arXiv subjects

Masahiko Kamoshita

Publications and source records attributed to Masahiko Kamoshita.

4 recordsLinked to original sources

arXiv2026

QSCI-CMP: Quantum-Selected Configuration Interaction with Chemically Motivated Preselection

We present QSCI-CMP, a quantum-classical hybrid algorithm for molecular ground-state calculations that reduces both the query count and the gate count of sample-based quantum diagonalization with amplitude amplification (SQD-AA). SQD-AA mitigates the measurement bottleneck of quantum-selected configuration interaction (QSCI) by amplifying the basis states that have not yet been measured. Its oracle, however, specifies the measured states by listing them one by one, so its gate count grows with the number of collected states. Moreover, the quantum resources are spent even on states whose importance is evident from chemical knowledge, such as low-order excitations from the Hartree-Fock reference, which could be collected classically at the outset. We therefore propose to fix such chemically trivial states in advance, include them in the diagonalization subspace from the start, and exclude them from the amplification target, using a low-cost oracle that recognizes them through the excitation level and the seniority number of each basis state. We numerically demonstrate that QSCI-CMP reduces the query count and the gate count required to reach chemical accuracy by up to approximately 68% and 72% relative to SQD-AA for 24-qubit systems. The chemically trivial subspace is freely tunable within the classical computational budget. A larger subspace shifts more work onto the classical solver and increases the reduction in quantum cost, and when it captures the ground state sufficiently well, no quantum sampling is needed at all. We also point out that a query-optimal iteration count known from the analysis of quantum search further reduces the query count of both methods by approximately 12%.

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arXiv2026

Evaluating higher-order product formulae for molecular ground-state energy estimation

We evaluate deterministic higher-order product formulae for molecular ground-state energy estimation. Motivated by recent fault-tolerant architectures in which non-Clifford operations may be generated more locally and cheaply than in conventional assumptions, we re-examine such formulae as practical candidates for quantum chemistry. Using one-dimensional hydrogen chains from $\mathrm{H}_2$ to $\mathrm{H}_{15}$ as benchmarks, we estimate both the total gate count and the depth of $R_Z$-rotation layers required to reach a target energy error. To make this comparison feasible at larger system sizes, we use a perturbative method to estimate the eigenvalue error induced by each product formula and thereby evaluate the cost of the corresponding phase-estimation procedure. Among the previously considered formulae, the eighth-order construction introduced by Morales et al. [M. E. S. Morales et al., "Greatly improved higher-order product formulae for quantum simulation," arXiv:2210.15817v2 (2024)] minimizes both cost metrics in the benchmark at a chemically relevant target error. We also find that increasing the formal order does not automatically reduce the total cost: near chemical accuracy, the tenth-order formula introduced in the same work can be less efficient than the eighth-order one. Motivated by this observation, we construct a new fourth-order formula; it achieves the lowest total gate count among the formulae considered for all H-chain instances near chemical accuracy and over much of the 0.1-10 mHa target-error window for most instances, while also reducing the $R_Z$-layer depth. These results clarify how deterministic higher-order product formulae should be selected for molecular ground-state energy estimation.

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arXiv2025

Orbital-rotated Fermi-Hubbard model as a benchmarking problem for quantum chemistry with the exact solution

Quantum chemistry is a key target for quantum computing, but benchmarking quantum algorithms for large molecular systems remains challenging due to the lack of exactly solvable yet structurally realistic models. In particular, molecular Hamiltonians typically contain $O(N^4)$ Pauli terms, significantly increasing the cost of quantum simulations, while many exactly solvable models, such as the one-dimensional Fermi-Hubbard (1D FH) model, contain only $O(N)$ terms. In this work, we introduce the orbital-rotated Fermi-Hubbard (ORFH) model as a scalable and exactly solvable benchmarking problem for quantum chemistry algorithms. Starting from the 1D FH model, we apply a spin-involved orbital rotation to construct a Hamiltonian that retains the exact ground-state energy but exhibits a Pauli term count scaling as $O(N^4)$, similar to real molecular systems. We analyze the ORFH Hamiltonian from multiple perspectives, including operator norm and electronic correlation. We benchmark variational quantum eigensolver (VQE) optimizers and Pauli term grouping methods, and compare their performance with those for hydrogen chains. Furthermore, we show that the ORFH Hamiltonian increases the computational difficulty for classical methods such as the density matrix renormalization group (DMRG), offering a nontrivial benchmark beyond quantum algorithms. Our results demonstrate that the ORFH model provides a versatile and scalable testbed for benchmarking quantum chemistry algorithms under realistic structural conditions, while maintaining exact solvability even at large system sizes.

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arXiv2024

ADAPT-QSCI: Adaptive Construction of an Input State for Quantum-Selected Configuration Interaction

We present a quantum-classical hybrid algorithm for calculating the ground state and its energy of the quantum many-body Hamiltonian by proposing an adaptive construction of a quantum state for the quantum-selected configuration interaction (QSCI) method. QSCI allows us to select important electronic configurations in the system to perform CI calculation (subspace diagonalization of the Hamiltonian) by sampling measurement for a proper input quantum state on a quantum computer, but how we prepare a desirable input state has remained a challenge. We propose an adaptive construction of the input state for QSCI in which we run QSCI repeatedly to grow the input state iteratively. We numerically illustrate that our method, dubbed ADAPT-QSCI, can yield accurate ground-state energies for small molecules, including a noisy situation for eight qubits where error rates of two-qubit gates and the measurement are both as large as 1%. ADAPT-QSCI serves as a promising method to take advantage of current noisy quantum devices and pushes forward its application to quantum chemistry.

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