11 | | The total area \(A_0\) and the corresponding efficiency \(\epsilon(E)\) are of course only available for simulated data. For simulated data, \(A_0\) is the production area and \(\epsilon(E)\) the corresponding energy dependent efficiency of the analysis chain. |

| 11 | The total area \(A_0\) and the corresponding efficiency \(\epsilon(E)\) are of course only available for simulated data. For simulated data, \(A_0\) is the production area and \(\epsilon(E)\) the corresponding energy dependent efficiency of the analysis chain. For a given energy bin, the efficiency is then defined as |

| 12 | |

| 13 | \[\epsilon(E) = \frac{N_\textrm{exc}(E)}{N_0(E)} \] |

| 14 | |

| 15 | where \(N_0\) is the number of simulated events in this energy bin and \(N_{exc}\) the number of *excess* events that are produced by the analysis chain. |

| 16 | |

| 17 | The number of excess events, for data and simulations, is defined as |

| 18 | |

| 19 | \[N_\textrm{exc} = N_\textrm{sig} - N_\textrm{bg}\] |

| 20 | |

| 21 | where \{N_\textrm{sig}\) is the number of events identified as potential gammas from the source direction ('on-source') and \(N_\textrm{bg}\) the number of gamma-like events measured 'off-source'. Note that for Simulations, \(N_\textrm{bg}\) is not necessarily zero for wobble-mode observations as an event can survive the analysis for on- and off-events, if this is not protected by the analysis chain. |