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Drell-Yan cross-sections with fiducial cuts: impact of linear power corrections and $q_T$-resummation in PDF determination

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arxiv 2209.13535 v1 pith:4K4QIHPZ submitted 2022-09-27 hep-ph

classification hep-ph
keywords correctionsdistributionfiduciallinearpowerpredictionsdescriptiondetermination
verification ladder T0 review T1 audit T2 compute T3 formal

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abstract

Measurement at Hadron colliders of neutral- and charged-current Drell-Yan production provide essential constraints in the determination of parton distribution functions. Experimentally, they have reached percent level precision, challenging the accuracy of the theoretical predictions. In this work we benchmark the novel implementation in $\texttt{DYTurbo}$ of linear fiducial power corrections in the $q_T$-subtraction formalism at NLO and NNLO in QCD. We illustrate how the inclusion of linear fiducial power corrections impacts predictions for precise $W$ and $Z$ measurements from the LHC and affects their description by modern global parton distribution functions. The further inclusion of $q_T$-resummation corrections in the theoretical predictions leads to a better modelling of the lepton $p_T$ distribution and we study how this improve the description of the data.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Drell-Yan Transverse-Momentum Spectra at N$^3$LL$'$ and Approximate N$^4$LL with SCETlib

    hep-ph 2024-11 conditional novelty 7.0 of 10

    State-of-the-art LHC predictions for W/Z transverse momentum spectra at N3LL' and approximate N4LL accuracy, with a rigorous reduction of nonperturbative TMD physics to one effective function per process.

  2. MATRIX HAWAII: PineAPPL interpolation grids with MATRIX

    hep-ph 2025-06 accept novelty 6.0 of 10

    Matrix Hawaii provides a public interface between PineAPPL and MATRIX that generates interpolation grids at NNLO QCD + NLO EW accuracy for a range of LHC processes, with sub-permille interpolation errors.

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