arXiv subjects

Miwako Tsuji

Publications and source records attributed to Miwako Tsuji.

9 recordsLinked to original sources

arXiv2026

Crossing the 12,000-atom barrier with heterogeneous quantum-classical supercomputing: quantum chemistry of protein-ligand complexes

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 $3.0 \cdot 10^9$ measurement outcomes -- the most resource-intensive HQC computation for quantum chemistry to date. We compute fragment wavefunctions via optimized subspace diagonalization on 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 $>40\times$ increase in system size and up to $210\times$ 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.

quant-ph↗

arXiv2026

Quantum-HPC Software Stacks and the openQSE Reference Architecture: A Survey

Quantum resources are increasingly integrated into high-performance computing (HPC) and cloud environments, but quantum high-performance computing (QHPC) software stacks remain isolated, often proprietary, full-stack solutions lacking common interfaces across runtime, resource management, orchestration, and execution layers. This paper analyzes nine production QHPC stacks and identifies common design patterns and emerging requirements, covering deployment models, application interaction patterns, SDK support, and readiness for fault-tolerant operation. The survey exposes consistent needs in runtime abstraction, resource management, interconnect semantics, and observability. Based on these findings, we propose the open quantum-HPC software ecosystem ( openQSE) reference architecture as a first step toward unifying the state-of-the-practice. openQSE defines a set of layer boundaries that allow different implementations to interoperate while preserving deployment flexibility, and is structured to support both current noisy intermediate-scale quantum (NISQ) workloads and future fault-tolerant quantum computing (FTQC) systems without changes to upper-layer application interfaces.

quant-ph↗

arXiv2026

The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute

Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continues at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence times. This perspective paper examines the relationship between QC and high-performance computing (HPC), highlighting their complementary roles in enhancing computational efficiency. It is widely acknowledged that even fully error-corrected QCs will not be suited for all computational task. Rather, future compute infrastructures are anticipated to employ quantum acceleration within hybrid systems that integrate HPC and QC. While QCs can enhance classical computing, traditional HPC remains essential for maximizing quantum acceleration. This integration is a priority for supercomputing centers and companies, sparking innovation to address the challenges of merging these technologies. The Accelerated Data Analytics and Computing Institute (ADAC) is comprised of globally leading HPC centers. ADAC has established a Quantum Computing Working Group to promote and catalyze collaboration among its members. This paper synthesizes insights from the QC Working Group, supplemented by findings from a member survey detailing ongoing projects and strategic directions. By outlining the current landscape and challenges of QC integration into HPC ecosystems, this work aims to provide HPC specialists with a deeper understanding of QC and its future implications for computationally intensive endeavors.

quant-ph↗

arXiv2026

Quantum-HPC hybrid computation of biomolecular excited-state energies

We develop a workflow within the ONIOM framework and demonstrate it on the hybrid computing system consisting of the supercomputer Fugaku and the Quantinuum Reimei trapped-ion quantum computer. This hybrid platform extends the layered approach for biomolecular chemical reactions to accurately treat the active site, such as a protein, and the large and often weakly correlated molecular environment. Our result marks a significant milestone in enabling scalable and accurate simulation of complex biomolecular reactions

quant-ph↗

arXiv2025

Closed-loop calculations of electronic structure on a quantum processor and a classical supercomputer at full scale

Quantum computers must operate in concert with classical computers to deliver on the promise of quantum advantage for practical problems. To achieve that, it is important to understand how quantum and classical computing can interact together, and how one can characterize the scalability and efficiency of hybrid quantum-classical workflows. So far, early experiments with quantum-centric supercomputing workflows have been limited in scale and complexity. Here, we use a Heron quantum processor deployed on premises with the entire supercomputer Fugaku to perform the largest computation of electronic structure involving quantum and classical high-performance computing. We design a closed-loop workflow between the quantum processors and 152,064 classical nodes of Fugaku, to approximate the electronic structure of chemistry models beyond the reach of exact diagonalization, with accuracy comparable to some all-classical approximation methods. Our work pushes the limits of the integration of quantum and classical high-performance computing, showcasing computational resource orchestration at the largest scale possible for current classical supercomputers.

