A (Event generation) What information do you get....

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Normalizing sample production like W/Z for Powheg to NNLO cross sections means the total number of events reflects the higher-order accuracy of NNLO calculations. While the production occurs at lower orders (LO or NLO), the shapes of distributions are influenced by these lower orders. The scaling of events is calculated using the ratio of LO/NLO to NNLO cross sections. However, POWHEG samples do not achieve true NLO accuracy for distributions, as they incorporate NLO plus parton shower effects rather than fixed-order calculations. This distinction is crucial for understanding the reliability of event generation in particle physics simulations.
ChrisVer
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What information do you get by reading that some sample production (like the W/Z for Powheg) is normalized to the NNLO cross sections?
 
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ChrisVer said:
What information do you get by reading that some sample production (like the W/Z for Powheg) is normalized to the NNLO cross sections?

The Meaning on that statement is that the total number of events is normalized to the calculated NNLO inclusive cross section.

The production itself is done at a lower order (LO or NLO), so the shapes of all the distrubutions reflect these lower orders.

But the total normalization is accurate to NNLO.
 
So the events get scaled by something like this:
\frac{\sigma_{LO/NLO}}{\sigma_{NNLO}}?
 
ChrisVer said:
So the events get scaled by something like this:
\frac{\sigma_{LO/NLO}}{\sigma_{NNLO}}?

The total number of events are normalised by \frac{\sigma_{NNLO}}{\sigma_{LO/NLO}}
 
So practically:

\sigma_{nnlo}/\sigma_{nlo} d \sigma_{nlo} /dX

Where X is the observable. Practically though, POWHEG samples are not actually NLO accurate for distributions, since it's NLO+PS (not fixed order).
 
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