[Halld-cpp] DNP Abstract

[David Lawrence]

Hi All,

  As I mentioned at last week’s meeting, I’ve been invited to give a talk at the 
DNP meeting in Pittsburg on how we’ve used Machine Learning in the 
development of the !muon detector. Below is a draft of the abstract I plan
to submit. Comments are welcomed. 

Regards,
-David


The Charged Pion Polarizability(CPP) experiment is approved 
to run in Hall-D at Jefferson Lab using the GlueX detector. 
CPP requires that $\pi^{+{}} \pi^{-{}}$ production events be 
distinguished from $\mu^{+{}}\mu^{-{}}$ to better than 99\% accuracy. 
This drives the design of a new MWPC-based detector capable of 
separating the $\pi$ events from the $\mu$ events. A multivariate
analysis of simulated data was initially done to study the
feasibility of a detector with this level of performance. More
recently, the design parameters of the detector have been
refined using a similar technique. Details on the initial study
and how machine learning has contributed to the detector design
will be presented.
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