3 papers
hep-ph2026
SMEFT-Pheno-Agent: a natural-language-driven AI agent for machine-learning-assisted Standard Model Effective Field Theory phenomenology
Yu-Chen Guo, Jie Wang, Ji-Chong Yang
We present SMEFT-Pheno-Agent, a Python workflow guided by a natural-language AI agent to perform machine-learning-assisted Standard Model Effective Field Theory (SMEFT) phenomenolo…
hep-ph2025
Enhancing Phase Transition Calculations with Fitting and Neural Network
Ligong Bian, Hongxin Wang, Yang Xiao +3
The computation of bounce action in a phase transition involves solving partial differential equations, inherently introducing non-negligible numerical uncertainty. Deriving charac…
hep-ph2024
Search for Neutral Triple Gauge Couplings with Production at Future Electron Positron Colliders
Yu-Chen Guo, Chun-Jing Pan, Man-Qi Ruan +1
This study investigates Neutral Triple Gauge Couplings (nTGCs) through production at future electron-positron colliders. The impact of beam polarization on cross section is an…