# Publications

## Quantum Error Detection with Generalized Syndrome Measurement

Quantum error detection has been an experimental focus on early fault-tolerant quantum hardware. However, it requires multiple mid-circuit measurements to extract the syndrome and the readout-induced noise acts as a main contribution to the state infidelity. We present a novel method named Generalized Syndrome Measurement for quantum error detection that only requires a single-shot measurement on a single ancilla, while the canonical syndrome measurement needs to measure multiple times to extract the syndrome for each stabilizer generator. Our method minimizes the readout-induced noise by using single-shot measurements with a tolerable overhead on the gate complexity. We simulated the performance of our method using [[4, 2, 2]] and [[5, 1, 3]] code under realistic noise, and our method outperforms the canonical method when the gate error is comparatively small than the readout error. As mid-circuit measurements are more costly for various kinds of near-term scalable quantum hardware, our method can significantly boost the development of early fault-tolerant quantum computing.

## Computation of Green's function by local variational quantum compilation

Computation of the Green's function is crucial to study the properties of quantum many-body systems such as strongly correlated systems. Although the high-precision calculation of the Green's function is a notoriously challenging task on classical computers, the development of quantum computers may enable us to compute the Green's function with high accuracy even for classically-intractable large-scale systems. Here, we propose an efficient method to compute the real-time Green's function based on the local variational quantum compilation (LVQC) algorithm, which simulates the time evolution of a large-scale quantum system using a low-depth quantum circuit constructed through optimization on a smaller-size subsystem. Our method requires shallow quantum circuits to calculate the Green's function and can be utilized on both near-term noisy intermediate-scale and long-term fault-tolerant quantum computers depending on the computational resources we have. We perform a numerical simulation of the Green's function for the one- and two-dimensional Fermi-Hubbard model up to 4×4 sites lattice (32 qubits) and demonstrate the validity of our protocol compared to a standard method based on the Trotter decomposition. We finally present a detailed estimation of the gate count for the large-scale Fermi-Hubbard model, which also illustrates the advantage of our method over the Trotter decomposition.

## Computational analysis of chemical reactions using a variational quantum eigensolver algorithm without specifying spin multiplicity

The analysis of a chemical reaction along the ground state potential energy surface in conjunction with an unknown spin state is challenging because electronic states must be separately computed several times using different spin multiplicities to find the lowest energy state. However, in principle, the ground state could be obtained with just a single calculation using a quantum computer without specifying the spin multiplicity in advance. In the present work, ground state potential energy curves for PtCO were calculated as a proof-of-concept using a variational quantum eigensolver (VQE) algorithm. This system exhibits a singlet-triplet crossover as a consequence of the interaction between Pt and CO. VQE calculations using a statevector simulator were found to converge to a singlet state in the bonding region, while a triplet state was obtained at the dissociation limit. Calculations performed using an actual quantum device provided potential energies within ±2 kcal/mol of the simulated energies after adopting error mitigation techniques. The spin multiplicities in the bonding and dissociation regions could be clearly distinguished even in the case of a small number of shots. The results of this study suggest that quantum computing can be a powerful tool for the analysis of the chemical reactions of systems for which the spin multiplicity of the ground state and variations in this parameter are not known in advance.

## Quantum-Selected Configuration Interaction: classical diagonalization of Hamiltonians in subspaces selected by quantum computers

We propose quantum-selected configuration interaction (QSCI), a class of hybrid quantum-classical algorithms for calculating the ground- and excited-state energies of many-electron Hamiltonians on noisy quantum devices. Suppose that an approximate ground state can be prepared on a quantum computer either by variational quantum eigensolver or by some other method. Then, by sampling the state in the computational basis, which is hard for classical computation in general, one can identify the electron configurations that are important for reproducing the ground state. The Hamiltonian in the subspace spanned by those important configurations is diagonalized on classical computers to output the ground-state energy and the corresponding eigenvector. The excited-state energies can be obtained similarly. The result is robust against statistical and physical errors because the noisy quantum devices are used only to define the subspace, and the resulting ground-state energy strictly satisfies the variational principle even in the presence of such errors. The expectation values of various other operators can also be estimated for obtained eigenstates with no additional quantum cost, since the explicit eigenvectors in the subspaces are known. We verified our proposal by numerical simulations, and demonstrated it on a quantum device for an 8-qubit molecular Hamiltonian. The proposed algorithms are potentially feasible to tackle some challenging molecules by exploiting quantum devices with several tens of qubits, assisted by high-performance classical computing resources for diagonalization.

## Almost optimal measurement scheduling of molecular Hamiltonian via finite projective plane

We propose an efficient and almost optimal scheme for measuring molecular Hamiltonians in quantum chemistry on quantum computers, which requires 2N^{2} distinct measurements in the leading order with N being the number of molecular orbitals. It achieves the state-of-the-art by improving a previous proposal by Bonet-Monroig et al. [Phys. Rev. X 10, 031064 (2020)] which exhibits 17N^{2}/6 scaling in the leading order. We develop a novel method based on a finite projective plane to construct sets of simultaneously-measurable operators contained in molecular Hamiltonians. Each measurement only requires a depth-O(N) circuit consisting of O(N^{2}) one- and two-qubit gates under the Jordan-Wigner and parity mapping, assuming the linear connectivity of qubits on quantum hardwares. Because evaluating expectation values of molecular Hamiltonians is one of the major bottlenecks in the applications of quantum devices to quantum chemistry, our finding is expected to accelerate such applications.

## Clifford+T-gate Decomposition with Limited Number of T gates, its Error Analysis, and Performance of Unitary Coupled Cluster Ansatz in Pre-FTQC Era

Fault-tolerant quantum computation (FTQC) is essential to robustly implement quantum algorithms and thus to maximize advantages of quantum computers. In this context, a quantum circuit is decomposed into universal gates that can be fault-tolerantly implemented, for example, Clifford+T gates. Here, T gate is usually regarded as an essential resource for quantum computation because its action cannot be simulated efficiently on classical computers. Practically, it is highly likely that only a limited number of T gates are available in the near future due to its experimental difficulty of fault-tolerant implementation. In this paper, considering this Pre-FTQC era, we investigate Clifford+T decomposition with a limited budget of T gates and propose a new model of the error of such decomposition. More concretely, we propose an algorithm to generate the most accurate Clifford+T-gate decomposition of a given single-qubit rotation gate with a fixed number of T gates. We also propose to model the error of Clifford+T decomposition using well-known depolarizing noise by considering the average of the effects of the error. We numerically verified our model successfully explains the decomposition error for a wide variety of molecules using our decomposition algorithm. Thus, we shed light on a first-stage application of quantum computers from a practical point of view and fuel further research towards what quantum computation can achieve in the upcoming future.

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