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Combinatorial optimization problems are one of the areas where near-term noisy quantum computers may have practical advantage against classical computers. Recently a novel feedback-based quantum optimization algorithm has been proposed by Magann \textit{et al}. The method explicitly determines quantum circuit parameters by feeding back measurement results thus avoids classical parameter optimization that is known to cause significant trouble in quantum approximate optimization algorithm, the well-studied near-term algorithm. Meanwhile, a significant drawback of the feedback-based quantum optimization is that it requires deep circuits, rendering the method unsuitable to noisy quantum devices. In this study we propose a new feedback law for parameter determination by introducing the second-order approximation with respect to time interval, a hyperparameter in the feedback-based quantum optimization. This allows one to take larger time interval, leading to acceleration of convergence to solutions. In numerical simulations on the maximum cut problem we demonstrate that our proposal significantly reduces circuit depth, with its linear scaling with the problem size smaller by more than an order of magnitude. We expect that the new feedback law proposed in this work may pave the way for feedback-based quantum optimization with near-term noisy quantum computers., Comment: 7 pages, 6 figures

Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring and simulation of quantum many-body systems. In the last decade, research and development of QCs have rapidly advanced. Now hundreds of physical qubits are at our disposal, and one can find several remarkable experiments actually outperforming the classical computer in a specific computational task. On the other hand, it is unclear what the typical usages of the QCs are. Here we conduct an extensive survey on the papers that are posted in the quant-ph section in arXiv and claim to have used QCs in their abstracts. To understand the current situation of the research and development of the QCs, we evaluated the descriptive statistics about the papers, including the number of qubits employed, QPU vendors, application domains and so on. Our survey shows that the annual number of publications is increasing, and the typical number of qubits employed is about six to ten, growing along with the increase in the quantum volume (QV). Most of the preprints are devoted to applications such as quantum machine learning, condensed matter physics, and quantum chemistry, while quantum error correction and quantum noise mitigation use more qubits than the other topics. These imply that the increase in QV is fundamentally relevant, and more experiments for quantum error correction, and noise mitigation using shallow circuits with more qubits will take place., Comment: 14 pages, 5 figures, figures regenerated

Quantum approximate optimization algorithm (QAOA) is a promising hybrid quantum-classical algorithm to solve combinatorial optimization problems in the era of noisy intermediate-scale quantum computers. Recently warm-start approaches have been proposed to improve the performance of QAOA, where approximate solutions are obtained by classical algorithms in advance and incorporated into the initial state and/or unitary ansatz. In this work, we study in detail how the accuracy of approximate solutions affect the performance of the warm-start QAOA (WS-QAOA). We numerically find that in typical MAX-CUT problems, WS-QAOA tends to outperform QAOA as approximate solutions become closer to the exact solutions in terms of the Hamming distance. We reveal that this could be quantitatively attributed to the initial state of the ansatz. We also solve MAX-CUT problems by WS-QAOA with approximate solutions obtained via QAOA, having a better result than QAOA especially when the circuit is relatively shallow. We believe that our study may deepen understanding of the performance of WS-QAOA and also provide a guide as to the necessary quality of approximate solutions.

Variational quantum eigensolver (VQE) is regarded as a promising candidate of hybrid quantum-classical algorithm for the near-term quantum computers. Meanwhile, VQE is confronted with a challenge that statistical error associated with the measurement as well as systematic error could significantly hamper the optimization. To circumvent this issue, we propose classically-optimized VQE (co-VQE), where the whole process of the optimization is efficiently conducted on a classical computer. The efficacy of the method is guaranteed by the observation that quantum circuits with a constant (or logarithmic) depth are classically tractable via simulations of local subsystems. In co-VQE, we only use quantum computers to measure nonlocal quantities after the parameters are optimized. As proof-of-concepts, we present numerical experiments on quantum spin models with topological phases. After the optimization, we identify the topological phases by nonlocal order parameters as well as unsupervised machine learning on inner products between quantum states. The proposed method maximizes the advantage of using quantum computers while avoiding strenuous optimization on noisy quantum devices. Furthermore, in terms of quantum machine learning, our study shows an intriguing approach that employs quantum computers to generate data of quantum systems while using classical computers for the learning process., Comment: 8 pages, 6 figures

We theoretically study magnetoelectric effects in a heterostructure of a generic band insulator and a ferromagnet. In contrast to the kinetic magnetoelectric effect in metals, referred to as the Edelstein effect or the inverse spin galvanic effect, our mechanism relies on virtual interband transitions between the valence and conduction bands and therefore immune to disorder or impurity scattering. By calculating electric field-induced magnetization by the linear response theory, we reveal that the magnetoelectric effect shows up without specific parameter choices. The magnetoelectric effect qualitatively varies by changing the direction of the magnetic moment in the ferromagnet: the response is diagonal for the out-of-plane moment, whereas it is off-diagonal for the inplane moment. We also find out that in optical frequencies, the magnetoelectric signal can be drastically enhanced via interband resonant excitations. Finally, we estimate the magnitude of the magnetoelectric effect for a hybrid halide perovskite semiconductor as an example of the band insulator and compare it with other magnetoelectric materials. We underscore that our mechanism is quite general and widely expectable, only requiring the Rashba spin-orbit coupling and exchange coupling. Our result could potentially offer a promising method of Joule heating-free electric manipulation of magnetic moments in spintronic devices., Comment: 11 pages, 8 figures

We study magnetic textures realized in noncentrosymmetric Kondo lattice models, in which localized magnetic moments weakly interact with itinerant electrons subject to Rashba and Dresselhaus spin-orbit couplings. By virtue of state-of-the-art numerical simulations as well as variational calculations, we uncover versatile multiple-$Q$ orderings under zero magnetic field, which are found to originate in the instabilities of the Fermi surface whose spin degeneracy is lifted by the spin-orbit couplings. In the case with equally-strong Rashba and Dresselhaus spin-orbit couplings, which is known to realize a persistent spin helix in semiconductor quantum wells, we discover a sextuple-$Q$ magnetic ordering with a checkerboard-like spatial pattern of the spin scalar chirality. In the presence of either Rashba or Dresselhaus spin-orbit coupling, we find out another multiple-$Q$ ordering, which is distinct from Skyrmion crystals discussed under the same symmetry. Our results indicate that the cooperation of the spin-charge and spin-orbit couplings brings about richer magnetic textures than those studied within effective spin models. The situations would be experimentally realized, e.g., in noncentrosymmetric heavy-fermion compounds and heterostructures of spin-orbit coupled metals and magnetic insulators.