フォロー
Hayata Yamasaki
Hayata Yamasaki
Department of Physics, Graduate School of Science, The University of Tokyo
確認したメール アドレス: phys.s.u-tokyo.ac.jp - ホームページ
タイトル
引用先
引用先
年
Spallation reaction study for fission products in nuclear waste: Cross section measurements for 137Cs and 90Sr on proton and deuteron
H Wang, H Otsu, H Sakurai, DS Ahn, M Aikawa, P Doornenbal, N Fukuda, ...
Physics Letters B 754, 104-108, 2016
672016
Equivalence of approximate gottesman-kitaev-preskill codes
T Matsuura, H Yamasaki, M Koashi
Physical Review A 102 (3), 032408, 2020
632020
Cost-reduced all-Gaussian universality with the Gottesman-Kitaev-Preskill code: Resource-theoretic approach to cost analysis
H Yamasaki, T Matsuura, M Koashi
Physical Review Research 2 (2), 023270, 2020
612020
Time-efficient constant-space-overhead fault-tolerant quantum computation
H Yamasaki, M Koashi
Nature Physics 20 (2), 247-253, 2024
362024
General quantum resource theories: distillation, formation and consistent resource measures
K Kuroiwa, H Yamasaki
Quantum 4, 355, 2020
322020
Multipartite entanglement outperforming bipartite entanglement under limited quantum system sizes
H Yamasaki, A Pirker, M Murao, W Dür, B Kraus
Physical Review A 98 (5), 052313, 2018
322018
Polylog-overhead highly fault-tolerant measurement-based quantum computation: all-Gaussian implementation with Gottesman-Kitaev-Preskill code
H Yamasaki, K Fukui, Y Takeuchi, S Tani, M Koashi
arXiv preprint arXiv:2006.05416, 2020
312020
Entanglement detection with imprecise measurements
S Morelli, H Yamasaki, M Huber, A Tavakoli
Physical Review Letters 128 (25), 250501, 2022
242022
Activation of genuine multipartite entanglement: Beyond the single-copy paradigm of entanglement characterisation
H Yamasaki, S Morelli, M Miethlinger, J Bavaresco, N Friis, M Huber
Quantum 6, 695, 2022
192022
Stochastic gradient line Bayesian optimization for efficient noise-robust optimization of parameterized quantum circuits
S Tamiya, H Yamasaki
npj Quantum Information 8 (1), 90, 2022
182022
Learning with optimized random features: Exponential speedup by quantum machine learning without sparsity and low-rank assumptions
H Yamasaki, S Subramanian, S Sonoda, M Koashi
Advances in neural information processing systems 33, 13674-13687, 2020
162020
Quantum state merging for arbitrarily small-dimensional systems
H Yamasaki, M Murao
IEEE Transactions on Information Theory 65 (6), 3950-3972, 2018
162018
State exchange with quantum side information
Y Lee, R Takagi, H Yamasaki, G Adesso, S Lee
Physical Review Letters 122 (1), 010502, 2019
142019
Graph-associated entanglement cost of a multipartite state in exact and finite-block-length approximate constructions
H Yamasaki, A Soeda, M Murao
Physical Review A 96 (3), 032330, 2017
132017
One-shot quantum error correction of classical and quantum information
Y Nakata, E Wakakuwa, H Yamasaki
Physical Review A 104 (1), 012408, 2021
112021
Entanglement cost for infinite-dimensional physical systems
H Yamasaki, K Kuroiwa, P Hayden, L Lami
arXiv preprint arXiv:2401.09554, 2024
102024
Every quantum helps: Operational advantage of quantum resources beyond convexity
K Kuroiwa, R Takagi, G Adesso, H Yamasaki
Physical Review Letters 132 (15), 150201, 2024
82024
Concatenate codes, save qubits
S Yoshida, S Tamiya, H Yamasaki
arXiv preprint arXiv:2402.09606, 2024
82024
Energy-consumption advantage of quantum computation
F Meier, H Yamasaki
arXiv preprint arXiv:2305.11212, 2023
82023
Exponential error convergence in data classification with optimized random features: Acceleration by quantum machine learning
H Yamasaki, S Sonoda
arXiv preprint arXiv:2106.09028, 2021
82021
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