2022年度 | 大阪大学基礎工学研究科藤井研究室

K. Mizuta and K. Fujii,
“Optimal Hamiltonian simulation for time-periodic systems” Quantum 7, 962 (2023). arXiv:2209.05048
Y. Takada, Y.Takeuchi, and K.Fujii,
“Highly accurate decoder for topological color codes with simulated annealing” arXiv:2303.01348
A. Nakayama, K. Mitarai, L. Placidi, T. Sugimoto, and K. Fujii,
“VQE-generated Quantum Circuit Dataset for Machine Learning” arXiv:2302.09751
Y. Kawase, K. Mitarai, and K. Fujii,
“Parametric t-stochastic neighbor embedding with quantum neural network” Phys. Rev. Research 4 (4), 043199 (2022). arXiv:2202.04238
L. Erhart, K. Mitarai, W. Mizukami, and K. Fujii,
“Constructing Local Bases for a Deep Variational Quantum Eigensolver for Molecular Systems” Phys. Rev. Applied 18 (6), 064051 (2022). arXiv:2202.08473
S. Hakkaku, Y. Tashima, K. Mitarai, W. Mizukami, and K. Fujii,
“Quantifying Fermionic Nonlinearity of Quantum Circuits” Phys Rev Research 4 (4),043100 (2022). arXiv:2111.14599　
J. Fujisaki, H. Oshima, S. Sato, and K. Fujii,
“Practical and scalable decoder for topological quantum error correction with an Ising machine” Phys. Rev. Research 4 (4), 043086 (2022). arXiv:2203.15304
K. Mizuta, Y. O. Nakagawa, K. Mitarai, and K. Fujii,
“Local variational quantum compilation of a large-scale Hamiltonian dynamics” PRX Quantum 3 (4), 040302 (2022). arXiv:2203.15484
K. Mitarai, Y. Suzuki, W. Mizukami, Y. O. Nakagawa, and K. Fujii,
“Quadratic Clifford expansion for efficient benchmarking and initialization of variational quantum algorithms” Phys. Rev. Research 4 (3), 033012 (2022). arXiv:2011.09927
K. Kubo, K. Miyamoto, K. Mitarai, and K. Fujii,
“Pricing multi-asset derivatives by variational quantum algorithms” arXiv:2207.01277
F. Kobayashi, K. Mitarai, and K. Fujii,
“Parent Hamiltonian as a benchmark problem for variational quantum eigensolvers” Physical Review A 105 (5), 052415 (2022). arXiv:2109.11759