2026-08-12 –, Alte Mensa — Audi Max All times in Europe/Berlin
Lattice Quantum Chromodynamics (Lattice QCD) is a first-principles approach to strongly interacting gauge theories and requires large-scale high-performance computing. Production codes in this field have traditionally been written in C, C++, or Fortran.
JuliaQCD is a Lattice QCD simulation framework written entirely in Julia, developed to explore whether a high-level language can support both rapid development and large-scale HPC simulations. The framework provides distributed-memory parallelism via MPI and achieves competitive performance on modern CPUs and GPUs while keeping lattice field operations and data structures modular and expressive through multiple dispatch.
In our recent work [1], we extend JuliaQCD by introducing compiler-level reverse-mode automatic differentiation for the first time. Using LLVM-based AD, Hybrid Monte Carlo (HMC) force terms are generated directly from the action code, removing the need for separately derived and manually maintained force implementations. We validate the correctness of the automatically generated forces and examine their performance relative to conventional hand-written implementations.
This work demonstrates how Julia can support both conventional HPC-style implementations and more modern compiler-based techniques within a single, coherent framework for large-scale scientific computing.
[1] Yuki Nagai, Akio Tomiya, Hiroshi Ohno, "Lattice Gauge Theory via LLVM-Level Automatic Differentiation", arXiv:2602.20516
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