Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes
Abstract
We develop a workflow decomposing a molecule into fragments via quantum embedding and simulating them with a heterogeneous quantum-classical (HQC) method. We sample fragment electronic configurations on two 156-qubit quantum processors (ibm_cleveland, ibm_kobe), using up to 94 qubits, running 21,006 circuits for over 239 hours, collecting 3.0 · 109 measurement outcomes -- the most resource-intensive HQC computation for quantum chemistry to date. We compute fragment wavefunctions via optimized subspace diagonalization on supercomputers Fugaku, Miyabi-G, and ROQUO, achieving 72.5% parallel efficiency with scalable distributed linear algebra kernels. We simulate two protein-ligand complexes spanning dispersion- and electrostatics-dominated regimes (11,608, 12,635 atoms), demonstrate >40× increase in system size and up to 210× improvement in accuracy over previous state-of-the-art, with HQC matching coupled-cluster (CCSD) accuracy in fragment energies. We present the first HQC protein-ligand binding prediction using a mixed-basis set and an automated end-to-end workflow enabling practical HQC calculations of large protein systems.
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BibTeX
@misc{kennethmmerz2026crossing,
title = {{Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes}},
author = {Kenneth M. Merz, Jr. and Akhil Shajan and Danil Kaliakin and Fangchun Liang and Yuichi Otsuka and Tomonori Shirakawa and Lukas Broers and Han Xu and Miwako Tsuji and Mitsuhisa Sato and Seiji Yunoki and Ryo Wakizaka and Yukio Kawashima and Jun Doi and Hitomi Takahashi and Toshinari Itoko and Hiroshi Horii and Thaddeus Pellegrini and Javier Robledo Moreno and Kevin J. Sung and Ella Fejer and Robert Walkup and Seetharami Seelam and Mario Motta},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2605.01138},
eprint = {2605.01138},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.01138},
}
RIS
TY - UNPB
TI - Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes
AU - Kenneth M. Merz, Jr.
AU - Akhil Shajan
AU - Danil Kaliakin
AU - Fangchun Liang
AU - Yuichi Otsuka
AU - Tomonori Shirakawa
AU - Lukas Broers
AU - Han Xu
AU - Miwako Tsuji
AU - Mitsuhisa Sato
AU - Seiji Yunoki
AU - Ryo Wakizaka
AU - Yukio Kawashima
AU - Jun Doi
AU - Hitomi Takahashi
AU - Toshinari Itoko
AU - Hiroshi Horii
AU - Thaddeus Pellegrini
AU - Javier Robledo Moreno
AU - Kevin J. Sung
AU - Ella Fejer
AU - Robert Walkup
AU - Seetharami Seelam
AU - Mario Motta
PY - 2026
DA - 2026/09/05
PB - arXiv
DO - 10.48550/arxiv.2605.01138
UR - https://arxiv.org/abs/2605.01138
AB - We develop a workflow decomposing a molecule into fragments via quantum embedding and simulating them with a heterogeneous quantum-classical (HQC) method. We sample fragment electronic configurations on two 156-qubit quantum processors (ibm_cleveland, ibm_kobe), using up to 94 qubits, running 21,006 circuits for over 239 hours, collecting 3.0 · 10^9 measurement outcomes -- the most resource-intensive HQC computation for quantum chemistry to date. We compute fragment wavefunctions via optimized subspace diagonalization on supercomputers Fugaku, Miyabi-G, and ROQUO, achieving 72.5% parallel efficiency with scalable distributed linear algebra kernels. We simulate two protein-ligand complexes spanning dispersion- and electrostatics-dominated regimes (11,608, 12,635 atoms), demonstrate >40× increase in system size and up to 210× improvement in accuracy over previous state-of-the-art, with HQC matching coupled-cluster (CCSD) accuracy in fragment energies. We present the first HQC protein-ligand binding prediction using a mixed-basis set and an automated end-to-end workflow enabling practical HQC calculations of large protein systems.
ER -