論文 - 山本　直樹

Natural quantum reservoir computing for temporal information processing

Suzuki Y., Gao Q., Pradel K.C., Yasuoka K., Yamamoto N.

Scientific Reports （Scientific Reports）  12 （ 1 ）  2022年12月

　概要を見る

Reservoir computing is a temporal information processing system that exploits artificial or physical dissipative dynamics to learn a dynamical system and generate the target time-series. This paper proposes the use of real superconducting quantum computing devices as the reservoir, where the dissipative property is served by the natural noise added to the quantum bits. The performance of this natural quantum reservoir is demonstrated in a benchmark time-series regression problem and a practical problem classifying different objects based on temporal sensor data. In both cases the proposed reservoir computer shows a higher performance than a linear regression or classification model. The results indicate that a noisy quantum device potentially functions as a reservoir computer, and notably, the quantum noise, which is undesirable in the conventional quantum computation, can be used as a rich computation resource.

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Speed limits for two-qubit gates with weakly anharmonic qubits

Ashhab S., Yoshihara F., Fuse T., Yamamoto N., Lupascu A., Semba K.

Physical Review A （Physical Review A）  105 （ 4 ）  2022年04月

ISSN  24699926

　概要を見る

We consider the implementation of two-qubit gates when the physical systems used to realize the qubits possess additional quantum states in the accessible energy range. We use optimal control theory to determine the maximum achievable gate speed for two-qubit gates in the qubit subspace of the many-level Hilbert space, and we analyze the effect of the additional quantum states on the gate speed. We identify two competing mechanisms. On one hand, higher energy levels are generally more strongly coupled to each other. Under suitable conditions, this stronger coupling can be utilized to make two-qubit gates significantly faster than the reference value based on simple qubits. On the other hand, a weak anharmonicity constrains the speed at which the system can be adequately controlled: according to the intuitive picture, faster operations require stronger control fields, which are more likely to excite higher levels in a weakly anharmonic system, which in turn leads to faster decoherence and uncontrolled leakage outside the qubit space. To account for this constraint, we modify the pulse optimization algorithm to avoid pulses that lead to appreciable population of the higher levels. In this case, we find that the presence of the higher levels can lead to a significant reduction in the maximum achievable gate speed. We also compare the optimal-control gate speeds with those obtained using the cross-resonance or selective-darkening gate protocol. We find that this protocol, with some parameter optimization, can be used to achieve a relatively fast implementation of the controlled-NOT gate. These results can help the search for optimized gate implementations in realistic quantum computing architectures, such as those based on superconducting circuits. They also provide guidelines for desirable conditions on anharmonicity that would allow optimal utilization of the higher levels to achieve fast quantum gates.

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Grover search revisited: Application to image pattern matching

Tezuka H., Nakaji K., Satoh T., Yamamoto N.

Physical Review A （Physical Review A）  105 （ 3 ）  2022年03月

ISSN  24699926

　概要を見る

The landmark Grover algorithm for amplitude amplification serves as an essential subroutine in various types of quantum algorithms, with guaranteed quantum speedup in query complexity. However, there has been no proposal to realize the original motivating application of the algorithm, i.e., the database search or more broadly the pattern matching in a practical setting, mainly due to the technical difficulty in efficiently implementing the data loading and amplitude amplification processes. In this paper, we propose a quantum algorithm that approximately executes the entire Grover database search or pattern matching algorithm. The key idea is to use the recently proposed approximate amplitude encoding method on a shallow quantum circuit, together with the easily implementable inversion-test operation for realizing the projected quantum state having similarity to the query data, followed by the amplitude amplification operation that is independent to the target data index. We provide a thorough demonstration of the algorithm in the problem of image pattern matching.

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Noisy quantum amplitude estimation without noise estimation

Tanaka T., Uno S., Onodera T., Yamamoto N., Suzuki Y.

Physical Review A （Physical Review A）  105 （ 1 ）  2022年01月

ISSN  24699926

　概要を見る

Many quantum algorithms contain an important subroutine - the quantum amplitude estimation. As the name implies, this is essentially the parameter estimation problem and thus can be handled via the established statistical estimation theory. However, this problem has an intrinsic difficulty that the system, i.e., the real quantum computing device, inevitably introduces unknown noise; the probability distribution model then has to incorporate many nuisance noise parameters, resulting that the construction of an optimal estimator becomes inefficient and difficult. For this problem we apply the theory of nuisance parameters (more specifically, the parameter orthogonalization method) to precisely compute the maximum likelihood estimator for only the target amplitude parameter by removing the other nuisance noise parameters. That is, we can estimate the amplitude parameter without estimating the noise parameters. We validate the parameter orthogonalization method in a numerical simulation and study the performance of the estimator in the experiment using a real superconducting quantum device.

