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Probing Neutral Triple Gauge Couplings via $ZZ$ Production at $e^+e^-$ Colliders with Machine Learning

High Energy Physics - Phenomenology 2026-04-10 v3 High Energy Physics - Experiment

Abstract

Neutral triple gauge couplings (nTGCs) first arise from the dimension-8 operators of the Standard Model Effective Field Theory (SMEFT), rather than the dimension-4 SM Lagrangian and dimension-6 SMEFT operators, opening up a unique window for probing new physics at the dimension-8 level. In this work, we formulate the nTGC form factors of ZZVZZV^* (V ⁣ ⁣= ⁣Z,γV\!\!=\!Z,\gamma) that are compatible with the spontaneous breaking of the SU(2)\otimesU(1) electroweak gauge symmetry and consistently match the dimension-8 nTGC operators in the broken phase. We study the sensitivities for probing both the ZZVZZV^* form factors and the corresponding new physics scales through ZZZZ production (with visible/invisible fermionic ZZ decays) at high energy e+ee^+e^- colliders including CEPC, FCC-ee, ILC and CLIC. In particular, we identify the dimension-8 operator that contributes to the pure triple ZZ boson coupling ZZZZZZ^* alone, but not the mixed ZZγZZ\gamma^* coupling. We further study the correlations between probes of the ZZZZZZ^* and ZZγZZ\gamma^* couplings. Using machine learning, we show that angular distributions of the final-state fermions can play key roles in suppressing the SM backgrounds. The sensitivities can be further improved by using polarized ee^\mp beams. We demonstrate that machine learning is advantageous for handling the 4-body final states from ZZZZ decays and improves significantly the sensitivity reaches of probes of nTGCs in e+ee^+e^- collisions. We find that nTGC new physics scales can be probed up to the multi-TeV scale at the proposed e+ee^+e^- colliders.

Keywords

Cite

@article{arxiv.2506.21433,
  title  = {Probing Neutral Triple Gauge Couplings via $ZZ$ Production at $e^+e^-$ Colliders with Machine Learning},
  author = {John Ellis and Hong-Jian He and Rui-Qing Xiao and Shi-Ping Zeng},
  journal= {arXiv preprint arXiv:2506.21433},
  year   = {2026}
}

Comments

PRD published version. 40 pages (including 27 Figs + Tables)