Qunova Joins Only 21 in JHPC-quantum Test User Program

Qunova Computing has been selected as one of 21 organizations worldwide to join the JHPC-quantum Test User Program, a Japanese national initiative designed to advance hybrid quantum-high performance computing. The agreement, formalized through a Memorandum of Understanding with JHPC-quantum and funded by NEDO, grants Qunova no-cost access to a uniquely powerful platform combining the Supercomputer Fugaku with an IBM Quantum System Two. Qunova is one of only two non-Japanese organizations participating, reflecting international recognition of its expertise in quantum chemistry and materials science. “It is a privilege to be included in JHPC-quantum alongside many of Japan’s most distinguished research institutions and prominent corporations,” said Kevin Rhee, CEO of Qunova Computing, adding that the partnership will accelerate the company’s path to demonstrating industrial quantum advantage in real-world chemistry applications.

Qunova’s HI-VQE Algorithm for Industrial Quantum Chemistry

This integrated platform represents a significant leap forward in the pursuit of solving complex computational problems, and Qunova’s participation highlights the potential of its proprietary HI-VQE (Handover Iterative Variational Quantum Eigensolver) algorithm. The JHPC-quantum initiative is currently midway through its five-year research and development mandate, running through October, and is designed to connect supercomputers and quantum computers through advanced system software, ultimately supporting the commercial deployment of hybrid quantum applications.

Qunova will leverage this access to apply its HI-VQE algorithm to challenging problems in quantum chemistry, with a particular focus on the iron-sulfur cluster, a benchmark problem with implications for both materials science and drug discovery. The fact that Qunova is one of just two non-Japanese organizations participating in this program demonstrates the power and maturity of our HI-VQE algorithm. The JHPC-quantum platform’s comprehensive hardware, including a superconducting quantum computer in Kobe and a trapped-ion quantum computer in Wako, allows for a diverse range of computational approaches. Qunova specializes in developing hybrid quantum-classical algorithms that combine the strengths of both conventional and quantum computing, aiming to solve problems currently intractable for even the most powerful supercomputers. This partnership accelerates Qunova’s path to demonstrating industrial quantum advantage and provides access to Japan’s expanding network of industrial quantum end users.

JHPC-quantum Platform Integrates Fugaku Supercomputer and IBM Quantum System Two

The convergence of high-performance computing and quantum processing is rapidly evolving, with several national initiatives now establishing integrated platforms to explore hybrid applications; the JHPC-quantum project in Japan stands out due to its scale and ambition. This initiative, funded by NEDO under Japan’s Ministry of Economy, Trade and Industry, recently selected 21 organizations, including Qunova Computing, for its Test User Program, granting them access to a uniquely powerful computational environment. Central to JHPC-quantum is the integration of two distinct, yet complementary, computing architectures: the Supercomputer Fugaku and an IBM Quantum System Two. This combination creates one of the world’s most comprehensive hybrid quantum-HPC environments, offering researchers an unprecedented ability to tackle complex problems that exceed the capabilities of either system alone. The platform also includes a trapped-ion quantum computer in Wako (Quantinuum “Reimei”), further expanding the range of quantum hardware available to program participants.

“It is a true privilege to be included in JHPC-quantum alongside many of Japan’s most distinguished research institutions and prominent corporations,”

Kevin Rhee, CEO of Qunova Computing
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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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