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Quantum semi-supervised generative adversarial network for enhanced data classification

Nakaji K., Yamamoto N.

Scientific Reports （Scientific Reports）  11 （ 1 ）  2021年12月

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In this paper, we propose the quantum semi-supervised generative adversarial network (qSGAN). The system is composed of a quantum generator and a classical discriminator/classifier (D/C). The goal is to train both the generator and the D/C, so that the latter may get a high classification accuracy for a given dataset. Hence the qSGAN needs neither any data loading nor to generate a pure quantum state, implying that qSGAN is much easier to implement than many existing quantum algorithms. Also the generator can serve as a stronger adversary than a classical one thanks to its rich expressibility, and it is expected to be robust against noise. These advantages are demonstrated in a numerical simulation.

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Applications of quantum computing for investigations of electronic transitions in phenylsulfonyl-carbazole TADF emitters

Gao Q., Jones G.O., Motta M., Sugawara M., Watanabe H.C., Kobayashi T., Watanabe E., Ohnishi Y.y., Nakamura H., Yamamoto N.

npj Computational Materials （npj Computational Materials）  7 （ 1 ）  2021年12月

　概要を見る

A quantum chemistry study of the first singlet (S1) and triplet (T1) excited states of phenylsulfonyl-carbazole compounds, proposed as useful thermally activated delayed fluorescence (TADF) emitters for organic light emitting diode (OLED) applications, was performed with the quantum Equation-Of-Motion Variational Quantum Eigensolver (qEOM-VQE) and Variational Quantum Deflation (VQD) algorithms on quantum simulators and devices. These quantum simulations were performed with double zeta quality basis sets on an active space comprising the highest occupied and lowest unoccupied molecular orbitals (HOMO, LUMO) of the TADF molecules. The differences in energy separations between S1 and T1 (ΔEST) predicted by calculations on quantum simulators were found to be in excellent agreement with experimental data. Differences of 17 and 88 mHa with respect to exact energies were found for excited states by using the qEOM-VQE and VQD algorithms, respectively, to perform simulations on quantum devices without error mitigation. By utilizing state tomography to purify the quantum states and correct energy values, the large errors found for unmitigated results could be improved to differences of, at most, 4 mHa with respect to exact values. Consequently, excellent agreement could be found between values of ΔEST predicted by quantum simulations and those found in experiments.

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Amplitude estimation via maximum likelihood on noisy quantum computer

Tanaka T., Suzuki Y., Uno S., Raymond R., Onodera T., Yamamoto N.

Quantum Information Processing （Quantum Information Processing）  20 （ 9 ）  2021年09月

ISSN  15700755

　概要を見る

Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude of a given quantum state, which is a core subroutine in various computing tasks such as the Monte Carlo methods. One of those algorithms is based on the maximum likelihood estimate with parallelized quantum circuits. In this paper, we extend this method so that it incorporates the realistic noise effect, and then give an experimental demonstration on a superconducting IBM Quantum device. The maximum likelihood estimator is constructed based on the model assuming the depolarization noise. We then formulate the problem as a two-parameters estimation problem with respect to the target amplitude parameter and the noise parameter. In particular we show that there exist anomalous target values, where the Fisher information matrix becomes degenerate and consequently the estimation error cannot be improved even by increasing the number of amplitude amplifications. The experimental demonstration shows that the proposed maximum likelihood estimator achieves quantum speedup in the number of queries, though the estimation error saturates due to the noise. This saturated value of estimation error is consistent to the theory, which implies the validity of the depolarization noise model and thereby enables us to predict the basic requirement on the hardware components (particularly the gate error) in quantum computers to realize the quantum speedup in the amplitude estimation task.

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Modified Grover operator for quantum amplitude estimation

Uno S., Suzuki Y., Hisanaga K., Raymond R., Tanaka T., Onodera T., Yamamoto N.

