activity
20222026
most citedPrediction of Seismic Intensity Distributions Using Neural Networks

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Active interference suppression in frequency-division-multiplexed quantum gates via off-resonant microwave tones

Haruki Mitarai, Yukihiro Tadokoro, Hiroya Tanaka

The increasing number of control lines connecting quantum processors to external electronics constitutes a major bottleneck in the realization of large-scale quantum computers. Fre…

quant-ph2025

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

Haruki Mitarai, Yukihiro Tadokoro, Hiroya Tanaka

The increasing number of qubits in quantum processors necessitates a corresponding increase in the number of control lines between the processor, which is typically operated at cry…

cs.CV2024

Data-Driven Prediction of Seismic Intensity Distributions Featuring Hybrid Classification-Regression Models

Koyu Mizutani, Haruki Mitarai, Kakeru Miyazaki +2

Earthquakes are among the most immediate and deadly natural disasters that humans face. Accurately forecasting the extent of earthquake damage and assessing potential risks can be…

quant-ph2023★ 1 cited

Quantum synchronization of qubits via dynamical Casimir effect

Haruki Mitarai, Yoshihiko Hasegawa

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…

cs.CV2022★ 1 cited

Prediction of Seismic Intensity Distributions Using Neural Networks

Koyu Mizutani, Haruki Mitarai, Kakeru Miyazaki +3

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…