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
-1,165.22
M_2
-93.60
M_3
1,995.83
mL1
3,047.82
mL3
3,552.19
mE1
3,416.43
mE3
3,927.45
mQ1
1,334.20
mQ3
2,834.07
mU1
2,502.07
mU3
2,932.73
mD1
3,682.48
mD3
2,967.13
At
3,134.34
Ab
2,708.08
Atau
-1,434.64
mu
-2,342.82
mA
2,915.04
tan(beta)
17.83
The truth!
2
M_1
275.57
M_2
810.43
M_3
213.76
mL1
1,448.44
mL3
2,457.29
mE1
3,691.35
mE3
1,376.87
mQ1
1,267.27
mQ3
2,722.50
mU1
566.68
mU3
2,855.25
mD1
3,366.87
mD3
2,457.55
At
-3,142.59
Ab
-3,981.80
Atau
3,985.09
mu
1,670.18
mA
1,932.69
tan(beta)
39.17
The truth!
3
M_1
372.49
M_2
-2,735.45
M_3
976.39
mL1
2,464.16
mL3
1,029.24
mE1
1,709.34
mE3
2,257.63
mQ1
756.67
mQ3
3,887.73
mU1
2,352.12
mU3
3,089.60
mD1
1,824.58
mD3
3,200.41
At
-4,435.46
Ab
-3,677.59
Atau
-501.59
mu
-384.46
mA
3,518.01
tan(beta)
14.78
The truth!
4
M_1
-3,910.70
M_2
318.99
M_3
461.08
mL1
1,563.88
mL3
2,079.32
mE1
1,309.68
mE3
349.09
mQ1
3,252.23
mQ3
3,894.58
mU1
1,087.96
mU3
2,583.19
mD1
961.75
mD3
898.67
At
2,816.54
Ab
-18.29
Atau
-556.39
mu
425.11
mA
3,229.24
tan(beta)
40.40
The truth!
5
M_1
1,344.51
M_2
-3,815.23
M_3
3,578.27
mL1
2,940.75
mL3
1,115.36
mE1
3,358.07
mE3
3,966.86
mQ1
3,146.52
mQ3
1,652.51
mU1
671.29
mU3
2,827.79
mD1
1,913.34
mD3
3,261.46
At
3,356.60
Ab
2,047.21
Atau
2,539.99
mu
-119.79
mA
513.32
tan(beta)
36.67
The truth!
6
M_1
3,123.06
M_2
-256.44
M_3
1,228.54
mL1
3,263.53
mL3
2,107.76
mE1
2,740.54
mE3
1,236.85
mQ1
3,589.73
mQ3
468.49
mU1
3,682.34
mU3
3,814.63
mD1
3,063.98
mD3
3,353.92
At
-3,375.83
Ab
-2,687.98
Atau
3,837.51
mu
3,782.89
mA
4,664.84
tan(beta)
26.05
The truth!
7
M_1
-1,526.13
M_2
1,070.57
M_3
1,944.18
mL1
2,767.25
mL3
1,308.09
mE1
1,839.41
mE3
1,511.93
mQ1
3,176.73
mQ3
3,467.00
mU1
3,026.18
mU3
2,804.33
mD1
3,892.87
mD3
3,702.95
At
3,379.44
Ab
1,239.31
Atau
-1,367.97
mu
-2,499.47
mA
3,140.76
tan(beta)
41.00
The truth!
8
M_1
-574.82
M_2
2,590.89
M_3
552.59
mL1
3,296.04
mL3
1,416.69
mE1
2,292.02
mE3
3,703.36
mQ1
3,738.14
mQ3
892.66
mU1
1,552.15
mU3
2,165.11
mD1
2,732.42
mD3
528.46
At
-3,107.58
Ab
-3,349.48
Atau
-1,953.79
mu
896.22
mA
3,578.28
tan(beta)
23.12
The truth!
9
M_1
-138.79
M_2
204.45
M_3
818.76
mL1
2,790.04
mL3
2,740.62
mE1
806.88
mE3
557.20
mQ1
3,682.08
mQ3
2,708.54
mU1
2,949.96
mU3
2,932.82
mD1
3,092.68
mD3
2,614.58
At
-3,785.43
Ab
-3,296.33
Atau
-831.42
mu
183.97
mA
1,143.72
tan(beta)
8.03
The truth!
10
M_1
3,038.54
M_2
-835.81
M_3
2,904.39
mL1
2,081.62
mL3
2,134.30
mE1
3,425.06
mE3
3,542.61
mQ1
3,777.31
mQ3
1,044.36
mU1
933.43
mU3
3,820.23
mD1
3,371.46
mD3
2,925.93
At
-7,118.10
Ab
3,133.52
Atau
-201.87
mu
976.71
mA
1,218.72
tan(beta)
7.03
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
