PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 28, 2026Journal of High Energy Physics2 citationsOpen Access

Collins-type fragmentation energy correlator in semi-inclusive deep inelastic lepton-hadron scattering

QCQing-Hong CaoZYZhite YuCYC.-P. Yuan

Key Points

  • To explore fragmentation energy correlators (FECs) and their significance in parton fragmentation dynamics.
  • Defined non-perturbative fragmentation energy correlators (FECs)
  • Derived a collinear factorization formula for FECs
  • Conducted a spin decomposition analogous to transverse-momentum-dependent fragmentation functions
  • Performed next-to-leading-order calculations in semi-inclusive deep-inelastic scattering for quark non-singlet components.
  • Developed a theoretical framework for fragmentation energy correlators
  • Showed sensitivity of Collins-type quark FEC to chiral symmetry breaking
  • Validated the consistency of calculations with traditional fragmentation theories.

Abstract

A bstract We initiate a systematic study of fragmentation energy correlators (FECs), which generalize traditional fragmentation functions and encode non-perturbative information about transverse dynamics in parton fragmentation processes. We define boost-invariant, non-perturbative FECs and derive a corresponding collinear factorization formula. A spin decomposition of the FECs is carried out, analogous to that of transverse-momentum-dependent fragmentation functions. In this work we focus particularly on the Collins-type quark FEC, which is sensitive to chiral symmetry breaking and characterizes the azimuthal asymmetry in the fragmentation of a transversely polarized quark. We perform a next-to-leading-order calculation of the corresponding hard coefficient in semi-inclusive deep-inelastic scattering for the quark non-singlet component, thereby validating the consistency of our theoretical framework.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Cao et al. (2026) studied this question.

synapsesocial.com/papers/69a286490a974eb0d3c0117fhttps://doi.org/10.1007/jhep02(2026)244
Ask AI
Helpful
Bookmark
Share
View Full Paper