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Shunta Arai
Shunta Arai
Institute of Science Tokyo
Verified email at m.titech.ac.jp - Homepage
Title
Cited by
Cited by
Year
Deep neural network detects quantum phase transition
S Arai, M Ohzeki, K Tanaka
Journal of the Physical Society of Japan 87 (3), 033001, 2018
412018
Mean field analysis of reverse annealing for code-division multiple-access multiuser detection
S Arai, M Ohzeki, K Tanaka
Physical Review Research 3 (3), 033006, 2021
312021
Teacher-student learning for a binary perceptron with quantum fluctuations
S Arai, M Ohzeki, K Tanaka
Journal of the Physical Society of Japan 90 (7), 074002, 2021
172021
Dynamics of order parameters of nonstoquastic Hamiltonians in the adaptive quantum Monte Carlo method
S Arai, M Ohzeki, K Tanaka
Physical Review E 99 (3), 032120, 2019
132019
Effectiveness of quantum annealing for continuous-variable optimization
S Arai, H Oshiyama, H Nishimori
Physical Review A 108 (4), 042403, 2023
82023
Quantum annealing for continuous-variable optimization: How is it effective?
S Arai, H Oshiyama, H Nishimori
arXiv e-prints, arXiv: 2305.06631, 2023
22023
Mean field analysis of reverse annealing for code-division multiple-access multiuser demodulator
S Arai, M Ohzeki, K Tanaka
arXiv e-prints, arXiv: 2004.11066, 2020
12020
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
R Hagiwara, S Arai, S Takabe
arXiv preprint arXiv:2501.03518, 2025
2025
Deep unfolded local quantum annealing
S Arai, S Takabe
Physical Review Research 6 (4), 043325, 2024
2024
Dynamical Analysis of Quantum Annealing
ACC Coolen, T Nikoletopoulos, S Arai, K Tanaka
Sublinear Computation Paradigm: Algorithmic Revolution in the Big Data Era …, 2022
2022
Mean-Field Analysis of Sourlas Codes with Adiabatic Reverse Annealing
S Arai
Sublinear Computation Paradigm: Algorithmic Revolution in the Big Data Era …, 2021
2021
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