The following is a review of error propagation needed in amplitude analysis.
Consider a Monte-Carlo (MC) integral over the intensities of N detected events out of Ngen generated.
where we take n coherent amplitudes and allow incoherent sums indexed by
γ, δ to allow for applications like spin-density matrices (ρ).
When amplitude analysis fits contain amplitudes with not free parameters, it is convenient to
rearrange the summations above, to pre-compute the sum over the intensities of the events:
storing the term in square brackets, a matrix indexed by α,β, for contractions with varying free production parameters u in the course of a fit.
When considering the uncertainty on the overall integral, both the errors on u parameters
and those from the finite MC set of events will contribute. A single detected event (i) can be viewed as one sample of a Poisson process, having therefore an uncertainty of
σi=1. An integral over such events is then a weighted sum of such samples,
having therefore a contribution to the variance:
