| 1 |
< |
The dominant (There are also some rare decays to kaons, but these are not |
| 2 |
< |
considered here.) hadronic decays of taus consist of a varying number of |
| 3 |
< |
charged and neutral pions. The neutral pions undergo prompt decay to photon |
| 4 |
< |
pairs. These decays proceed through intermediate resonances, given in |
| 1 |
> |
The dominant (excluding rare decays to kaons, which are not considered here.) |
| 2 |
> |
hadronic decays of taus consist of a varying number of charged and neutral |
| 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 and |
| 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 |
