  New hard-scattering measurements from the LHC proton-lead run have the
potential to provide important constraints on the nuclear parton distributions
and thus contributing to a better understanding of the initial state in heavy
ion collisions. In order to quantify these constraints, as well as to assess
the compatibility with available nuclear data from fixed target experiments and
from RHIC, the traditional strategy is to perform a global fit of nuclear PDFs.
This procedure is however time consuming and technically challenging, and
moreover can only be performed by the PDF fitters themselves. In the case of
proton PDFs, an alternative approach has been suggested that uses Bayesian
inference to propagate the effects of new data into the PDFs without the need
of refitting. In this work, we apply this reweighting procedure to study the
impact on nuclear PDFs of low-mass Drell-Yan and single-inclusive
hadroproduction pseudo-data from proton-lead collisions at the LHC as
representative examples. In the hadroproduction case, in addition we assess the
possibility of discriminating between the DGLAP and CGC production frameworks.
We find that the LHC proton-lead data could lead to a substantial reduction of
the uncertainties on nuclear PDFs, in particular for the small-x gluon PDF
where uncertainties could decrease by up to a factor two. The Monte Carlo
replicas of EPS09 used in the analysis are released as a public code for
general use. It can be directly used, in particular, by the experimental
collaborations to check, in a straightforward manner, the degree of
compatibility of the new data with the global nPDF analyses.
