Publication

Journal Articles (peer reviewed)

Orthogonal frequency-division multiplexing for simultaneous gate operations on multiple qubits via a shared control line (First Author)

Haruki Mitarai, Yukihiro Tadokoro, Hiroya Tanaka

Phys. Rev. Applied 25, 044007 – Published 3 April, 2026

DATA-DRIVEN PREDICTION OF SEISMIC INTENSITY DISTRIBUTIONS FEATURING HYBRID CLASSIFICATION-REGRESSION MODELS

abstruct

Earthquakes are among the most immediate and deadly natural disasters faced by humans. Accurate prediction of the extent of earthquake damage and assessment of potential risks can save numerous lives. In this study, we developed a hybrid model combining classification and regression models, capable of predicting seismic intensity distributions based on the following earthquake parameters: location, depth, and magnitude. As these models are completely data-driven, they can predict seismic intensity distributions without geographic information. The dataset comprises seismic intensity data from earthquakes that occurred in the vicinity of Japan between 1997 and 2020. It includes 1,857 instances of seismic intensity data for earthquakes with a magnitude of 5.0 or greater, sourced from the Japan Meteorological Agency. Regression and classification models were trained, then combined to take advantage of each other and create a hybrid model. The proposed model outperformed commonly used ground-motion prediction equations (GMPEs) in terms of the correlation coefficient, F1 score, and MCC. Furthermore, the proposed model can predict abnormal seismic intensity distributions, a task that conventional GMPEs often struggle to achieve.

Koyu MIZUTANI, Haruki MITARAI, Kakeru MIYAZAKI, Soichiro KUMANO, Toshihiko YAMASAKI

Journal of Japan Association for Earthquake Engineering, 2025 Volume 25 Issue 11 Pages 11_40-11_56

https://doi.org/10.5610/jaee.25.11_40

arXiv: https://arxiv.org/abs/2402.02150

Surgical skill assessment using an AI-based surgical phase recognition model for laparoscopic cholecystectomy

Yoshitsugu Yanagida, Shin Takenaka, Daichi Kitaguchi, Shogo Hamano, Atsuki Tanaka, Haruki Mitarai, Raito Suzuki, Kimimasa Sasaki, Nobuyoshi Takeshita, Tetsuya Ishimaru, Jun Fujishiro & Masaaki Ito

Surg Endosc 39, 5018–5026 (2025)

https://doi.org/10.1007/s00464-025-11903-1

Quantum synchronization of qubits via the dynamical Casimir effect (First Author)

abstruct

In this paper, we study the synchronization of qubits induced by the dynamical Casimir effect in an atom-cavity quantum electrodynamics system. Our investigation revolves around a pragmatic configuration of a quantum system, where two superconducting qubits are coupled to a shared coplanar waveguide resonator terminated at one end by a superconducting quantum interference device. The theoretical analyses of the system dynamics reveal sufficient conditions for ensuring synchronization which are anticipated to be accomplished by photon generation in the resonator. By numerically analyzing the time evolution of the system, we confirm that the conditions are satisfied by photon generation via the dynamical Casimir effect, resulting in qubit synchronization. Notably, we unveil a remarkable feature that is unique to synchronization induced by the dynamical Casimir effect: the differences in the initial states of qubits and the differences in the coupling strengths of qubits to an electromagnetic field affect the synchronization independently without overlap between these factors.

Cite as

Haruki Mitarai, Yoshihiko Hasegawa

Phys. Rev. A 110, 043719 – Published 25 October, 2024

http://arxiv.org/abs/2308.15788

https://journals.aps.org/pra/abstract/10.1103/PhysRevA.110.043719

Improvement of Non-Uniform Temperature Distributions in Intrinsic Josephson Junction Stacks

abstruct

Terahertz (THz) electromagnetic (EM) wave emitters have been expected for applications because these waves are suitable for non-destructive inspection, telecommunication technologies, and other uses. Strong and coherent THz EM waves are known to radiate from large-sized intrinsic Josephson junction (IJJ) stacks in which the self-heating effect is considerably larger and the temperatures in the mesa are non- uniformly distributed. In this study, we numerically investigate and discuss the temperature and current distributions in large- sized IJJ stacks because these parameters are difficult to analyze through experimental investigation. The temperature and current distributions can be obtained by self-consistently solving the non- linear diffusion equation in an equivalent circuit of the mesa by considering the temperature dependence of several parameters. As shown in the numerical results, self-heating caused the local temperature of the center in the mesa to exceed the critical temperature (Tc). To improve the non-uniform temperature and current distributions, we propose an improvement in which an external heat generation system is placed on the edges of the mesa. By applying this measure, the temperature distribution is improved because the edges of the IJJ mesa are heated externally. Furthermore, the local temperatures throughout the mesa were held below Tc, and the current—voltage characteristics were improved using the proposed improvement.

cite

Dai Oikawa, Keita Tsuzuki, Yuki Kumagai, Haruki Mitarai, Hiroya Andoh, Toko Sugiura, Takehiko Tsukamoto,

IEEE Trans. Appl. Supercond. Vol.31, 5, pp.1-4 (2021).

DOI: 10.1109/TASC.2021.3055448

Numerical analysis of temperature and current distributions in large-size intrinsic Josephson junctions with self-heating

abstruct

In this study, we focused on temperature and current distributions in voltage-state large-size intrinsic Josephson junction (IJJ) mesas with a self-heating effect. Because it is difficult to experimentally obtain temperature and current distributions in IJJ mesas, we numerically computed these distributions by solving non-linear diffusion and temperature dependence circuit equations. The local temperature in the mesa exceeded the critical temperature, and a normal-state appeared in the high bias region. Non-uniform temperature and current density distributions were obtained for each bias point of the current–voltage (I–V) characteristics. Normalized c-axis current distributions decreased with an increase in the bias current in the high bias regions. These results were explained using temperature dependent c-axis resistivity.

cite

Dai Oikawa, Haruki Mitarai, Hiromi Tanaka, Keita Tsuzuki, Yuki Kumagai, Toko Sugiura, Hiroya Andoh, Takehiko Tsukamoto,

AIP Advances Vol.10(8), 085113, (2020).

DOI : https://doi.org/10.1063/5.0018989

Preprints (not peer reviewed)

Active interference suppression in frequency-division-multiplexed quantum gates via off-resonant microwave tones (First Author)

Haruki Mitarai, Yukihiro Tadokoro, Hiroya Tanaka

arXiv: https://arxiv.org/abs/2601.14547

International Conference

Prediction of Seismic Intensity Distributions Using Neural Networks (Co-First Author)

abstruct

The ground motion prediction equation is commonly used to predict the seismic intensity distribution. However, it is not easy to apply this method to seismic distributions affected by underground plate structures, which are commonly known as abnormal seismic distributions. This study proposes a hybrid of regression and classification approaches using neural networks. The proposed model treats the distributions as 2-dimensional data like an image. Our method can accurately predict seismic intensity distributions, even abnormal distributions.