Quantum--classical break-even in electronic dynamics of macrocyclic molecules
Abstract
Here we demonstrate quantum--classical break-even for chemical dynamics applications, reaching useful accuracy with a quantum-hardware wall-clock time comparable to that estimated for practical classical computing resources. To this end, we develop a workflow for problems that are hardware-native but classically hard. We target large ring-shaped molecules that map naturally onto quantum hardware with neighboring connections. Exploiting the spatial locality of interactions, we compress short-time evolution within a small region using tensor networks. We then use rotational symmetry to replicate the compressed circuit in space and time, enabling long-time dynamics of large systems with practical classical processing times. We apply the workflow to conjugated macrocycles with rotational periodicity, 12-qubit benzene and 120-qubit [60]annulene, by embedding their electronic structure onto loops of IBM quantum processors. For the annulene, we compared the quantum-processing-unit (QPU) wall-clock times for hole-doped nonequilibrium dynamics to the estimated wall-clock time of two state-of-the-art classical methods, Majorana propagation and matrix-product-state time evolution based on the time-dependent variational principle. We show a situation in which a hybrid quantum--classical strategy is comparable to a classical-only counterpart in terms of both accuracy and computational time for a conventional high-performance computing system under ideal parallelization. These results show that quantum hardware can become a realistic computational option for chemical simulations for practitioners in chemical science and engineering.
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BibTeX
@misc{kanno2026quantumclassical,
title = {{Quantum--classical break-even in electronic dynamics of macrocyclic molecules}},
author = {Shu Kanno and Kenji Sugisaki and Takashi Imamichi and Toshinari Itoko and Rei Sakuma and Hajime Nakamura and Qi Gao and Naoki Yamamoto},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.39693},
eprint = {2609.39693},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.39693},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Quantum--classical break-even in electronic dynamics of macrocyclic molecules
AU - Shu Kanno
AU - Kenji Sugisaki
AU - Takashi Imamichi
AU - Toshinari Itoko
AU - Rei Sakuma
AU - Hajime Nakamura
AU - Qi Gao
AU - Naoki Yamamoto
PY - 2026
DA - 2026/10/19
PB - arXiv
DO - 10.48550/arxiv.2609.39693
UR - https://arxiv.org/abs/2609.39693
AB - Here we demonstrate quantum--classical break-even for chemical dynamics applications, reaching useful accuracy with a quantum-hardware wall-clock time comparable to that estimated for practical classical computing resources. To this end, we develop a workflow for problems that are hardware-native but classically hard. We target large ring-shaped molecules that map naturally onto quantum hardware with neighboring connections. Exploiting the spatial locality of interactions, we compress short-time evolution within a small region using tensor networks. We then use rotational symmetry to replicate the compressed circuit in space and time, enabling long-time dynamics of large systems with practical classical processing times. We apply the workflow to conjugated macrocycles with rotational periodicity, 12-qubit benzene and 120-qubit [60]annulene, by embedding their electronic structure onto loops of IBM quantum processors. For the annulene, we compared the quantum-processing-unit (QPU) wall-clock times for hole-doped nonequilibrium dynamics to the estimated wall-clock time of two state-of-the-art classical methods, Majorana propagation and matrix-product-state time evolution based on the time-dependent variational principle. We show a situation in which a hybrid quantum--classical strategy is comparable to a classical-only counterpart in terms of both accuracy and computational time for a conventional high-performance computing system under ideal parallelization. These results show that quantum hardware can become a realistic computational option for chemical simulations for practitioners in chemical science and engineering.
ER -