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Gao, Jun

Publications and source records attributed to Gao, Jun.

High-energy neutrino deep inelastic scattering cross sections

We present a state-of-the-art prediction for cross sections of neutrino deep inelastic scattering (DIS) from nucleon at high neutrino energies, E v , up to 1000 EeV (10 12 GeV). Our calculations are based on the latest CT18 NNLO parton distribution functions (PDFs) and their associated uncertainties. To make predictions for the highest energies, we extrapolate the PDFs to small x according to several procedures and assumptions, thus affecting the uncertainties at ultrahigh E v ; we quantify the uncertainties corresponding to these choices. Similarly, we quantify the uncertainties introduced by the nuclear corrections that are required to evaluate neutrino-nuclear cross sections for the neutrino observatories. These results can be applied to currently running astrophysical neutrino observatories, such as IceCube and KM3NeT, as well as various future experiments that have been proposed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Determining SMEFT and PDF parameters simultaneously based on the CTEQ-TEA framework

The SM effective field theory (SMEFT) provides a model-independent and systematically improvable framework for new physics searches. In this talk, we outline our approach of simultaneously fitting SMEFT parameters and Probability Density Functions (PDFs) in an extension of the CT18 global analysis framework. To enhance the efficiency of our global fitting and Lagrange multiplier scans, we leverage machine-learning techniques. We focus on several representative operators relevant to top-quark pair production and jet production. Through this approach, we establish self-consistent limitations on the associated Wilson coefficients, and explore the correlations between these Wilson coefficients and the PDFs.

Shen, XiaoMin↗