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
636.67
M_2
-1,338.95
M_3
1,131.03
mL1
952.16
mL3
2,259.32
mE1
2,582.26
mE3
3,683.93
mQ1
747.56
mQ3
3,686.18
mU1
1,029.63
mU3
2,741.83
mD1
3,982.27
mD3
2,578.70
At
3,668.92
Ab
3,536.60
Atau
651.89
mu
-273.17
mA
3,056.02
tan(beta)
21.37
The truth!
2
M_1
-3,886.40
M_2
1,559.88
M_3
2,708.18
mL1
1,065.55
mL3
2,725.71
mE1
552.40
mE3
3,101.36
mQ1
1,296.52
mQ3
1,341.41
mU1
3,790.76
mU3
3,614.35
mD1
445.15
mD3
458.42
At
2,490.75
Ab
-2,868.59
Atau
-3,229.34
mu
342.07
mA
1,821.53
tan(beta)
52.16
The truth!
3
M_1
1,570.60
M_2
1,971.93
M_3
3,806.39
mL1
2,596.49
mL3
3,405.56
mE1
1,644.40
mE3
2,986.03
mQ1
1,813.25
mQ3
3,141.45
mU1
2,423.18
mU3
2,695.18
mD1
1,319.55
mD3
3,976.66
At
-3,659.95
Ab
-2,578.59
Atau
-2,872.96
mu
-347.76
mA
1,684.56
tan(beta)
16.88
The truth!
4
M_1
3,435.37
M_2
955.25
M_3
3,416.39
mL1
3,112.13
mL3
3,034.10
mE1
1,911.90
mE3
1,102.72
mQ1
2,260.99
mQ3
3,119.34
mU1
3,764.02
mU3
2,995.76
mD1
3,464.58
mD3
3,511.19
At
4,296.71
Ab
-423.42
Atau
-2,017.62
mu
-181.70
mA
1,877.29
tan(beta)
23.19
The truth!
5
M_1
2,717.88
M_2
498.90
M_3
3,966.22
mL1
3,791.47
mL3
3,423.96
mE1
3,674.92
mE3
2,106.28
mQ1
1,448.05
mQ3
2,406.42
mU1
1,431.62
mU3
3,933.26
mD1
854.50
mD3
3,317.25
At
-3,138.41
Ab
91.96
Atau
1,435.90
mu
592.26
mA
2,587.32
tan(beta)
21.65
The truth!
6
M_1
-137.60
M_2
1,250.00
M_3
2,752.43
mL1
3,681.05
mL3
3,402.67
mE1
2,270.56
mE3
949.43
mQ1
2,653.92
mQ3
3,322.78
mU1
2,914.22
mU3
3,461.58
mD1
2,155.94
mD3
561.57
At
2,446.56
Ab
-3,921.08
Atau
-1,928.48
mu
155.82
mA
2,884.00
tan(beta)
16.64
The truth!
7
M_1
221.67
M_2
209.84
M_3
2,832.74
mL1
2,103.03
mL3
2,564.16
mE1
3,486.15
mE3
3,660.77
mQ1
3,060.94
mQ3
1,095.42
mU1
2,904.74
mU3
3,603.97
mD1
3,645.86
mD3
2,791.78
At
3,971.88
Ab
-2,338.88
Atau
3,152.22
mu
-3,985.56
mA
1,240.18
tan(beta)
5.08
The truth!
8
M_1
2,837.39
M_2
3,881.79
M_3
879.73
mL1
1,826.19
mL3
3,921.00
mE1
272.66
mE3
3,431.79
mQ1
2,513.80
mQ3
2,765.47
mU1
3,428.19
mU3
3,101.47
mD1
552.88
mD3
1,292.72
At
-4,886.59
Ab
-3,116.73
Atau
-3,621.75
mu
-180.64
mA
1,961.60
tan(beta)
20.80
The truth!
9
M_1
-1,394.37
M_2
574.05
M_3
3,089.46
mL1
3,242.00
mL3
2,408.88
mE1
679.64
mE3
2,910.14
mQ1
1,693.00
mQ3
3,820.26
mU1
3,349.63
mU3
3,300.87
mD1
1,477.54
mD3
1,292.24
At
-2,288.94
Ab
464.31
Atau
-2,963.94
mu
1,889.43
mA
1,937.84
tan(beta)
26.14
The truth!
10
M_1
551.10
M_2
1,924.85
M_3
2,330.22
mL1
3,468.03
mL3
3,208.41
mE1
2,638.04
mE3
3,116.82
mQ1
559.95
mQ3
2,188.66
mU1
499.07
mU3
1,186.72
mD1
746.25
mD3
1,904.34
At
-4,063.66
Ab
-1,588.94
Atau
173.57
mu
809.54
mA
3,668.96
tan(beta)
16.52
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
