3 papers
cond-mat.mtrl-sci2026
Deep Learning-Accelerated Dynamic Kinetic Monte Carlo Simulation for Hydrogen Transport in Tungsten
Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura +5
In magnetic confinement fusion reactors, hydrogen plasma irradiation causes material saturation and recycling, where hydrogen released from the tungsten wall significantly impacts…
physics.plasm-ph2026
Development of a 3D-CNN-based Prediction Model for Migration Barriers in Plasma-Wall Interactions
Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura +5
Understanding the long-term transport of hydrogen isotopes in plasma-facing materials, such as tungsten, is critical for the steady-state operation of magnetic confinement fusion r…
quant-ph2024
Quantum conjugate gradient method using the positive-side quantum eigenvalue transformation
Kiichiro Toyoizumi, Kaito Wada, Naoki Yamamoto +1
Quantum algorithms are still challenging to solve linear systems of equations on real devices. This challenge arises from the need for deep circuits and numerous ancilla qubits. We…