New Journal of Physics （New Journal of Physics）  23 （ 8 ）  2021年08月

ISSN  13672630

　概要を見る

In this paper, we propose a quantum amplitude estimation method that uses a modified Grover operator and quadratically improves the estimation accuracy in the ideal case, as in the conventional one using the standard Grover operator. Under the depolarizing noise, the proposed method can outperform the conventional one in the sense that it can in principle achieve the ultimate estimation accuracy characterized by the quantum Fisher information in the limit of a large number of qubits, while the conventional one cannot achieve the same value of ultimate accuracy. In general this superiority requires a sophisticated adaptive measurement, but we numerically demonstrate that the proposed method can outperform the conventional one and approach to the ultimate accuracy, even with a simple non-adaptive measurement strategy.

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Quantum Functionalities Via Feedback Amplification

Shimazu R., Yamamoto N.

Physical Review Applied （Physical Review Applied）  15 （ 4 ）  2021年04月

　概要を見る

Feedback amplification is a key technique for synthesizing various functionalities, especially in electronic circuits involving op amps. This paper presents a quantum version of this methodology, where the general phase-preserving quantum amplifier and coherent (i.e., measurement-free) feedback are employed to construct various types of systems having useful functionalities: quantum versions of differentiator, integrator, self-oscillator, and active filters. The class of active filters includes the Butterworth filter, which can be used to enhance the capacity of an optical quantum communication channel, and the nonreciprocal amplifier, which enables measurement of a superconducting qubits system as well as protection of it by separating input from output fields. A particularly detailed investigation is performed on the active phase-canceling filter for realizing a broadband gravitational-wave detector; that is, the feedback-amplification method is used to construct an active filter that compensates the phase delay of the signal and eventually recovers the sensitivity in the high-frequency regime.

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Computational investigations of the lithium superoxide dimer rearrangement on noisy quantum devices

Gao Q., Garcia J.M., Yamamoto N., Nakamura H., Gujarati T.P., Jones G.O., Rice J.E., Wood S.P., Pistoia M., Yamamoto N.

Journal of Physical Chemistry A （Journal of Physical Chemistry A）  125 （ 9 ） 1827 - 1836 2021年03月

ISSN  10895639

　概要を見る

Quantum chemistry studies of biradical systems are challenging due to the required multiconfigurational nature of the wavefunction. In this work, Variational Quantum Eigensolver (VQE) is used to compute the energy profile for the lithium superoxide dimer rearrangement, involving biradical species, on quantum simulators and devices. Considering that current quantum devices can only handle limited number of qubits, we present guidelines for selecting an appropriate active space to perform computations on chemical systems that require many qubits. We show that with VQE performed with a quantum simulator reproduces results obtained with full-configuration interaction (Full CI) for the chosen active space. However, results deviate from exact values by about 39 mHa for calculations on a quantum device. This deviation can be improved to about 4 mHa using the readout mitigation approach and can be further improved to 2 mHa, approaching chemical accuracy, using the state tomography technique to purify the calculated quantum state.

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Linear open quantum systems with passive Hamiltonians and a single local dissipative process

Ma S., Woolley M.J., Petersen I.R., Yamamoto N.

Automatica （Automatica）  125 2021年03月

ISSN  00051098

　概要を見る

We consider linear open quantum systems with passive Hamiltonians and a single, local dissipative process. Generally speaking, these systems are easier to implement than systems with active Hamiltonians and non-local dissipative processes. We parametrize the set of all covariance matrices corresponding to pure Gaussian steady states that can be achieved by this type of quantum system. Given such pure states, we parametrize the corresponding linear quantum systems with passive Hamiltonians and a single, local dissipative process that generate them.

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Normalized Gradient Descent for Variational Quantum Algorithms

Suzuki Y., Yano H., Raymond R., Yamamoto N.

