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Unification of the $k_T$ and threshold resummations

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arxiv hep-ph/9812363 v1 pith:AJWB77KF submitted 1998-12-15 hep-ph

Hsiang-nan Li This is my paper · ORCID
classification hep-ph
keywords resummationthresholdexhibitspartonsimilartransversecollins-soperconjugate
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abstract

We derive a resummation formula for a $k_T$-dependent parton distribution function at threshold, where $k_T$ is a parton transverse momentum. The derivation requires infrared cutoffs for both longitudinal and transverse loop momenta as evaluating soft gluon emissions in the Collins-Soper resummation framework. This unified resummation exhibits suppression at large $b$, $b$ being the conjugate variable of $k_T$, which is similar to the $k_T$ resummation, and exhibits enhancement at small $b$, similar to the threshold resummation.

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Cited by 4 Pith papers

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

  1. A Toolbox for $q_T$ and $0$-Jettiness Subtractions at N$^3$LO

    hep-ph 2019-09 conditional novelty 8.0 of 10

    The paper provides the complete three-loop singular subtraction terms for qT and 0-jettiness and derives the first threshold predictions for the three-loop beam-function coefficients, later confirmed by direct calculation.

  2. Slepton pair production at next-to-leading power

    hep-ph 2025-10 unverdicted novelty 6.0 of 10

    Evaluates next-to-leading power threshold corrections for slepton pair production and finds them significant compared to leading power NLL terms, with underestimated scale errors for large masses.

  3. How much joint resummation do we need?

    hep-ph 2019-08 conditional novelty 6.0 of 10

    Joint resummation of two angularities, rather than one or many, yields the largest gain in predicting other angularities in e+ e- dijet events.

  4. Twist-3 contributions to $\gamma\gamma\to\pi^0\pi^0,\,K_S^0K_S^0$ in $k_T$ factorization

    hep-ph 2026-06 unverdicted novelty 4.0 of 10

    Twist-3 LCDA contributions in k_T factorization dominate twist-2 for neutral channels, bringing predictions closer to data while neutral-to-charged ratios remain flat unlike observations.

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