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While NNLO computations have been obtained for many process, using NNLO predictions in subsequent analyses remains difficult in practice. One obstacle for this is the necessity to rerun costly computations every time a change of parameters (such as scales) is desired.
I present a system that stores all the required information on events, such that it is possible to produce histograms of arbitrary observables, as well as variations of scales, PDFs and alpha_s.