ºÚÁÏÍø

Quantum-HPC Simulation at Scale: Hybrid Algorithms from Gauge Theories to Quantum Chemistry and Beyond 

Kazuki Ikeda 
University of Massachusetts Boston

Abstract: Quantum computing is likely to have its strongest early impact as part of a quantum HPC workflow, where QPUs work together with CPUs and GPUs to tackle many-body problems beyond the reach of classical simulation alone. In this talk, I present a research program centered on quantum-HPC simulation, with two main components: the development of core hybrid algorithms for excited states, real-time dynamics, and response functions, and their application to first-principles problems in gauge theories, curved-spacetime and cosmological quantum field theory, quantum materials, and quantum chemistry. I will highlight recent results from my work on hybrid variational methods and GPU-accelerated workflows for quantum simulations. I will then outline a vision for Aalto in which quantum-HPC simulation becomes both a scientific engine and a systems benchmark: demanding simulation workloads can drive advances in resource estimation, runtime orchestration, and, over the longer term, compiler and software-stack design for portable and reproducible hybrid computing across heterogeneous platforms. 

Bio: Kazuki Ikeda is a faculty member at the University of Massachusetts Boston whose research centers on quantum simulation: hybrid quantum-classical algorithms and workflows that combine quantum processors with CPUs and GPUs to study many-body systems beyond the reach of conventional methods. His work advances core algorithmic tools for excited states, real-time dynamics, constrained variational methods, and response functions, and applies them to first-principles problems in gauge theories, quantum field theory in curved spacetime and cosmology, quantum materials, and quantum chemistry. He leads collaborations spanning academia, national laboratories, and industry. Looking ahead, he is also interested in the compiler and software-stack advances that will make quantum-HPC simulation scalable, portable, and reproducible across heterogeneous platforms.