Computational Physics Minisymposium
The Computational Physics Minisymposium highlights numerical methods, algorithms, and software implementations—including testing and benchmarking—for modeling and simulation across a broad range of theoretical and computational physics subfields. It serves as a “trading port” for computational methods that connect diverse areas of physics. This year’s minisymposium will feature a special session spotlighting the JuliaQCD and JuliaFewBody ecosystems.
For electronic-structure calculations and molecular dynamics simulations in computational chemistry and materials science, submissions may also be a good fit for the JuliaMolSim Minisymposium, which will be held at a different time slot.
We presented on hadron physics at JuliaCon 2025, but there was no suitable minisymposium. In Japan, computational physics is the field with the largest Julia population, and there is a need for a minisymposium on the topic of computational physics. We expect to see participants from the field of computational physics.
I received my PhD in Physics from New Zealand Institute for Advanced Study in 2022. During my PhD, I worked with Prof. Joachim Brand developing quantum Monte Carlo algorithms for ultracold Bose gases. Later, I joined the Chemistry Department at Washington University in St. Louis as a postdoc, working with Prof. Robert Wexler on nested sampling.
My extensive interdisciplinary research experience spans chemistry and physics, with published works on molecular magnetism, metallic clusters and surfaces, as well as ultracold quantum gases. My research interests focus on developing efficient and accurate computational methods for solving complicated quantum and statistical mechanical problems. My main tools are (quantum and classical) Monte Carlo techniques.
I am an enthusiastic Julia programmer, I use the programming language to develop several open-source computational physics packages including Rimu.jl and FreeBird.jl. I am the Finance Chair of JuliaCon Global 2026. I am also building a Julia based materials science startup, Ainest, in Tallinn, Estonia.
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
PhD student at Yokohama City University and co-founder of JuliaFewBody
PhD student at the University of Copenhagen working on tensor networks
I received my Doctor of Science degree in Physics from The University of Tokyo in 2010. After graduation, I joined the Center for Computational Science and e-Systems (CCSE) at the Japan Atomic Energy Agency (JAEA) as a Senior Scientist, where I worked from 2010 to 2024. During this period, I was also a Visiting Scholar in the Department of Physics at the Massachusetts Institute of Technology (MIT) from 2016 to 2017 and a Visiting Researcher at the RIKEN Center for Advanced Intelligence Project (RIKEN AIP) from 2018 to 2023. Since 2024, I have been an Associate Professor at the Information Technology Center, The University of Tokyo.
My research focuses on developing novel computational methods by combining machine learning, statistical physics, and high-performance computing. I am particularly interested in quantum many-body physics, superconductivity, first-principles molecular dynamics, and lattice gauge theory. I also develop open-source software in Julia for large-scale scientific computing on modern supercomputers.
I am a developer of JuliaQCD project, FluxKAN.jl, TightBinding.jl and QuadraticHamiltonians.jl