arXiv subjects

Toshinari Itoko

Publications and source records attributed to Toshinari Itoko.

17 recordsLinked to original sources

arXiv2026

Quantum--classical break-even in electronic dynamics of macrocyclic molecules

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. Specifically, we construct a quantum workflow for electronic dynamics based on tensor-network circuit compression leveraging spatial locality, extending circuit compression beyond one-dimensional open-boundary systems. This enables application of the workflow to problems that are hardware-native but classically hard. The workflow targets one-dimensional periodic Hamiltonians: circuits classically optimized only for short-time evolution within a small spatial region can be replicated in both space and time to construct long-time dynamics of the full system without classically simulating the corresponding large-scale evolution. We apply the workflow to cyclic 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, the quantum-processing-unit (QPU) wall-clock times for hole-doped nonequilibrium dynamics became comparable to the estimated wall-clock time of two classical methods, Majorana propagation and matrix-product-state time evolution based on the time-dependent variational principle; this corresponds to tens to hundreds of compute nodes depending on the task (36 CPU cores per node), even assuming ideal scaling, bringing the quantum calculation into a wall-clock-time regime comparable to conventional parallel high-performance-computing resources. We also show a situation in which a hybrid quantum--classical calculation is a reasonable choice in terms of both accuracy and computational time. These results show that quantum hardware can become a realistic computational option for chemically relevant electronic dynamics.

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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.

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arXiv2026

Point-group symmetry analysis of many-electron wavefunctions on a quantum computer

A point group is a set of spatial symmetry operations in molecular systems and is an indispensable tool for analyzing molecular orbitals and spectroscopy experiments in chemistry. Several quantum algorithms to exploit this symmetry have been proposed, but practical implementations of point-group symmetry operations and the detailed symmetry analysis of realistic many-electron wavefunctions are still missing. In this work, we propose an ancilla-free hybrid method to analyze point-group symmetries of many-electron states, which works for both abelian and non-abelian groups. For a given wavefunction, our method calculates the projection weights of point-group irreducible representations by applying orbital rotations derived from the eigenvectors of the representation matrices, making it applicable to arbitrary basis functions. The usefulness of our approach is demonstrated through numerical simulations of benzene and ferrocene molecules. Furthermore, we perform a hardware demonstration of the weight calculation of the ground state and the first excited state of benzene in $D_{2h}$ symmetry, using up to 32 qubits of IBM's ibm_kawasaki device. By combining a tensor-network based encoding scheme and error mitigation techniques, we find the weights of irreducible representations for both states are faithfully reproduced within a few percent error. Our results suggest that the proposed method serves as a practical tool for analyzing symmetry properties of many-electron wavefunctions in realistic material simulations on near-term and early fault-tolerant quantum computers.

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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.

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arXiv2025

Hamiltonian simulation-based quantum-selected configuration interaction for large-scale electronic structure calculations with a quantum computer

Quantum-selected configuration interaction (QSCI) is an approach for quantum chemical calculations using current quantum computers. In conventional QSCI, Slater determinants used for the wave function expansion are sampled by iteratively performing approximate wave function preparation and subsequent measurement in the computational basis, and then the subspace Hamiltonian matrix is diagonalized on a classical computer. In this approach, preparation of a high-quality approximate wave function is necessary to accurately compute total energies. Here we propose a Hamiltonian simulation-based QSCI (HSB-QSCI) to avoid this difficulty, by sampling the Slater determinants from quantum states generated by the real-time evolution of approximate wave functions. We provide numerical simulations for the lowest spin-singlet and triplet states of oligoacenes (benzene, naphthalene, and anthracene), phenylene-1,4-dinitrene, and hexa-1,2,3,4,5-pentaene. We found that the HSB-QSCI is applicable not only to molecules where the Hartree--Fock provides a good approximation of the ground state, but also to strongly correlated systems where preparing a high-quality approximate wave function is hard. Hardware demonstrations of the HSB-QSCI are also reported for carbyne molecules expressed by up to 36 qubits, using an IBM Quantum processor. The HSB-QSCI captures more than 99.18\% of the correlation energies in the active space by considering about 1\% of all the Slater determinants in 36 qubit systems, illustrating the ability of the proposed method to efficiently consider important electronic configurations.

