South Korean quantum algorithm developer Qunova Computing has demonstrated chemical accuracy in an 80-qubit electronic-structure simulation of the [4Fe-4S] iron-sulfur cubane cluster, executing a hybrid workflow across an IBM Quantum System Two processor and the Fugaku supercomputer at RIKEN. Running its Handover Iterative Variational Quantum Eigensolver (HI-VQE) algorithm, the team achieved an extrapolated ground-state energy within 1.6 milliHartree (1 kcal/mol) of classical density-matrix renormalization group (DMRG) benchmarks while cutting classical supercomputing costs by roughly 300× compared to prior quantum diagonalization runs.
| Qunova HI-VQE 80-Qubit [4Fe-4S] Simulation Benchmarks | ||
|---|---|---|
| Benchmark Dimension | Measured Result / Specification | Comparison & Significance |
| Target System | [4Fe-4S] iron-sulfur cubane cluster (80 qubits) | Catalytic core in nitrogenase and hydrogenase enzymes; intractable for exact classical solvers. |
| Extrapolated Energy | −327.2482 ± 0.0007 Hartree | Matches classical DMRG reference (−327.2471 Ha) within chemical accuracy (1.6 mHa). |
| Classical HPC Efficiency | 2,518 Fugaku node-hours (reached −326.9821 Ha by iteration 2) | Represents an ~300× reduction in classical compute cost versus prior SQD benchmarks. |
| Compute Infrastructure | IBM Quantum System Two & RIKEN Fugaku supercomputer | Supported by Japan’s NEDO Post-5G quantum-HPC hybrid platform initiative. |
Transition-metal complexes such as iron-sulfur clusters govern critical biological and industrial processes, including nitrogen fixation and clean hydrogen synthesis, yet their strongly correlated electrons challenge both standard density functional theory and early quantum algorithms. While prior quantum-centric supercomputing experiments demonstrated subspace sampling on smaller active spaces, reaching quantitative chemical accuracy at 80 qubits has remained an open milestone.
Qunova’s HI-VQE architecture couples quantum state sampling with classical subspace diagonalization without relying on linearity or spatial locality assumptions, enabling application across catalysts, battery electrodes, and pharmaceutical targets. The company plans to integrate orbital rotation and optimization routines into future releases to process between 500 million and 3 billion unique electronic configurations.
Official release details are available via Qunova Computing here. Supporting scientific preprints on arXiv detail the [4Fe-4S] iron-sulfur cluster study here, the foundational HI-VQE methodology here, the classical DMRG benchmark for [4Fe-4S] here, and the prior Fugaku SQD comparison study here. Related QCR coverage includes Qunova’s entry into Japan’s JHPC-quantum test user program here, the addition of HI-VQE to IBM’s Qiskit Functions Catalog here, its launch on AWS Marketplace for Amazon Braket here, and the Cleveland Clinic, RIKEN, and IBM 12,635-atom protein-ligand simulation here.
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