# Constraints on nuclear parton distributions from dijet photoproduction at the LHC

## TL;DR

This study demonstrates that dijet photoproduction data from LHC ultraperipheral collisions can significantly reduce uncertainties in nuclear parton distribution functions, especially at small momentum fractions, using Bayesian reweighting techniques.

## Contribution

It introduces a method to incorporate LHC dijet photoproduction pseudo-data into nPDFs, showing substantial uncertainty reduction at small x values.

## Key findings

- Uncertainty in nCTEQ15 nPDFs reduces by about 50% at x=10^{-3} with 5% pseudo-data error.
- Reweighting has a smaller impact on EPPS16 nPDFs due to different parametrization.
- Pseudo-data can constrain nPDFs effectively at small momentum fractions.

## Abstract

Using QCD calculations of the cross section of inclusive dijet photoproduction in Pb-Pb ultraperipheral collisions in the LHC kinematics as pseudo-data, we study the effect of including these data using the Bayesian reweighting technique on nCTEQ15, nCTEQ15np, and EPPS16 nuclear parton distribution functions (nPDFs). We find that, depending on the assumed error of the pseudo-data, it leads to a significant reduction of the nPDF uncertainties at small values of the momentum fraction $x_A$. Taking the error to be 5\%, the uncertainty of nCTEQ15 and nCTEQ15np nPDFs reduces approximately by a factor of two at $x_A=10^{-3}$. At the same time, the reweighting effect on EPPS16 nPDFs is much smaller due to the higher value of the tolerance and a more flexible parametrization form.