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PreprintCC BY 4.0arXiv

Drell-Yan lepton pair production from low to high transverse momentum

Abstract

We present a technique for computing Drell-Yan lepton pair production at particle-level that achieves N3LO and approximate N4LL' accuracy at small to moderate transverse momentum, tree-level precision for Z+4, $5$, and $6$ jets, and approximate NLO EW precision at high transverse momentum. A crucial non-perturbative input, the Collins-Soper kernel, is obtained from continuum-limit lattice QCD results. High-precision theory results are recast into strictly positive event weights using an information-theoretic approach based on the maximum entropy principle.

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BibTeX
@misc{assi2026drellyan,
  title = {{Drell-Yan lepton pair production from low to high transverse momentum}},
  author = {Benoît Assi and Enrico Bothmann and John Campbell and Christian Gütschow and Stefan Höche and Wan-Li Ju and Max Knobbe and Marek Schönherr and Jesse Thaler and Michael L. Wagman},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.02169},
  eprint = {2610.02169},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.02169},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Drell-Yan lepton pair production from low to high transverse momentum
AU  - Benoît Assi
AU  - Enrico Bothmann
AU  - John Campbell
AU  - Christian Gütschow
AU  - Stefan Höche
AU  - Wan-Li Ju
AU  - Max Knobbe
AU  - Marek Schönherr
AU  - Jesse Thaler
AU  - Michael L. Wagman
PY  - 2026
DA  - 2026/10/01
PB  - arXiv
DO  - 10.48550/arxiv.2610.02169
UR  - https://arxiv.org/abs/2610.02169
AB  - We present a technique for computing Drell-Yan lepton pair production at particle-level that achieves N^3LO and approximate N^4LL' accuracy at small to moderate transverse momentum, tree-level precision for Z+4, $5$, and $6$ jets, and approximate NLO EW precision at high transverse momentum. A crucial non-perturbative input, the Collins-Soper kernel, is obtained from continuum-limit lattice QCD results. High-precision theory results are recast into strictly positive event weights using an information-theoretic approach based on the maximum entropy principle.
ER  -