Publications

Google Scholar

In Preparation

1. R. Sakurai, T. Okubo, S. Todo, Something interesting, in preparation

Preprints

1. R. Sakurai, K. Miyamoto, T. Okubo, Tensor train representations of Greeks for Fourier-based pricing of multi-asset options

Journal articles

1. K. Sakaue, H. Shinaoka, R. Sakurai, Adaptive sampling-based optimization of quantized tensor trains for noisy functions: applications to quantum simulations, SciPost Phys. 19, 038 (2025)

2. K. Kinjo, R. Sakurai, T. Kishimoto, and J. Ohkubo, Permutation of Tensor-Train Cores for Computing moments on Stochastic Differential Equations, J. Phys. Soc. Jpn. 94, 084001 (2025)

3. R. Sakurai, H. Takahashi, K. Miyamoto, Learning parameter dependence for Fourier-based option pricing with tensor trains, Mathematics 2025, 13(11), 1828

4. H. Takahashi, R. Sakurai, and H. Shinaoka, Compactness of quantics tensor train representations of local imaginary-time propagators, SciPost Phys. 18, 007 (2025)

5. R. Sakurai, O. J. Backhouse, G. H. Booth, W. Mizukami, H. Shinaoka, Comparative study on compact quantum circuits of quantum-classical hybrid algorithms for quantum impurity models, Phys. Rev. Research 6, 023110.

6. H. Shinaoka, M. Wallerberger, Y. Murakami, K. Nogaki, R. Sakurai, P. Werner, A. Kauch, Multi-scale space-time ansatz for correlation functions of quantum systems, Phys. Rev. X 13, 021015

7. M. Wallerberger, S. Badr, S. Hoshino, F. Kakizawa, T. Koretsune, Y. Nagai, K. Nogaki, T. Nomoto, H. Mori, J. Otsuki, S. Ozaki, R. Sakurai, C. Vogel, N. Witt, K. Yoshimi, H. Shinaoka, sparse-ir: optimal compression and sparse sampling of many-body propagators, SoftwareX Volume 21, February 2023, 1012661

8. R. Sakurai, W. Mizukami, and H. Shinaoka, Hybrid quantum-classical algorithm for computing imaginary-time correlation function, Phys. Rev. Research 4, 023219 (2022)

Japanese articles

1. 品岡寛, 村上雄太, 野垣康介, 櫻井理人, "Quantics tensor trainに基づく多スケール時空仮説と場の量子論", 物理学会誌「最近の研究から」覧, 2024年2月号(招待あり)