Proceedings - 2021 IEEE International Conference on Quantum Computing and Engineering, QCE 2021 （Proceedings - 2021 IEEE International Conference on Quantum Computing and Engineering, QCE 2021）     1 - 9 2021年

　概要を見る

Variational quantum algorithms (VQAs) are promising methods that leverage noisy quantum computers and classical computing techniques for practical applications. In VQAs, the classical optimizers such as gradient-based optimizers are utilized to adjust the parameters of the quantum circuit so that the objective function is minimized. However, they often suffer from the so-called vanishing gradient or barren plateau issue. On the other hand, the normalized gradient descent (NGD) method, which employs the normalized gradient vector to update the parameters, has been successfully utilized in several optimization problems. Here, we study the performance of the NGD methods in the optimization of VQAs for the first time. Our goal is two-fold. The first is to examine the effectiveness of NGD and its variants for overcoming the vanishing gradient problems. The second is to propose a new NGD that can attain the faster convergence than the ordinary NGD. We performed numerical simulations of these gradient-based optimizers in the context of quantum chemistry where VQAs are used to find the ground state of a given Hamiltonian. The results show the effective convergence property of the NGD methods in VQAs, compared to the relevant optimizers without normalization. Moreover, we make use of some normalized gradient vectors at the past iteration steps to propose the novel historical NGD that has a theoretical guarantee to accelerate the convergence speed, which is observed in the numerical experiments as well.

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Expressibility of the alternating layered ansatz for quantum computation

Nakaji K., Yamamoto N.

Quantum （Quantum）  5 2021年

　概要を見る

The hybrid quantum-classical algorithm is actively examined as a technique applicable even to intermediate-scale quantum computers. To execute this algorithm, the hardware efficient ansatz is often used, thanks to its implementability and expressibility; however, this ansatz has a critical issue in its trainability in the sense that it generically suffers from the so-called gradient vanishing problem. This issue can be resolved by limiting the circuit to the class of shallow alternating layered ansatz. However, even though the high trainability of this ansatz is proved, it is still unclear whether it has rich expressibility in state generation. In this paper, with a proper definition of the expressibility found in the literature, we show that the shallow alternating layered ansatz has almost the same level of expressibility as that of hardware efficient ansatz. Hence the expressibility and the trainability can coexist, giving a new designing method for quantum circuits in the intermediate-scale quantum computing era.

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Quantum self-learning Monte Carlo and quantum-inspired Fourier transform sampler

Endo K., Nakamura T., Fujii K., Yamamoto N.

Physical Review Research （Physical Review Research）  2 （ 4 ）  2020年12月

ISSN  26431564

　概要を見る

The self-learning metropolis-Hastings algorithm is a powerful Monte Carlo method that, with the help of machine learning, adaptively generates an easy-to-sample probability distribution for approximating a given hard-to-sample distribution. This paper provides a new self-learning Monte Carlo method that utilizes a quantum computer to output a proposal distribution. In particular, we show a novel subclass of this general scheme based on the quantum Fourier transform circuit; when the dimension of the input to QFT corresponding to the low-frequency components is not large, this sampler is classically simulable while having a certain advantage over conventional methods. The performance of this quantum-inspired algorithm is demonstrated by some numerical simulations.

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A Systems Theory Approach to the Synthesis of Minimum Noise Non-Reciprocal Phase-Insensitive Quantum Amplifiers

Petersen I.R., James M.R., Ugrinovskii V., Yamamoto N.

Proceedings of the IEEE Conference on Decision and Control （Proceedings of the IEEE Conference on Decision and Control）  2020-December   3836 - 3841 2020年12月

ISSN  07431546

　概要を見る

We present a systems theory approach to finding the minimum required level of added quantum noise in a nonreciprocal phase-insensitive quantum amplifier. We also present a synthesis procedure for constructing a quantum optical nonreciprocal phase-insensitive quantum amplifier which adds the minimum level of quantum noise and achieves a required gain and bandwidth. This synthesis procedure is based on a singularly perturbed quantum system involving the broadband approximation of a Bogoliubov transformation and leads to an amplifier involving three squeezers and six beamsplitters.

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Quantum speed limit for robust state characterization and engineering

Kobayashi K., Yamamoto N.

Physical Review A （Physical Review A）  102 （ 4 ）  2020年10月

ISSN  24699926

　概要を見る

In this paper we propose to use a quantum speed limit (QSL) as a measure of robustness of states, defining a state with a bigger QSL as more robust. From this perspective, it is important to have an explicitly computable QSL, because then we can formulate an engineering problem of the Hamiltonian that makes a target state robust against decoherence. Hence we derive an explicitly computable QSL that is applicable to general Markovian open quantum systems. This QSL is tighter than another explicitly computable QSL, in an important setup such that decoherence is small. Also, the Hamiltonian engineering problem with this QSL is a quadratic convex optimization problem, and thus it is efficiently solvable. The idea of robust state characterization and the Hamiltonian engineering, in terms of the QSL, is demonstrated with several examples.