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arXiv2025

Shift of quantum critical point of discrete time crystal on a noisy quantum simulator

Recent advances in quantum technology have enabled the simulation of quantum many-body systems on real quantum devices. However, such quantum simulators are inherently subject to decoherence, and its impact on system dynamics - particularly near quantum phase transitions - remains insufficiently understood. In this work, we experimentally investigate how decoherence in quantum devices affects the dynamics of quantum time crystals, using a 156-qubit IBM Quantum system. We find that decoherence shifts the location of critical behavior associated with the phase transition, suggesting that noisy simulations can lead to inaccurate identification of phase boundaries. Our results underscore the importance of understanding and mitigating decoherence to reliably simulate quantum many-body systems on near-term quantum hardware.

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arXiv2025

Quantum Optimization Benchmarking Library - The Intractable Decathlon

Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particularly in combinatorial optimization - where most algorithms are heuristics - it is key to empirically analyze their performance on hardware and track progress towards quantum advantage. To this extent, we present ten optimization problem classes that are difficult for existing classical algorithms and can (mostly) be linked to practically relevant applications, with the goal to enable systematic, fair, and comparable benchmarks for quantum optimization methods. Further, we introduce the Quantum Optimization Benchmarking Library (QOBLIB) where the problem instances and solution track records can be found. The individual properties of the problem classes vary in terms of objective and variable type, coefficient ranges, and density. Crucially, they all become challenging for established classical methods already at system sizes ranging from less than 100 to, at most, an order of 100,000 decision variables, allowing to approach them with today's quantum computers. We reference the results from state-of-the-art solvers for instances from all problem classes and demonstrate exemplary baseline results obtained with quantum solvers for selected problems. The baseline results illustrate a standardized form to present benchmarking solutions, which has been designed to ensure comparability of the used methods, reproducibility of the respective results, and trackability of algorithmic and hardware improvements over time. We encourage the optimization community to explore the performance of available classical or quantum algorithms and hardware platforms with the benchmarking problem instances presented in this work toward demonstrating quantum advantage in optimization.

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arXiv2025

Robust Error Accumulation Suppression for Quantum Circuits

We present a \textit{robust error accumulation suppression} (\textbf{REAS}) technique to manage errors in quantum computers. Our method reduces the accumulation of errors in any quantum circuit composed of single- or two-qubit gates expressed as $e^{-i σθ}$ for Pauli operators $σ$ and $θ\in [0,π)$, which forms a universal gate set. For coherent errors -- which include gate overrotation and crosstalk -- we demonstrate a reduction of the error scaling in an $L$-depth circuit from $O(L)$ to $O(\sqrt{L})$. This asymptotic error suppression behavior can be proven in a regime where all gates -- including those constituting the error-suppressing protocol itself -- are noisy. Going beyond coherent errors, we derive the general form of decoherence noise that can be suppressed by REAS. Lastly, we experimentally demonstrate the effectiveness of our approach regarding realistic errors using 100-qubit circuits with up to 64 two-qubit gate layers on IBM Quantum processors.

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arXiv2025

Multilevel Circuit Optimization in Quantum Compilers: A Case Study

In this paper, we explore multilevel circuit optimization (MLCO), where we deploy multiple gate sets and progressively lower the source circuit through the gate sets to the target circuit. At each level, we first perform an appropriate set of circuit simplifications and then lower the simplified circuit into the next level, decomposing the gates not supported there. We demonstrate its effectiveness, using as a case study the source circuit for Hamiltonian simulation to solve a partial differential equation, which is densely populated with multi-controlled gates and is transformed by the state-of-the-art circuit compiler to the target circuit with the quadratic number of CX gates in the number of qubits. MLCO makes visible higher-level circuit structures, providing us with insights about how to simplify the circuits and how to decompose the gates. By putting the right circuit structure in place and selecting the right decomposition algorithm, we could cause massive cancellation of entangling gates, thereby having achieved the quadratic reduction in the number of CX gates.

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arXiv2024

Dynamics of measurement-induced state transitions in superconducting qubits

We have investigated temporal fluctuation of superconducting qubits via the time-resolved measurement for an IBM Quantum system. We found that the qubit error rate abruptly changes during specific time intervals. Each high error state persists for several tens of seconds, and exhibits an on-off behavior. The observed temporal instability can be attributed to qubit transitions induced by a measurement stimulus. Resonant transition between fluctuating dressed states of the qubits coupled with high-frequency resonators can be responsible for the error-rate change.

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arXiv2023

Three-qubit Parity Gate via Simultaneous Cross Resonance Drives

Native multi-qubit parity gates have various potential quantum computing applications, such as entanglement creation, logical state encoding and parity measurement in quantum error correction. Here, using simultaneous cross-resonance drives on two control qubits with a common target, we demonstrate an efficient implementation of a three-qubit parity gate. We have developed a calibration procedure based on the one for the echoed cross-resonance gate. We confirm that our use of simultaneous drives leads to higher interleaved randomized benchmarking fidelities than a naive implementation with two consecutive CNOT gates. We also demonstrate that our simultaneous parity gates can significantly improve the parity measurement error probability for the heavy-hexagon code on an IBM Quantum processor using seven superconducting qubits with all-microwave control.

