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
2,254.27
M_2
-872.32
M_3
3,943.57
mL1
1,232.46
mL3
3,514.07
mE1
1,510.21
mE3
861.83
mQ1
3,432.09
mQ3
3,106.56
mU1
3,940.46
mU3
3,597.56
mD1
2,764.35
mD3
2,853.56
At
4,530.00
Ab
-2,307.04
Atau
-1,872.72
mu
335.96
mA
2,275.51
tan(beta)
12.89
The truth!
2
M_1
-3,614.02
M_2
-2,712.94
M_3
3,908.43
mL1
3,270.84
mL3
2,266.63
mE1
1,011.75
mE3
1,019.96
mQ1
1,629.85
mQ3
3,558.16
mU1
3,152.57
mU3
1,341.92
mD1
2,939.55
mD3
3,699.36
At
-4,215.55
Ab
-2,342.92
Atau
-2,247.09
mu
193.26
mA
3,055.17
tan(beta)
49.56
The truth!
3
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!
4
M_1
-1,785.11
M_2
950.24
M_3
834.69
mL1
3,261.94
mL3
1,741.09
mE1
1,842.61
mE3
1,020.77
mQ1
211.73
mQ3
1,347.75
mU1
656.39
mU3
1,194.04
mD1
3,832.55
mD3
923.08
At
-2,514.02
Ab
-1,336.92
Atau
-1,691.60
mu
-200.91
mA
995.61
tan(beta)
8.66
The truth!
5
M_1
1,518.53
M_2
-2,880.53
M_3
3,616.77
mL1
796.43
mL3
1,732.61
mE1
3,079.72
mE3
1,042.94
mQ1
3,192.40
mQ3
3,897.99
mU1
2,058.41
mU3
1,869.50
mD1
2,979.87
mD3
3,018.18
At
4,119.91
Ab
2,368.57
Atau
-65.99
mu
418.73
mA
2,720.49
tan(beta)
37.96
The truth!
6
M_1
-1,262.19
M_2
-3,064.49
M_3
647.31
mL1
207.16
mL3
2,590.81
mE1
706.11
mE3
3,564.93
mQ1
1,453.91
mQ3
3,758.29
mU1
3,840.44
mU3
3,326.33
mD1
1,904.24
mD3
1,615.73
At
4,516.67
Ab
-2,725.89
Atau
945.87
mu
-342.38
mA
3,442.65
tan(beta)
14.85
The truth!
7
M_1
669.34
M_2
-2,294.23
M_3
3,225.45
mL1
709.04
mL3
3,294.01
mE1
2,456.31
mE3
2,945.69
mQ1
701.15
mQ3
3,039.70
mU1
1,717.45
mU3
3,170.81
mD1
321.37
mD3
3,651.97
At
-4,384.57
Ab
-2,274.12
Atau
2,912.91
mu
1,539.20
mA
3,810.88
tan(beta)
47.20
The truth!
8
M_1
498.99
M_2
872.89
M_3
1,691.15
mL1
2,052.85
mL3
787.10
mE1
2,905.38
mE3
2,402.03
mQ1
1,370.91
mQ3
1,056.24
mU1
335.67
mU3
3,619.18
mD1
953.39
mD3
3,559.62
At
3,394.48
Ab
413.85
Atau
-2,398.76
mu
-1,926.01
mA
2,193.44
tan(beta)
33.46
The truth!
9
M_1
-1,060.66
M_2
-2,831.47
M_3
3,062.10
mL1
1,453.25
mL3
3,022.51
mE1
1,841.56
mE3
1,280.47
mQ1
1,922.48
mQ3
2,551.69
mU1
3,413.90
mU3
3,620.31
mD1
860.39
mD3
3,897.88
At
-3,910.11
Ab
-2,900.73
Atau
160.16
mu
2,838.92
mA
3,861.18
tan(beta)
6.41
The truth!
10
M_1
3,258.30
M_2
-3,571.23
M_3
3,878.89
mL1
1,526.53
mL3
2,214.05
mE1
3,249.33
mE3
2,009.55
mQ1
206.57
mQ3
3,455.08
mU1
3,048.61
mU3
2,541.51
mD1
1,885.01
mD3
1,905.69
At
4,015.29
Ab
3,941.28
Atau
-1,132.68
mu
-428.63
mA
3,215.17
tan(beta)
13.27
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
