Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866911639877451776 |
|---|---|
| author | Merz, Jr., Kenneth M. Shajan, Akhil Kaliakin, Danil Liang, Fangchun Otsuka, Yuichi Shirakawa, Tomonori Broers, Lukas Xu, Han Tsuji, Miwako Sato, Mitsuhisa Yunoki, Seiji Wakizaka, Ryo Kawashima, Yukio Doi, Jun Itoko, Toshinari Horii, Hiroshi Pellegrini, Thaddeus Moreno, Javier Robledo Sung, Kevin J. Fejer, Ella Walkup, Robert Seelam, Seetharami Motta, Mario |
| author_facet | Merz, Jr., Kenneth M. Shajan, Akhil Kaliakin, Danil Liang, Fangchun Otsuka, Yuichi Shirakawa, Tomonori Broers, Lukas Xu, Han Tsuji, Miwako Sato, Mitsuhisa Yunoki, Seiji Wakizaka, Ryo Kawashima, Yukio Doi, Jun Itoko, Toshinari Horii, Hiroshi Pellegrini, Thaddeus Moreno, Javier Robledo Sung, Kevin J. Fejer, Ella Walkup, Robert Seelam, Seetharami Motta, Mario |
| contents | Ab initio wavefunction methods provide accurate molecular simulations but their computational scaling restricts applications to small systems. We develop a workflow combining quantum embedding to decompose a molecule into fragments with a heterogeneous quantum-classical (HQC) method to simulate fragments. We sample fragment electronic configurations on two 156-qubit quantum processors (ibm$\_$cleveland, ibm$\_$kobe), using up to 94 qubits, running 9,200 circuits for over 100 hours, collecting $1.3 \cdot 10^9$ measurement outcomes - the most resource-intensive HQC computation for quantum chemistry to date. We compute fragment wavefunctions via optimized subspace diagonalization on two supercomputers (Fugaku, Miyabi-G), 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 and 12,635 atoms), demonstrate $>40\times$ increase in system size and up to $210\times$ improvement in accuracy over the previous state-of-the-art, with HQC matching coupled-cluster (CCSD) accuracy in fragment energies, and establish a scalable pathway for systematically improvable biomolecular simulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_01138 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes Merz, Jr., Kenneth M. Shajan, Akhil Kaliakin, Danil Liang, Fangchun Otsuka, Yuichi Shirakawa, Tomonori Broers, Lukas Xu, Han Tsuji, Miwako Sato, Mitsuhisa Yunoki, Seiji Wakizaka, Ryo Kawashima, Yukio Doi, Jun Itoko, Toshinari Horii, Hiroshi Pellegrini, Thaddeus Moreno, Javier Robledo Sung, Kevin J. Fejer, Ella Walkup, Robert Seelam, Seetharami Motta, Mario Quantum Physics Chemical Physics Computational Physics Ab initio wavefunction methods provide accurate molecular simulations but their computational scaling restricts applications to small systems. We develop a workflow combining quantum embedding to decompose a molecule into fragments with a heterogeneous quantum-classical (HQC) method to simulate fragments. We sample fragment electronic configurations on two 156-qubit quantum processors (ibm$\_$cleveland, ibm$\_$kobe), using up to 94 qubits, running 9,200 circuits for over 100 hours, collecting $1.3 \cdot 10^9$ measurement outcomes - the most resource-intensive HQC computation for quantum chemistry to date. We compute fragment wavefunctions via optimized subspace diagonalization on two supercomputers (Fugaku, Miyabi-G), 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 and 12,635 atoms), demonstrate $>40\times$ increase in system size and up to $210\times$ improvement in accuracy over the previous state-of-the-art, with HQC matching coupled-cluster (CCSD) accuracy in fragment energies, and establish a scalable pathway for systematically improvable biomolecular simulations. |
| title | Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes |
| topic | Quantum Physics Chemical Physics Computational Physics |
| url | https://arxiv.org/abs/2605.01138 |