quantum chemistry

Towards Chemically Accurate and Scalable Quantum Simulations on IQM Quantum Hardware: A Quantum-HPC Hybrid Approach

arXiv:2604.01983

summary

The paper presents large‑scale experiments on IQM’s 24‑qubit superconducting processor, using up to 16 qubits and sample‑based quantum diagonalization with various ansätze to compute molecular ground‑state energies and, together with density‑matrix embedding theory, achieve chemical accuracy for larger molecular systems.

Abstract

We present a large-scale experimental study of quantum-computing-based molecular simulation carried out on IQM's Sirius 24-qubit superconducting processor, utilizing up to 16 operational qubits. The work employs Sample-based Quantum Diagonalization (SQD) together with the Local Unitary Cluster Jastrow (LUCJ) ansatz to estimate ground-state energies for a set of benchmark molecules, including H $_{2}$ , LiH, BeH $_{2}$ , H $_{2}$ O, and NH $_{3}$ . In addition, we introduce a Linear-CNOT variant of the Unitary Coupled-Cluster Singles and Doubles (LCNot-UCCSD) ansatz within the SQD workflow, trading higher circuit depth for reduced classical preprocessing. A comparison between these ansÃ¤tze is provided, clarifying their respective strengths, limitations, and suitability for near-term quantum hardware. We further explore potential energy landscapes through 1D scans for H $_{2}$ and HeH $^{+}$ using both STO-3G and 6-31G basis sets, and for LiH and BeH $_{2}$ in STO-3G. Extending beyond this, we demonstrate the experimental construction of a full 2D potential energy surface for the water molecule on quantum hardware, mapped over a 32 $\times$ 32 grid in bond length and bond angle. To move beyond small benchmark systems, we combine SQD(LUCJ) with Density Matrix Embedding Theory (DMET) to compute active-space energies for a set of ligand-like molecules, as well as the pharmacologically relevant amantadine system. Across all studies, the majority of quantum-computed energies agree with reference FCI results, as well as with DMET-CASCI energies for embedded systems, to within chemical accuracy for the chosen basis sets. These results demonstrate the reliability of sample-based diagonalization approaches and underscore the potential of hybrid embedding strategies for extending quantum simulations to increasingly complex molecular systems, while also highlighting their practicality on current IQM quantum hardware.

86 pages, 41 figures

Topics & keywords

#quantum simulation #molecular electronic structure #variational ansatz #hybrid quantum‑classical #superconducting qubitsSample-based Quantum Diagonalization (SQD)Local Unitary Cluster Jastrow (LUCJ)LCNot-UCCSDDensity Matrix Embedding Theory (DMET)chemical accuracyIQM Sirius processor