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
-620.55
M_2
1,016.48
M_3
568.83
mL1
3,302.13
mL3
3,650.16
mE1
1,987.74
mE3
2,546.30
mQ1
3,849.70
mQ3
3,100.09
mU1
3,716.49
mU3
3,920.49
mD1
3,092.28
mD3
3,319.05
At
-1,727.82
Ab
2,664.96
Atau
-3,199.95
mu
-637.64
mA
605.91
tan(beta)
53.19
The truth!
2
M_1
732.48
M_2
758.27
M_3
1,796.61
mL1
2,672.21
mL3
3,926.23
mE1
2,084.60
mE3
3,793.81
mQ1
949.64
mQ3
1,642.15
mU1
2,389.47
mU3
762.43
mD1
958.50
mD3
1,811.05
At
-3,004.42
Ab
-1,730.03
Atau
1,118.16
mu
1,841.62
mA
2,478.74
tan(beta)
34.35
The truth!
3
M_1
847.13
M_2
2,440.64
M_3
1,704.05
mL1
3,499.45
mL3
3,008.15
mE1
1,400.54
mE3
1,321.62
mQ1
3,498.62
mQ3
3,147.64
mU1
1,731.39
mU3
3,970.24
mD1
652.13
mD3
1,907.42
At
-5,096.84
Ab
19.66
Atau
-878.54
mu
2,403.08
mA
2,501.88
tan(beta)
20.19
The truth!
4
M_1
-3,028.88
M_2
-313.94
M_3
2,239.41
mL1
2,557.54
mL3
1,932.98
mE1
2,857.47
mE3
403.44
mQ1
2,822.05
mQ3
1,475.65
mU1
3,635.51
mU3
3,081.26
mD1
1,774.99
mD3
2,615.11
At
3,098.93
Ab
-2,092.99
Atau
3,687.93
mu
3,154.29
mA
3,385.83
tan(beta)
18.76
The truth!
5
M_1
311.07
M_2
-1,697.60
M_3
262.76
mL1
2,757.23
mL3
658.86
mE1
3,021.67
mE3
2,260.32
mQ1
3,140.40
mQ3
903.55
mU1
3,771.31
mU3
3,406.99
mD1
2,291.59
mD3
2,104.39
At
-2,981.92
Ab
2,062.32
Atau
3,552.09
mu
3,108.82
mA
2,835.88
tan(beta)
44.16
The truth!
6
M_1
45.91
M_2
1,973.38
M_3
2,084.36
mL1
2,843.58
mL3
2,176.44
mE1
3,065.61
mE3
3,732.35
mQ1
3,855.31
mQ3
3,329.47
mU1
2,754.39
mU3
3,981.47
mD1
1,803.19
mD3
491.79
At
2,676.40
Ab
-1,950.29
Atau
-1,932.63
mu
157.59
mA
1,955.78
tan(beta)
13.58
The truth!
7
M_1
3,063.78
M_2
220.42
M_3
3,592.13
mL1
2,691.21
mL3
653.38
mE1
837.49
mE3
1,626.63
mQ1
3,058.29
mQ3
1,600.40
mU1
3,759.96
mU3
3,302.18
mD1
421.77
mD3
3,003.29
At
-5,736.00
Ab
620.34
Atau
-737.95
mu
3,963.01
mA
1,201.14
tan(beta)
8.98
The truth!
8
M_1
-281.28
M_2
-669.45
M_3
1,128.54
mL1
2,871.34
mL3
510.61
mE1
2,554.50
mE3
456.81
mQ1
1,961.78
mQ3
836.30
mU1
2,080.79
mU3
2,301.13
mD1
2,011.72
mD3
3,595.31
At
-2,489.49
Ab
-853.53
Atau
843.94
mu
4,001.70
mA
1,750.57
tan(beta)
17.36
The truth!
9
M_1
1,236.08
M_2
319.25
M_3
2,927.47
mL1
2,474.84
mL3
1,946.24
mE1
2,119.93
mE3
376.41
mQ1
302.50
mQ3
2,681.35
mU1
473.52
mU3
3,584.20
mD1
3,641.92
mD3
391.36
At
-4,374.58
Ab
-2,157.68
Atau
2,095.47
mu
3,238.54
mA
1,773.29
tan(beta)
29.96
The truth!
10
M_1
-1,453.49
M_2
3,630.46
M_3
3,190.09
mL1
1,968.32
mL3
3,769.49
mE1
1,199.64
mE3
3,632.77
mQ1
1,628.26
mQ3
3,633.90
mU1
938.50
mU3
3,899.36
mD1
388.85
mD3
3,085.48
At
4,161.09
Ab
1,045.93
Atau
3,199.49
mu
707.60
mA
3,357.62
tan(beta)
13.67
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