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arXiv2023

Detection of temporal fluctuation in superconducting qubits for quantum error mitigation

We have investigated instability of a superconducting quantum computer by continuously monitoring the qubit output. We found that qubits exhibit a step-like change in the error rates. This change is repeatedly observed, and each step persists for several minutes. By analyzing the correlation between the increased errors and anomalous variance of the output, we demonstrate quantum error mitigation based on post-selection. Numerical analysis on the proposed method was also conducted.

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arXiv2021

Approximate Solutions of Combinatorial Problems via Quantum Relaxations

Combinatorial problems are formulated to find optimal designs within a fixed set of constraints. They are commonly found across diverse engineering and scientific domains. Understanding how to best use quantum computers for combinatorial optimization is to date an open problem. Here we propose new methods for producing approximate solutions for the maximum cut problem and its weighted version, which are based on relaxations to local quantum Hamiltonians. These relaxations are defined through commutative maps, which in turn are constructed borrowing ideas from quantum random access codes. We establish relations between the spectra of the relaxed Hamiltonians and optimal cuts of the original problems, via two quantum rounding protocols. The first one is based on projections to random magic states. It produces average cuts that approximate the optimal one by a factor of least 0.555 or 0.625, depending on the relaxation chosen, if given access to a quantum state with energy between the optimal classical cut and the maximal relaxed energy. The second rounding protocol is deterministic and it is based on estimation of Pauli observables. The proposed quantum relaxations inherit memory compression from quantum random access codes, which allowed us to test the performances of the methods presented for 3-regular random graphs and a design problem motivated by industry for sizes up to 40 nodes, on superconducting quantum processors.

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arXiv2021

Sampling Strategy Optimization for Randomized Benchmarking

Randomized benchmarking (RB) is a widely used method for estimating the average fidelity of gates implemented on a quantum computing device. The stochastic error of the average gate fidelity estimated by RB depends on the sampling strategy (i.e., how to sample sequences to be run in the protocol). The sampling strategy is determined by a set of configurable parameters (an RB configuration) that includes Clifford lengths (a list of the number of independent Clifford gates in a sequence) and the number of sequences for each Clifford length. The RB configuration is often chosen heuristically and there has been little research on its best configuration. Therefore, we propose a method for fully optimizing an RB configuration so that the confidence interval of the estimated fidelity is minimized while not increasing the total execution time of sequences. By experiments on real devices, we demonstrate the efficacy of the optimization method against heuristic selection in reducing the variance of the estimated fidelity.

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arXiv2020

Scheduling of Operations in Quantum Compiler

When scheduling quantum operations, a shorter overall execution time of the resulting schedule yields a better throughput and higher fidelity output. In this paper, we demonstrate that quantum operation scheduling can be interpreted as a special type of job-shop problem. On this basis, we provide its formulation as Constraint Programming while taking into account commutation between quantum operations. We show that this formulation improves the overall execution time of the resulting schedules in practice through experiments with a real quantum compiler and quantum circuits from two common benchmark sets.

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arXiv2020

Demonstration of quantum volume 64 on a superconducting quantum computing system

We improve the quality of quantum circuits on superconducting quantum computing systems, as measured by the quantum volume, with a combination of dynamical decoupling, compiler optimizations, shorter two-qubit gates, and excited state promoted readout. This result shows that the path to larger quantum volume systems requires the simultaneous increase of coherence, control gate fidelities, measurement fidelities, and smarter software which takes into account hardware details, thereby demonstrating the need to continue to co-design the software and hardware stack for the foreseeable future.

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arXiv2019

Optimization of Quantum Circuit Mapping using Gate Transformation and Commutation

This paper addresses quantum circuit mapping for Noisy Intermediate-Scale Quantum (NISQ) computers. Since NISQ computers constraint two-qubit operations on limited couplings, an input circuit must be transformed into an equivalent output circuit obeying the constraints. The transformation often requires additional gates that can affect the accuracy of running the circuit. Based upon a previous work of quantum circuit mapping that leverages gate commutation rules, this paper shows algorithms that utilize both transformation and commutation rules. Experiments on a standard benchmark dataset confirm the algorithms with more rules can find even better circuit mappings compared with the previously-known best algorithms.

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