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We present MAPFF1.0, a determination of unpolarised charged-pionfragmentation functions (FFs) from a set of single-inclusive $e^+e^-$annihilation and lepton-nucleon semi-inclusive deep-inelastic-scattering(SIDIS) data. FFs are parametrised in terms of a neural network (NN) and fittedto data exploiting the knowledge of the analytic derivative of the NN itselfw.r.t. its free parameters. Uncertainties on the FFs are determined by means ofthe Monte Carlo sampling method properly accounting for all sources ofexperimental uncertainties, including that of parton distribution functions.Theoretical predictions for the relevant observables, as well as evolutioneffects, are computed to next-to-leading order (NLO) accuracy in perturbativeQCD. We exploit the flavour sensitivity of the SIDIS measurements delivered bythe HERMES and COMPASS experiments to determine a minimally-biased set of sevenindependent FF combinations. Moreover, we discuss the quality of the fit to theSIDIS data with low virtuality $Q^2$ showing that, as expected, low-$Q^2$ SIDISmeasurements are generally harder to describe within a NLO-accurateperturbative framework.

A determination of unpolarised pion fragmentation functions using semi-inclusive deep-inelastic-scattering data: MAPFF1.0