| 1 |
The dominant (excluding rare decays to kaons, which are not considered here.)
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| 2 |
hadronic decays of taus consist of a varying number of charged and neutral
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| 3 |
pions. The neutral pions undergo prompt decay to photon pairs. These decays
|
| 4 |
proceed through intermediate resonances, given in
|
| 5 |
table~\ref{table:decay_modes}. Each of these decay modes uniquely maps to a
|
| 6 |
tau final state multiplicity, and each resonance has a different invariant
|
| 7 |
mass. This implies that the problem of hadronic tau identification can be
|
| 8 |
reframed from a global search for collimated hadrons under the tau mass into an
|
| 9 |
ensemble of searches for single production of the various decay resonances
|
| 10 |
given in table~\ref{table:decay_modes}. In this paper, we present a novel
|
| 11 |
algorithm, the ``Tau Neural Classifier'' (TaNC) which uses this approach to
|
| 12 |
improve on traditional tau-ID strategies.
|
| 13 |
|
| 14 |
\begin{table}
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| 15 |
\caption{Visible products of hadronic tau decays}
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| 16 |
\centering
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| 17 |
\begin{tabular}{ l c r r }
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| 18 |
Visible Decay Products & Resonance & Mass (M$e$V/$c^2$) & Fraction \\
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| 19 |
\hline
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| 20 |
$\pi^{-}$ & n/a & 135 & fixme \\
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| 21 |
$\pi^{-}\pi^0$ & $\rho$ & 770 & fixme \\
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| 22 |
$\pi^{-}\pi^0\pi^0$ & $a1$ & 1200 & fixme \\
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| 23 |
$\pi^{-}\pi^{-}\pi^{+}$ & $a1$ & 1200 & fixme \\
|
| 24 |
$\pi^{-}\pi^{-}\pi^{+}\pi^0$ & $a1$ & 1200 & fixme \\
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| 25 |
\hline
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| 26 |
Total & & & 65\% \\
|
| 27 |
\end{tabular}
|
| 28 |
\label{table:decay_modes}
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| 29 |
\end{table}
|
| 30 |
|
