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
1,163.97
M_2
527.60
M_3
3,853.06
mL1
1,115.06
mL3
3,379.02
mE1
2,593.99
mE3
1,839.14
mQ1
3,985.87
mQ3
2,883.42
mU1
1,329.27
mU3
2,634.85
mD1
1,386.05
mD3
801.54
At
-4,094.10
Ab
1,273.48
Atau
2,727.78
mu
977.38
mA
2,399.00
tan(beta)
27.37
The truth!
2
M_1
-2,450.03
M_2
2,875.27
M_3
1,222.64
mL1
3,652.69
mL3
2,655.79
mE1
2,965.26
mE3
1,109.89
mQ1
744.86
mQ3
691.84
mU1
1,824.33
mU3
3,301.69
mD1
1,140.89
mD3
269.05
At
2,859.91
Ab
2,347.47
Atau
3,308.46
mu
222.31
mA
1,254.35
tan(beta)
12.13
The truth!
3
M_1
3,145.09
M_2
-509.96
M_3
2,094.72
mL1
930.71
mL3
3,604.42
mE1
3,973.01
mE3
3,480.53
mQ1
3,960.80
mQ3
1,490.68
mU1
2,895.91
mU3
3,872.41
mD1
2,544.65
mD3
2,738.48
At
-3,777.83
Ab
3,174.31
Atau
-336.15
mu
-1,282.28
mA
3,661.03
tan(beta)
6.87
The truth!
4
M_1
1,556.66
M_2
-1,519.92
M_3
3,459.34
mL1
2,817.50
mL3
3,938.08
mE1
966.52
mE3
474.60
mQ1
3,510.80
mQ3
1,797.24
mU1
2,026.41
mU3
2,387.20
mD1
290.49
mD3
2,801.80
At
-2,829.00
Ab
1,075.12
Atau
-3,164.65
mu
-229.49
mA
2,278.99
tan(beta)
19.02
The truth!
5
M_1
-3,122.52
M_2
3,578.68
M_3
2,747.38
mL1
1,698.66
mL3
1,259.10
mE1
980.94
mE3
2,570.15
mQ1
840.23
mQ3
1,611.79
mU1
2,399.89
mU3
2,337.06
mD1
1,112.90
mD3
3,422.72
At
3,620.30
Ab
-90.49
Atau
-3,393.28
mu
-231.38
mA
2,765.48
tan(beta)
6.79
The truth!
6
M_1
262.21
M_2
-3,921.38
M_3
2,063.89
mL1
2,837.83
mL3
3,115.89
mE1
1,586.59
mE3
2,116.34
mQ1
471.21
mQ3
3,412.62
mU1
2,926.03
mU3
2,954.99
mD1
1,732.16
mD3
2,804.98
At
-6,047.68
Ab
1,455.32
Atau
2,159.94
mu
254.88
mA
3,305.74
tan(beta)
4.40
The truth!
7
M_1
1,782.39
M_2
242.32
M_3
527.68
mL1
3,581.72
mL3
636.14
mE1
2,001.86
mE3
3,454.08
mQ1
3,352.85
mQ3
3,422.16
mU1
3,917.09
mU3
1,796.32
mD1
2,904.91
mD3
3,995.61
At
3,080.60
Ab
3,122.21
Atau
847.69
mu
-1,483.01
mA
2,128.15
tan(beta)
27.95
The truth!
8
M_1
-3,746.36
M_2
2,956.82
M_3
660.82
mL1
3,713.86
mL3
1,748.43
mE1
778.23
mE3
2,439.69
mQ1
1,431.60
mQ3
2,281.97
mU1
2,868.52
mU3
3,899.57
mD1
3,025.33
mD3
2,912.35
At
3,694.86
Ab
-3,665.22
Atau
-911.43
mu
-276.89
mA
3,325.52
tan(beta)
11.56
The truth!
9
M_1
1,406.82
M_2
479.11
M_3
2,752.75
mL1
1,237.56
mL3
3,397.80
mE1
855.43
mE3
1,051.00
mQ1
3,298.53
mQ3
1,714.20
mU1
3,423.92
mU3
3,461.49
mD1
298.39
mD3
1,780.29
At
-4,891.53
Ab
-3,732.95
Atau
826.74
mu
-1,515.66
mA
2,327.56
tan(beta)
6.50
The truth!
10
M_1
3,998.36
M_2
3,227.07
M_3
3,482.92
mL1
3,263.25
mL3
458.61
mE1
3,566.25
mE3
3,889.77
mQ1
704.03
mQ3
3,601.64
mU1
3,547.97
mU3
1,426.06
mD1
2,804.13
mD3
2,241.84
At
-3,724.78
Ab
-287.97
Atau
-1,157.24
mu
256.11
mA
1,095.50
tan(beta)
9.42
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
