Error propagation in Amplitude Analysis

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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: