Neural simulation-based inference on unbinned top-quark pair data at 13 TeV yields improved gluon PDF precision over traditional binned analyses while incorporating experimental and theoretical uncertainties.
Neural-Network Extraction of Unpolarized Transverse-Momentum-Dependent Distributions
3 Pith papers cite this work, alongside 21 external citations. Polarity classification is still indexing.
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Neural-network parametrization yields first global unpolarized TMD extraction from DY plus SIDIS data at N³LL, producing broader PDFs with smaller uncertainties than DY-only NN fits.
Collins asymmetries for pion-in-jet production at the EIC are calculated in LO and Weizsacker-Williams approximations, showing quark-channel dominance and clearer access to sea-quark transversity.
citing papers explorer
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Proton Structure from Neural Simulation-Based Inference at the LHC
Neural simulation-based inference on unbinned top-quark pair data at 13 TeV yields improved gluon PDF precision over traditional binned analyses while incorporating experimental and theoretical uncertainties.
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Neural-Network extraction of TMDs with SIDIS data
Neural-network parametrization yields first global unpolarized TMD extraction from DY plus SIDIS data at N³LL, producing broader PDFs with smaller uncertainties than DY-only NN fits.
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Collins asymmetries for pion-in-jet production in polarized $\ell p$ collisions at the EIC
Collins asymmetries for pion-in-jet production at the EIC are calculated in LO and Weizsacker-Williams approximations, showing quark-channel dominance and clearer access to sea-quark transversity.