diff --git a/docs/livetime.rst b/docs/livetime.rst index 44ecaea..889a251 100644 --- a/docs/livetime.rst +++ b/docs/livetime.rst @@ -12,6 +12,20 @@ the sum of the weights. L_{eff} = \frac{\sum{w_i}}{\sum{w_i^2}} +The effective livetime is defined as the time the detector would need to take data to have a sample +with the same average, relative uncertainty as the MC set [#]_. +The uncertainty of an unweighted sample with :math:`N=RL` events is :math:`\sqrt{N}`, +which assumes a Poisson distribution +of the event number. :math:`R` is the event rate and :math:`L` the livetime. +The uncertainty of the event rate :math:`R=\sum_i w_i` from a weighted MC set is +:math:`\Delta R = \sqrt{\sum_i w_i^2}` [#]_. +Thus we can easily derive the above definition from + +.. math:: + \frac{\sqrt{N}}{N} = \frac{\sqrt{RL}}{RL} \overset{!}{=} \frac{\Delta R}{R} + +Rearranging the last equality results in the above expression for the effective livetime. + As shown in the example below it can be calculated for any sample or for any subsample by using histograms. @@ -20,3 +34,7 @@ As shown in the example below it can be calculated for any sample or for any sub .. figure:: livetime_rate.svg .. figure:: livetime_livetime.svg + + +.. [#] See `this `_ report by Michelangelo D’Agostino (requires password access). +.. [#] This can be derived from the fundamental properties of the variance: :math:`\sigma^2(cx)=c^2\sigma^2(x)` and :math:`\sigma^2(x_1+x_2)=\sigma^2(x_1)+\sigma^2(x_2)`, see e.g. `here `_.