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Efficient Discrete Feature Encoding for Variational Quantum Classifier

Yano H., Suzuki Y., Raymond R., Yamamoto N.

Proceedings - IEEE International Conference on Quantum Computing and Engineering, QCE 2020 （Proceedings - IEEE International Conference on Quantum Computing and Engineering, QCE 2020）     11 - 21 2020年10月

　概要を見る

Recent days have witnessed significant interests in applying quantum-enhanced techniques for solving machine learning tasks in, e.g., classification, regression, and recommender systems. Variational methods that use quantum resources of imperfect quantum devices with the help of classical computing techniques are popular for supervised learning. Variational Quantum Classification (VQC) is one of such variational methods with possible quantum advantage in using quantum-enhanced features that are hard to compute by classical methods. Its performance depends on the mapping of classical features into quantum-enhanced feature space. Although there have been many quantum-mapping functions proposed so far, there is little discussion on efficient mapping of discrete features, such as, race, gender, marriage status and others that are often significant for classifying datasets of interest. We first introduce the use of Quantum Random Access Coding (QRAC) to map such discrete features efficiently into limited number of qubits for VQC. We numerically show that QRAC can help speeding up the training of VQC by reducing its parameters via reduction on the number of qubits for the mapping. We confirm the effectiveness of the QRAC in VQC by experimenting on classification of healthcare datasets with both simulators and real quantum devices.

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Temporal information processing on noisy quantum computers

Chen J., Nurdin H.I., Yamamoto N.

Physical Review Applied （Physical Review Applied）  14 （ 2 ）  2020年08月

　概要を見る

The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems. Reservoir computing is an efficient learning paradigm that utilizes nonlinear dynamical systems for temporal information processing, i.e., processing of input sequences to produce output sequences. Here we propose quantum reservoir computing that harnesses complex dissipative quantum dynamics. Our class of quantum reservoirs is universal, in that any nonlinear fading memory map can be approximated arbitrarily closely and uniformly over all inputs by a quantum reservoir from this class. We describe a subclass of the universal class that is readily implementable using quantum gates native to current noisy gate-model quantum computers. Proof-of-principle experiments on remotely accessed cloud-based superconducting quantum computers demonstrate that small and noisy quantum reservoirs can tackle high-order nonlinear temporal tasks. Our theoretical and experimental results pave the path for attractive temporal processing applications of near-term gate-model quantum computers of increasing fidelity but without quantum error correction, signifying the potential of these devices for wider applications including neural modeling, speech recognition, and natural language processing, going beyond static classification and regression tasks.

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Analysis and synthesis of feature map for kernel-based quantum classifier

Suzuki Y., Yano H., Gao Q., Uno S., Tanaka T., Akiyama M., Yamamoto N.

Quantum Machine Intelligence （Quantum Machine Intelligence）  2 （ 1 ）  2020年06月

ISSN  25244906

　概要を見る

A method for analyzing the feature map for the kernel-based quantum classifier is developed; that is, we give a general formula for computing a lower bound of the exact training accuracy, which helps us to see whether the selected feature map is suitable for linearly separating the dataset. We show a proof of concept demonstration of this method for a class of 2-qubit classifier, with several 2-dimensional datasets. Also, a synthesis method, which combines different kernels to construct a better-performing feature map in a lager feature space, is presented.

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Amplitude estimation without phase estimation

Suzuki Y., Uno S., Raymond R., Tanaka T., Onodera T., Yamamoto N.

Quantum Information Processing （Quantum Information Processing）  19 （ 2 ）  2020年02月

ISSN  15700755

　概要を見る

This paper focuses on the quantum amplitude estimation algorithm, which is a core subroutine in quantum computation for various applications. The conventional approach for amplitude estimation is to use the phase estimation algorithm, which consists of many controlled amplification operations followed by a quantum Fourier transform. However, the whole procedure is hard to implement with current and near-term quantum computers. In this paper, we propose a quantum amplitude estimation algorithm without the use of expensive controlled operations; the key idea is to utilize the maximum likelihood estimation based on the combined measurement data produced from quantum circuits with different numbers of amplitude amplification operations. Numerical simulations we conducted demonstrate that our algorithm asymptotically achieves nearly the optimal quantum speedup with a reasonable circuit length.

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