quant-ph↗

arXiv2025

Asynchronous-Many-Task Systems: Challenges and Opportunities -- Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

Dynamic and adaptive mesh refinement is pivotal in high-resolution, multi-physics, multi-model simulations, necessitating precise physics resolution in localized areas across expansive domains. Today's supercomputers' extreme heterogeneity presents a significant challenge for dynamically adaptive codes, highlighting the importance of achieving performance portability at scale. Our research focuses on astrophysical simulations, particularly stellar mergers, to elucidate early universe dynamics. We present Octo-Tiger, leveraging Kokkos, HPX, and SIMD for portable performance at scale in complex, massively parallel adaptive multi-physics simulations. Octo-Tiger supports diverse processors, accelerators, and network backends. Experiments demonstrate exceptional scalability across several heterogeneous supercomputers including Perlmutter, Frontier, and Fugaku, encompassing major GPU architectures and x86, ARM, and RISC-V CPUs. Parallel efficiency of 47.59% (110,080 cores and 6880 hybrid A100 GPUs) on a full-system run on Perlmutter (26% HPCG peak performance) and 51.37% (using 32,768 cores and 2,048 MI250X) on Frontier are achieved.

cs.DC↗

arXiv2024

Quantum circuit synthesis via a random combinatorial search

We use a random search technique to find quantum gate sequences that implement perfect quantum state preparation or unitary operator synthesis with arbitrary targets. This approach is based on the recent discovery that there is a large multiplicity of quantum circuits that achieve unit fidelity in performing a given target operation, even at the minimum number of single-qubit and two-qubit gates needed to achieve unit fidelity. We show that the fraction of perfect-fidelity quantum circuits increases rapidly as soon as the circuit size exceeds the minimum circuit size required for achieving unit fidelity. This result implies that near-optimal quantum circuits for a variety of quantum information processing tasks can be identified relatively easily by trying only a few randomly chosen quantum circuits and optimizing their parameters. In addition to analyzing the case where the CNOT gate is the elementary two-qubit gate, we consider the possibility of using alternative two-qubit gates. In particular, we analyze the case where the two-qubit gate is the B gate, which is known to reduce the minimum quantum circuit size for two-qubit operations. We apply the random search method to the problem of decomposing the 4-qubit Toffoli gate and find a 15 CNOT-gate decomposition.

quant-ph↗

arXiv2024

Massively parallel CMA-ES with increasing population

The Increasing Population Covariance Matrix Adaptation Evolution Strategy (IPOP-CMA-ES) algorithm is a reference stochastic optimizer dedicated to blackbox optimization, where no prior knowledge about the underlying problem structure is available. This paper aims at accelerating IPOP-CMA-ES thanks to high performance computing and parallelism when solving large optimization problems. We first show how BLAS and LAPACK routines can be introduced in linear algebra operations, and we then propose two strategies for deploying IPOP-CMA-ES efficiently on large-scale parallel architectures with thousands of CPU cores. The first parallel strategy processes the multiple searches in the same ordering as the sequential IPOP-CMA-ES, while the second one processes concurrently these multiple searches. These strategies are implemented in MPI+OpenMP and compared on 6144 cores of the supercomputer Fugaku. We manage to obtain substantial speedups (up to several thousand) and even super-linear ones, and we provide an in-depth analysis of our results to understand precisely the superior performance of our second strategy.

cs.DC↗

arXiv2021

102 PFLOPS Lattice QCD quark solver on Fugaku

We present results on the world's first over 100 PFLOPS single precision lattice QCD quark solver on the japanese new supercomputer Fugaku. We achieve a factor 38 time speedup from the supercomputer K on the same problem size, $192^4$, with 102 PFLOPS, 10% floating-point operation efficiency against single precision floating-point operation peak. The evaluation region is the single precision BiCGStab for a Clover-Wilson Dirac matrix with Schwarz Alternating Procedure domain decomposition preconditioning using Jacobi iteration for the local domain matrix inversion.

hep-lat↗