2026-08-12 –, Room 5
Inside atomic nuclei, "empty space" is not empty: the strong force comes from a gluon field that fluctuates and binds quarks into protons and neutrons. Lattice QCD computes this by simulating QCD on a grid in space and time, usually on supercomputers. VisualizingQCD.jl, a JuliaQCD package, turns your own configuration files into 3D movies of local observables, so Julia users can see, debug, and share the quantum vacuum.
Quantum chromodynamics (QCD) is the theory of the strong force that holds atomic nuclei together. It predicts that the "vacuum" is a fluctuating gluon field, so even empty space has structure, and those fluctuations shape protons and neutrons. Lattice QCD makes this computable by simulating QCD on a 4D grid and generating many snapshots of the gluon field, typically on supercomputers. Because the output is a large 4D dataset, visualization is a practical way to build intuition, compare runs, and explain results.
Previous QCD outreach movies showed how compelling vacuum visualization can be, but they are fixed examples. When you develop algorithms or tune parameters, you want to visualize your own configurations from your own simulations. VisualizingQCD.jl, part of the JuliaQCD project, provides an open-source pipeline that reads ILDG configuration files, computes a 3D scalar field on each time slice, and renders iso-surfaces into MP4 videos with Makie. The workflow is plain Julia code, so it is reproducible and easy to extend.
In this short talk I will demo the pipeline end to end, starting from an ILDG file and producing a movie in a few lines. Next I will explain what can be visualized, focusing on local observables such as plaquette-based activity (the smallest loop on the grid), action density after gradient flow (a standard smoothing procedure), a common probe of vacuum structure. I will close with performance notes and pointers for adding new observables within the JuliaQCD ecosystem.
I am an associate professor in Tokyo Woman’s Christian University and Kyoto University, visiting researcher of RIKEN using Julia for lattice QCD with machine learning.
My CV: https://www2.yukawa.kyoto-u.ac.jp/~akio.tomiya/index_en.html