# Gluonic hadron structure and new machine-learning approaches for lattice QCD

- Institution: CERN
- Speaker: Phiala Elisabeth Shanahan
- Year: 2026
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3026445)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

I will describe recent advances in our theoretical understanding of the gluon structure of protons and glueballs from lattice QCD, highlighting the synergy with current and planned experiments. I will also describe how mathematically rigorous approaches to incorporating machine learning in algorithms for lattice field theory promise to open new frontiers in this arena.

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## Lectures

1. [Gluonic hadron structure and new machine-learning approaches for lattice QCD](https://invisiblenetwork.ai/learn/cern/3026445/7a0264ac78e3), 1 h 13 min (CERN's player)