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Résumé |
What if we could make predictions for experimental measurements at the Large
Hadron Collider based entirely on first-principles theoretical calculations?
While this dream is hopelessly out of reach, we do have a growing catalog of
precision calculations in quantum chromodynamics (QCD) as a well as increasingly
accurate Monte Carlo generators. In this talk, I show how to leverage ideas
from information theory and machine learning to merge these disparate QCD
predictions into a unified theoretical prediction with associated uncertainties.
Our strategy highlights the importance of logarithmic moments, which have not
been previously studied in the QCD literature, either experimentally or
theoretically. |
