59 citations · 167 across the 9 of their papers we have counts for
9 papers
Tensor train representations of Greeks for Fourier-based pricing of multi-asset options
Rihito Sakurai, Koichi Miyamoto, Tsuyoshi Okubo
Efficient computation of Greeks for multi-asset options remains a key challenge in quantitative finance. While Monte Carlo (MC) simulation is widely used, it suffers from the large…
Permutation of Tensor-Train Cores for Computing Moments on Stochastic Differential Equations
Kayo Kinjo, Rihito Sakurai, Tatsuya Kishimoto +1
Tensor networks, particularly the tensor train (TT) format, have emerged as powerful tools for high-dimensional computations in physics and computer science. In solving coupled dif…
Adaptive sampling-based optimization of quantics tensor trains for noisy functions: applications to quantum simulations
Kohtaroh Sakaue, Hiroshi Shinaoka, Rihito Sakurai
Tensor cross interpolation (TCI) is a powerful technique for learning a tensor train (TT) by adaptively sampling a target tensor based on an interpolation formula. However, when th…
Learning parameter dependence for Fourier-based option pricing with tensor trains
Rihito Sakurai, Haruto Takahashi, Koichi Miyamoto
A long-standing issue in mathematical finance is the speed-up of option pricing, especially for multi-asset options. A recent study has proposed to use tensor train learning algori…
Compactness of quantics tensor train representations of local imaginary-time propagators
Haruto Takahashi, Rihito Sakurai, Hiroshi Shinaoka
Space-time dependence of imaginary-time propagators, vital for \textit{ab initio} and many-body calculations based on quantum field theories, has been revealed to be compressible u…
Comparative study on compact quantum circuits of hybrid quantum-classical algorithms for quantum impurity models
Rihito Sakurai, Oliver J. Backhouse, George H. Booth +2
Predicting the properties of strongly correlated materials is a significant challenge in condensed matter theory. The widely used dynamical mean-field theory faces difficulty in so…
Multiscale space-time ansatz for correlation functions of quantum systems based on quantics tensor trains
Hiroshi Shinaoka, Markus Wallerberger, Yuta Murakami +4
Correlation functions of quantum systems -- central objects in quantum field theories -- are defined in high-dimensional space-time domains. Their numerical treatment thus suffers…
sparse-ir: optimal compression and sparse sampling of many-body propagators
Markus Wallerberger, Samuel Badr, Shintaro Hoshino +13
We introduce sparse-ir, a collection of libraries to efficiently handle imaginary-time propagators, a central object in finite-temperature quantum many-body calculations. We levera…
Hybrid quantum-classical algorithm for computing imaginary-time correlation functions
Rihito Sakurai, Wataru Mizukami, Hiroshi Shinaoka
Quantitative descriptions of strongly correlated materials pose a considerable challenge in condensed matter physics and chemistry. A promising approach to address this problem is…