Speaker
Mr
Andrey Kupich
(BINP)
Description
The technique of discrimination of the $e^+e^-\to e^+e^-$ and
$e^+e^-\to \pi^+\pi^-$ events in energy range $0.5 < \sqrt{s} < 1$ GeV based on the difference in the energy deposition in calorimeter of SND detector was developed by applying
machine learning method. In particular the following parameters are used: $^0E_{j}$ is the
energy deposition in $j$th layer of the tower with the maximal energy
deposition, $^1E_{j}$ is the sum of energy
depositions in $j$th layer of eight towers that surround the tower with
the maximal energy deposition, $^2E_{j}$ is the sum of energy
depositions in $j$th layer of the other towers of the cluster ($j=1,2,3$).Identification efficiency for $e^+e^-\to e^+e^-$
and $e^+e^-\to \pi^+\pi^-$ events is estimated to be in the range from 99.3 to 99.8 %. Contribution of the identification efficiencies errors to the total error of $e^+e^-\to\pi^+\pi^-$ cross section is less than
0.2% for the most energy points.
Primary author
Mr
Andrey Kupich
(BINP)
