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
-3,003.62
M_2
198.68
M_3
1,329.23
mL1
2,397.59
mL3
2,988.28
mE1
2,665.31
mE3
701.98
mQ1
1,793.43
mQ3
2,173.73
mU1
1,410.07
mU3
3,806.93
mD1
2,114.63
mD3
2,255.79
At
3,312.57
Ab
-1,294.32
Atau
278.07
mu
-2,887.72
mA
2,181.91
tan(beta)
25.00
The truth!
2
M_1
553.86
M_2
3,728.93
M_3
1,294.34
mL1
1,888.45
mL3
3,204.86
mE1
1,383.10
mE3
837.02
mQ1
735.69
mQ3
2,154.20
mU1
404.31
mU3
3,245.12
mD1
1,191.78
mD3
1,749.18
At
-4,779.16
Ab
-3,894.66
Atau
-212.02
mu
4,041.48
mA
1,069.10
tan(beta)
22.15
The truth!
3
M_1
-3,182.49
M_2
-454.30
M_3
1,051.90
mL1
294.24
mL3
2,653.40
mE1
3,533.88
mE3
118.11
mQ1
718.58
mQ3
2,630.97
mU1
2,604.80
mU3
1,957.12
mD1
1,053.12
mD3
1,467.55
At
3,860.89
Ab
-1,449.07
Atau
3,329.19
mu
112.81
mA
3,774.63
tan(beta)
7.67
The truth!
4
M_1
-3,548.97
M_2
-1,042.83
M_3
2,610.99
mL1
1,369.01
mL3
1,264.01
mE1
1,685.59
mE3
1,241.01
mQ1
2,445.83
mQ3
1,686.02
mU1
2,555.39
mU3
3,899.81
mD1
3,328.03
mD3
1,245.89
At
-3,227.31
Ab
-2,797.61
Atau
1,513.59
mu
1,154.80
mA
2,566.78
tan(beta)
22.09
The truth!
5
M_1
-1,254.28
M_2
-639.50
M_3
3,953.00
mL1
761.50
mL3
2,502.33
mE1
3,647.01
mE3
846.22
mQ1
2,978.47
mQ3
2,494.17
mU1
590.15
mU3
3,792.61
mD1
3,636.84
mD3
3,384.90
At
2,960.93
Ab
-1,781.39
Atau
437.95
mu
-3,917.86
mA
3,400.95
tan(beta)
17.06
The truth!
6
M_1
-1,848.39
M_2
248.45
M_3
3,256.19
mL1
3,452.07
mL3
3,410.46
mE1
3,724.15
mE3
2,412.66
mQ1
3,258.17
mQ3
3,193.36
mU1
932.03
mU3
2,270.06
mD1
3,938.15
mD3
2,911.53
At
-2,910.88
Ab
2,178.07
Atau
-199.52
mu
-931.95
mA
3,625.84
tan(beta)
53.29
The truth!
7
M_1
620.59
M_2
-608.33
M_3
988.56
mL1
3,235.29
mL3
1,814.28
mE1
1,704.14
mE3
2,109.84
mQ1
1,577.26
mQ3
1,920.97
mU1
957.48
mU3
3,611.34
mD1
1,354.68
mD3
2,623.86
At
3,121.97
Ab
-3,189.65
Atau
-473.37
mu
1,446.52
mA
2,879.63
tan(beta)
53.05
The truth!
8
M_1
708.60
M_2
1,778.11
M_3
1,517.70
mL1
1,132.59
mL3
999.63
mE1
949.92
mE3
1,920.87
mQ1
862.97
mQ3
3,035.11
mU1
1,527.01
mU3
3,978.45
mD1
2,609.07
mD3
3,430.06
At
5,102.15
Ab
3,387.65
Atau
3,586.30
mu
-2,199.40
mA
1,297.68
tan(beta)
9.58
The truth!
9
M_1
859.24
M_2
-2,500.85
M_3
1,392.98
mL1
1,245.39
mL3
1,992.12
mE1
3,009.36
mE3
2,710.68
mQ1
688.84
mQ3
2,596.30
mU1
983.72
mU3
3,801.39
mD1
2,244.40
mD3
3,992.95
At
3,429.53
Ab
3,590.71
Atau
-3,054.90
mu
-1,741.88
mA
1,457.30
tan(beta)
13.97
The truth!
10
M_1
-611.25
M_2
-902.58
M_3
1,941.25
mL1
2,216.88
mL3
640.49
mE1
2,904.00
mE3
2,676.87
mQ1
1,210.42
mQ3
3,340.36
mU1
3,761.30
mU3
3,756.29
mD1
1,952.46
mD3
3,729.66
At
-3,073.76
Ab
-2,065.12
Atau
2,238.93
mu
612.30
mA
1,551.50
tan(beta)
35.13
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
