1
2,026.41
mU3
2,387.20
mD1
290.49
mD3
2,801.80
At
-2,829.00
Ab
1,075.12
Atau
-3,164.65
mu
-229.49
mA
2,278.99
tan(beta)
19.02
The truth!
5
M_1
-266.05
M_2
3,942.36
M_3
1,641.19
mL1
2,676.33
mL3
1,836.00
mE1
3,846.84
mE3
3,068.64
mQ1
828.79
mQ3
1,148.30
mU1
1,382.82
mU3
3,418.30
mD1
3,283.42
mD3
208.16
At
-2,937.67
Ab
1,868.35
Atau
1,193.35
mu
274.29
mA
1,692.92
tan(beta)
44.80
The truth!
6
M_1
800.58
M_2
-135.23
M_3
3,079.86
mL1
3,393.47
mL3
1,936.86
mE1
745.70
mE3
691.29
mQ1
2,813.37
mQ3
3,613.45
mU1
411.49
mU3
2,078.88
mD1
1,550.93
mD3
3,879.76
At
-2,839.51
Ab
2,973.63
Atau
-556.14
mu
1,918.80
mA
1,866.56
tan(beta)
54.02
The truth!
7
M_1
-165.29
M_2
164.87
M_3
2,140.50
mL1
733.33
mL3
546.49
mE1
551.57
mE3
3,440.30
mQ1
1,605.27
mQ3
1,286.36
mU1
1,767.83
mU3
3,091.62
mD1
2,238.65
mD3
2,688.50
At
-2,838.73
Ab
-1,529.42
Atau
450.41
mu
3,959.58
mA
1,387.62
tan(beta)
12.79
The truth!
8
M_1
262.80
M_2
1,404.88
M_3
613.15
mL1
1,739.78
mL3
1,737.93
mE1
733.88
mE3
3,581.65
mQ1
399.77
mQ3
716.38
mU1
320.40
mU3
2,469.53
mD1
2,794.16
mD3
535.01
At
-2,915.32
Ab
-533.02
Atau
866.35
mu
574.31
mA
785.62
tan(beta)
18.93
The truth!
9
M_1
-1,859.00
M_2
-220.00
M_3
3,105.51
mL1
2,790.86
mL3
1,611.55
mE1
610.50
mE3
768.95
mQ1
2,560.13
mQ3
1,207.14
mU1
3,026.60
mU3
3,270.64
mD1
261.84
mD3
1,231.56
At
-6,022.78
Ab
133.58
Atau
-3,412.47
mu
563.39
mA
1,813.84
tan(beta)
4.89
The truth!
10
M_1
3,030.27
M_2
588.10
M_3
847.12
mL1
1,507.87
mL3
3,375.20
mE1
1,628.50
mE3
3,113.69
mQ1
2,796.57
mQ3
1,156.28
mU1
3,730.22
mU3
3,106.64
mD1
3,686.54
mD3
3,660.03
At
-3,508.47
Ab
-2,785.54
Atau
2,874.45
mu
3,439.88
mA
1,411.71
tan(beta)
13.01
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
