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IBM and RIKEN Named Gordon Bell Prize Finalists

IBM, RIKEN, and the Cleveland Clinic have been named Gordon Bell Prize finalists for a record-breaking quantum-classical simulation that streamlines complex molecular biology research.

IBM Research AI3 days agoResearch
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IBM, RIKEN, and the Cleveland Clinic have secured a spot as finalists for the prestigious 2026 ACM Gordon Bell Prize. The recognition honors their collaborative work in quantum-centric supercomputing, which produced the largest known quantum-enabled simulation of biologically relevant molecules to date. The research team successfully modeled a massive 12,635-atom protein system by combining quantum processors with classical high-performance computing infrastructure.

To achieve this milestone, the researchers integrated IBM Quantum Heron processors with several of the world's most powerful supercomputers. These classical systems included RIKEN's Fugaku and RUQUO supercomputers, alongside the University of Tokyo's Miyabi-G system. By distributing the computational load across these diverse architectures, the team demonstrated how hybrid quantum-classical systems can tackle scientific problems previously considered too complex for classical hardware alone.

Building on their initial success, the collaboration recently introduced a fully automated end-to-end workflow running on RIKEN's ROQUO, a new JHPC-Quantum GPU supercomputer. This automation eliminates the extensive manual coordination and frequent data transfers previously required to link quantum and classical resources across different organizations. Additionally, the team reported significantly improved accuracy in calculating protein-ligand binding energy, yielding results that closely align with expected physical behaviors in benchmark systems.

For computational chemists and biologists, these advancements represent a major shift in how molecular simulations are conducted. By automating the integration of quantum and classical resources, the new workflow reduces operational friction and accelerates the time required to reach solutions. Practitioners can now evaluate a wider array of experimental conditions, study larger proteins, and scale their research to increasingly complex molecular systems, paving the way for faster drug discovery.

This is our own summary of reporting by IBM Research AI

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