Searching for Rare Events
Axceleon would like to thank Dr. Igor Mandic from Institute Jozef Stefan for sharing his use of EnFuzion in high energy physics.
What is the high energy physics data analysis problem?
For separation of event categories, the researchers use vertex fit probability, probabilities of two different constraint fits, and particle identification. The particle identification provides the possibility of choosing the purity of identification. Higher purity means lower efficiency. Similarly, the distributions of vertex and constraint fit probabilities are different for signal and background events. The researchers can also vary the values of the probabilities that are required for accepting an event, which changes the signal and background efficiencies.
The problem in this kind of analysis is to choose the actual values at which one cuts because the separation quantities are correlated. In this case, the researchers wanted to maximize the statistical significance of a potential signal. This significance is described by the ratio and are signal and background efficiencies, respectively.
How did EnFuzion help solve the problem?
How was EnFuzion used?
Preparing input parameters
A program that calculated S for five values of particle identification purity needs about two minutes of real time on an HP735 computer. In this case, vertex fit probability and two constraint fit probabilities were input parameters.
The values of cuts that they tested are
prob1 less than 1, 2, 5 and 10 percent
Performing the computation
This plan file generated the following user interface for job execution, which was used to select input parameters:
To calculate all possible combinations of input parameters, 304 jobs were generated. On average, each job required around 2.5 minutes on a single HP machine. The total elapsed time for the execution of 304 jobs, using seven HP machines was less than two hours. Here is a detailed report from EnFuzion:
Fri Feb 28 19:08:31 1997: ===== Run Finished =====
In the figure, the researchers show S as a function of prob3 and particle identification cut (for values of prob1 = 10 and prob2 = 15). One can observe the maximum of S. The position of the peak at the edge of the plot suggests that the particle identification cut should be extended to confirm that this is the true maximum.
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