# Optimal choice of factorization scales for the description of jet production at the LHC

## TL;DR

This paper investigates how choosing optimal factorization scales in perturbative QCD improves the precision of jet production predictions at the LHC, reducing theoretical uncertainties and enhancing the comparison with experimental data.

## Contribution

It introduces a method to determine optimal factorization scales for PDFs and fragmentation functions, improving the convergence and accuracy of pQCD calculations for jet production.

## Key findings

- Optimal scales reduce residual dependence in predictions.
- Method applicable at LO, NLO, and NNLO levels.
- Enhanced agreement between theory and LHC jet data.

## Abstract

To obtain more precise parton distribution functions (PDFs) it is important to include data on inclusive high transverse energy jet production in the global parton analyses. These data have high statistics and the NNLO terms in the perturbative QCD (pQCD) description are now available. Our aim is to reduce the uncertainty in the comparison of the jet data with pQCD. To ensure the best convergence of the pQCD series it is important to choose the appropriate factorization scales, $\mu_F$. We show that it is possible to absorb and resum in the incoming PDFs and fragmentation function ($D$) an essential part of the higher $\alpha_s$ order corrections by determining the `optimal' values of $\mu_F$. We emphasize that it is necessary to optimize different factorization scales for the various factors in the cross section: indeed, both of the PDFs, and also the fragmentation function, have their own optimal scale. We show how the values of these scales can be calculated for the LO (NLO) part of the pQCD prediction of the cross section based on the theoretically known NLO (NNLO) corrections. After these scales are fixed at their optimal values, the residual factorization scale dependence is much reduced.