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
646.50
M_2
1,208.48
M_3
1,205.90
mL1
3,287.70
mL3
2,216.49
mE1
2,295.29
mE3
1,521.53
mQ1
765.40
mQ3
2,954.29
mU1
2,929.61
mU3
2,523.74
mD1
526.20
mD3
3,392.85
At
-3,860.52
Ab
83.81
Atau
2,221.14
mu
-937.37
mA
3,376.18
tan(beta)
41.36
The truth!
2
M_1
2,691.94
M_2
3,289.08
M_3
3,562.65
mL1
259.11
mL3
2,367.45
mE1
882.82
mE3
3,595.89
mQ1
1,999.94
mQ3
3,179.69
mU1
3,827.37
mU3
2,278.56
mD1
1,676.65
mD3
3,113.20
At
-4,541.23
Ab
-2,148.98
Atau
-3,744.68
mu
-222.41
mA
3,829.01
tan(beta)
51.71
The truth!
3
M_1
2,118.90
M_2
-453.80
M_3
3,679.94
mL1
3,843.88
mL3
502.41
mE1
3,548.97
mE3
2,328.50
mQ1
2,431.16
mQ3
3,030.28
mU1
838.68
mU3
2,204.64
mD1
510.26
mD3
626.12
At
2,846.19
Ab
-3,889.31
Atau
-2,284.37
mu
1,160.15
mA
3,465.67
tan(beta)
28.51
The truth!
4
M_1
3,441.03
M_2
3,750.86
M_3
3,866.11
mL1
921.79
mL3
3,359.56
mE1
3,615.87
mE3
3,440.60
mQ1
369.63
mQ3
3,898.90
mU1
207.96
mU3
3,940.80
mD1
612.26
mD3
2,303.33
At
6,271.32
Ab
-593.53
Atau
-1,281.71
mu
190.10
mA
2,958.95
tan(beta)
18.67
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
-1,915.68
M_2
2,857.30
M_3
853.01
mL1
756.46
mL3
3,446.67
mE1
2,441.00
mE3
830.70
mQ1
3,080.85
mQ3
1,399.31
mU1
3,797.04
mU3
3,498.91
mD1
1,158.71
mD3
2,608.12
At
2,991.54
Ab
1,856.55
Atau
-1,677.85
mu
-234.32
mA
2,481.09
tan(beta)
54.02
The truth!
7
M_1
1,904.92
M_2
970.68
M_3
2,279.47
mL1
2,996.04
mL3
1,979.65
mE1
689.22
mE3
1,648.97
mQ1
1,086.06
mQ3
1,818.75
mU1
3,230.60
mU3
2,387.58
mD1
2,006.17
mD3
1,116.09
At
3,804.12
Ab
435.45
Atau
2,185.02
mu
-484.12
mA
779.95
tan(beta)
6.47
The truth!
8
M_1
2,036.55
M_2
751.78
M_3
1,041.18
mL1
1,581.45
mL3
624.62
mE1
1,066.00
mE3
1,187.71
mQ1
1,364.26
mQ3
2,015.17
mU1
3,483.13
mU3
1,867.48
mD1
1,473.60
mD3
3,985.56
At
-2,729.25
Ab
-1,291.91
Atau
1,857.35
mu
296.13
mA
2,094.62
tan(beta)
33.35
The truth!
9
M_1
-2,410.48
M_2
1,232.78
M_3
2,837.48
mL1
1,163.05
mL3
2,384.15
mE1
3,036.99
mE3
1,350.61
mQ1
2,433.66
mQ3
3,905.57
mU1
904.17
mU3
1,444.39
mD1
2,820.15
mD3
3,360.93
At
2,903.51
Ab
-3,968.87
Atau
-3,080.17
mu
-184.77
mA
1,720.69
tan(beta)
16.05
The truth!
10
M_1
1,190.16
M_2
2,500.28
M_3
2,863.55
mL1
3,885.76
mL3
3,154.91
mE1
1,459.81
mE3
2,073.34
mQ1
454.94
mQ3
2,432.36
mU1
773.12
mU3
1,722.66
mD1
1,912.73
mD3
1,298.83
At
4,463.54
Ab
-1,121.71
Atau
1,726.78
mu
-392.58
mA
2,083.42
tan(beta)
5.25
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
