High Performance Computing, Quantum Software

RIKEN will use QunaSys software to link supercomputer with quantum chips

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September 5, 2026 by Ivy Delaney

RIKEN will integrate QunaSys’s QURI SDK Enterprise into its project, linking the supercomputer Fugaku with both the IBM Quantum System Two “ibm_kobe” and the Quantinuum System Model H2 “Reimei.” This creates a hybrid platform allowing users to access quantum devices directly from Fugaku’s compute nodes, rather than operating them in isolation. The QURI SDK Enterprise includes libraries like QSCI and ADAPT-QSCI, targeting applications in quantum chemistry, materials science, and CAE, with the goal of enabling future practical uses. QunaSys states that comprehensive documentation, sample code, and toolchains allow researchers to begin development quickly.

QURI SDK Enterprise Integrates Fugaku, IBM Quantum, and Reimei

The JHPC-quantum project now allows users to directly access quantum hardware from Fugaku’s computing resources through QunaSys’s QURI SDK Enterprise, integrating quantum processing units with a leading supercomputer. Researchers can now build computational workflows that use the unique characteristics of each quantum device, bypassing the traditional isolation of quantum computations. Parallel computation across multiple nodes and processors is enabled through mpiQulacs on Fugaku’s compute nodes and a cuQuantum-based backend on the JHPC-quantum GPU supercomputer “ROQUO”, extending the scale of simulated quantum circuits beyond single-node limitations.

This integration extends beyond Fugaku, with QURI SDK Enterprise also supporting JHPC-quantum’s ROQUO cluster, an NVIDIA GB200 NVL4-based system. QunaSys intends to expand this environment incrementally, moving toward utility-scale quantum-HPC hybrid computing, and will continue to collaborate with RIKEN to broaden the functionality of the SDK and its support for additional devices and HPC environments. By linking these resources, the project aims to accelerate the development of practical quantum applications.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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