2020年 | 大阪大学基礎工学研究科藤井研究室

R. Suzuki, K. Mitarai, and K. Fujii,
“Computational power of one- and two-dimensional dual-unitary quantum circuits” arXiv:2103.09211
K. Mitarai and K. Fujii,
“Constructing a virtual two-qubit gate by sampling single-qubit operations” New Journal of Physics 23, 023021 (2020). arXiv:1909.07534
K. Mitarai and K. Fujii,
“Overhead for simulating a non-local channel with local channels by quasiprobability sampling” Quantum 5, 388 (2020). arXiv:2006.11174v2
K. Endo, T. Nakamura, K. Fujii, and N. Yamamoto,
“Quantum self-learning Monte Carlo and quantum-inspired Fourier transform sampler ” Phys. Rev. Research 2, 043442 (2020). arXiv:2005.14075
N. Yoshioka, Y. O. Nakagawa, K. Mitarai, and K. Fujii,
“Variational quantum algorithm for nonequilibrium steady states” Phys. Rev. Research 2, 043289 (2020). arXiv:1908.09836
Y. Suzuki, Y. Kawase, Y. Masumura, Y. Hiraga, M. Nakadai, J. Chen, K. M. Nakanishi, K. Mitarai, R. Imai, S. Tamiya, T. Yamamoto, T. Yan, T. Kawakubo, Y. O. Nakagawa, Y. Ibe, Y. Zhang, H. Yamashita, H. Yoshimura, A. Hayashi, and K. Fujii,
“Qulacs: a fast and versatile quantum circuit simulator for research purpose” arXiv:2011.13524
K. M. Nakanishi, K. Fujii, and S. Todo,
“Sequential minimal optimization for quantum-classical hybrid algorithms” Phys. Rev. Research 2, 043158 (2020). arXiv:1903.12166
A. Davaasuren, Y. Suzuki, K. Fujii, and M. Koashi,
“General framework for constructing fast and near-optimal machine-learning-based decoder of the topological stabilizer codes” Phys. Rev. Research 2, 033399 (2020). arXiv:1801.04377
A. Kutvonen, T. Sagawa, and K. Fujii,
“Optimizing a quantum reservoir computer for time series prediction” Scientific Reports 10,14687 (2020). arXiv:1807.03947
K. Mitarai and K. Fujii,
“Overhead of the non-local-to-local channel decomposition by quasiprobability sampling” arXiv:2006.11174
K. Endo, T. Nakamura, K. Fujii, and N. Yamamoto,
“Quantum self-learning Monte Carlo with quantum Fourier transform sampler” arXiv:2005.14075