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Sample-based quantum diagonalisation with supercomputers

Algorithms and benchmarks / Chemistry and materials

A quantum-centric supercomputing workflow: a quantum processor samples electronic configurations and a supercomputer diagonalises the Hamiltonian in the space they span, giving upper bounds for the ground-state energy.

Era
Noisy intermediate-scale (NISQ)
Problem class
Chemistry and materials
Speedup
Not established; the method targets problems beyond exact classical diagonalisation.

How it works

Circuits prepare states close to the ground state; their measured bit strings select configurations; noisy samples are cleaned with classical processing, and a large classical diagonalisation runs on the selected space.

Typical use cases

  • Molecules and iron-sulfur clusters relevant to catalysis.

Resource estimates

No resource estimate with stated assumptions was verified for this family in this release.

Demonstrations

  • 2025: Circuits of up to 77 qubits and 10,570 gates with the Fugaku supercomputer for the dissociation of N2 and the [2Fe-2S] and [4Fe-4S] clusters. (J. Robledo-Moreno et al. 2025)

Hardware platforms that fit

  • Superconducting qubits: Run with circuits of up to 77 qubits on a Heron superconducting processor together with the Fugaku supercomputer (Robledo-Moreno et al. 2025).

What you need to run it

Classical simulation
The diagonalisation step itself needs a supercomputer; the quantum part is too large for state-vector simulation at the published sizes.
Noisy hardware (NISQ)
Around 50 to 100 qubits with thousands of gates, plus a tightly coupled HPC system: the model of hybrid HPC-quantum centres such as those of EuroHPC.
Fault-tolerant machine
Not applicable for this family.
Annealer or analogue simulator
Not applicable for this family.

Calculate the memory of a simulation

Where to run it in Europe

Superconducting qubits

The full infrastructure catalogue · The infrastructure deployment tracker

Software

Other open-source frameworks

  • Qiskit (IBM (United States); non-European)

A listing is not an endorsement; check each tool for the features you need.

Limitations and open questions

  • The energies are variational upper bounds; their accuracy compared with the best classical methods has to be checked case by case.

In the Quantum Algorithm Zoo

No matching Zoo entry was found on 23 October 2026; the Zoo lists algorithms with a proven or conjectured speedup, not this family.

Index: the Quantum Algorithm Zoo by Stephen P. Jordan, last updated 2026-09-10, checked 2026-10-23. The portal links to it and copies no description from it. Browse the full Quantum Algorithm Zoo (external site)

Named in European procurements

None of the procurement documents read for this release names it.

Sources

  1. J. Robledo-Moreno et al. (2025). Chemistry Beyond the Scale of Exact Diagonalization on a Quantum-Centric Supercomputer. Science Advances 11, eadu9991 (2025); arXiv:2405.05068. Read: abstract page, retrieved 2026-10-23.