Quantum software developer Qunova Computing has signed a Memorandum of Understanding (MoU) to join JHPC-quantum (Japan High-Performance Computing), a national quantum-supercomputing convergence project funded by the New Energy and Industrial Technology Development Organization (NEDO). The agreement designates Qunova as an official participant in the initiative’s Test User Program following a technical selection process managed by the RIKEN Center for Computational Science. Out of 21 participating organizations selected globally, Qunova is one of only two non-Japanese entities admitted, granting the company direct utility access to Japan’s flagship integrated classical-quantum computational nodes.

Technical Architecture & Algorithmic Handover Mechanisms

The computing infrastructure managed under the JHPC-quantum framework addresses the integration limits between classical Message Passing Interface (MPI) supercomputing clusters and distributed quantum coprocessors. Traditional Variational Quantum Eigensolver (VQE) algorithms frequently encounter performance degradation on Noisy Intermediate-Scale Quantum (NISQ) hardware due to the high volume of quantum measurements (shots) required to achieve chemical accuracy, alongside processing overheads when passing variables between Python-based developer frameworks and high-performance classical nodes. To resolve these execution barriers, Qunova will deploy its proprietary Handover Iterative Variational Quantum Eigensolver (HI-VQE) algorithm.

The HI-VQE framework restructures standard hybrid processing parameters by introducing a mathematical “handover” loop that splits computational loads based on hardware efficiency:

  1. Core Subspace Extraction: The algorithm utilizes the quantum processor as a targeted coprocessor, executing shallow-depth hardware circuits to isolate the specific multi-reference electronic configurations that dominate a molecule’s ground state. Qunova Computing
  2. Problem Transformation: The initial, high-dimensional Hamiltonian is rewritten and compressed into a simplified active space framework, reducing the cumulative quantum sampling burden.
  3. Classical Optimization: The transformed problem is passed back to the classical supercomputer to resolve the remaining configuration interactions, achieving an energy precision threshold of 1.6 mHa (chemical accuracy). Qunova Computing
  4. Target Application: The joint project will apply this hybrid stack to benchmark strongly correlated electronic systems, focusing on iron-sulfur (Fe–S) clusters—a complex 40-qubit active space molecular simulation that serves as a diagnostic standard for battery design, materials informatics, and small-molecule drug discovery.

Ecosystem Convergence & Hybrid Infrastructure Mapping

The Test User Program provides Qunova with allocation time across an interconnected national hardware network overseen by RIKEN and SoftBank. The compute infrastructure links Japan’s flagship classical supercomputer, Fugaku, alongside next-generation NVIDIA Grace-Blackwell liquid-cooled AI clusters via a high-speed, low-latency networking bus. This classical layer is integrated with local quantum backends, including an on-premises superconducting IBM Quantum System Two installed in Kobe (“IBM Kobe”) and a high-fidelity trapped-ion Quantinuum platform located in Wako (“Reimei”).

Operating midway through its five-year R&D mandate running from November 2023 through October 2028, the JHPC-quantum project uses a unified API layer to manage job queues and cross-node data exchanges. By incorporating Qunova’s hardware-agnostic solvers into this multi-platform testbed, the initiative aims to establish production-grade software libraries ahead of the platform’s scheduled commercial cloud pre-release in 2028.

You can review the official partnership announcement via the Qunova Computing news room here. For an analysis of the selection benchmarks, intellectual property protocols, and active enterprise participation parameters governing the hybrid testbed, access the primary JHPC-quantum program registry here.

June 3, 2026

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