21 citations · 49 across the 8 of their papers we have counts for
9 papers
Quantum--classical break-even in electronic dynamics of macrocyclic molecules
Shu Kanno, Kenji Sugisaki, Takashi Imamichi +5
Here we demonstrate quantum--classical break-even for chemical dynamics applications, reaching useful accuracy with a quantum-hardware wall-clock time comparable to that estimated…
Point-group symmetry analysis of many-electron wavefunctions on a quantum computer
Rei Sakuma, Kenji Sugisaki, Shu Kanno +2
A point group is a set of spatial symmetry operations in molecular systems and is an indispensable tool for analyzing molecular orbitals and spectroscopy experiments in chemistry.…
Tensor-based phase difference estimation on time series analysis
Shu Kanno, Kenji Sugisaki, Rei Sakuma +3
We propose a phase-difference estimation algorithm based on the tensor-network circuit compression, leveraging time-evolution data to pursue scalability and higher accuracy on a qu…
Quantum phase estimation based filtering: performance analysis and application to low-energy spectral calculation
Rei Sakuma, Kaito Wada, Shu Kanno +5
Filtering is an important technique in quantum computing used for isolating or enhancing some specific states of quantum many-body systems. In this paper, we analyze the performanc…
Hamiltonian simulation-based quantum-selected configuration interaction for large-scale electronic structure calculations with a quantum computer
Kenji Sugisaki, Shu Kanno, Toshinari Itoko +2
Quantum-selected configuration interaction (QSCI) is an approach for quantum chemical calculations using current quantum computers. In conventional QSCI, Slater determinants used f…
Tensor-based quantum phase difference estimation for large-scale demonstration
Shu Kanno, Kenji Sugisaki, Hajime Nakamura +5
We develop an energy calculation algorithm leveraging quantum phase difference estimation (QPDE) scheme and a tensor-network-based unitary compression method in the preparation of…
Entanglement-assisted phase estimation algorithm for calculating dynamical response functions
Rei Sakuma, Shu Kanno, Kenji Sugisaki +2
Dynamical response functions are fundamental quantities to describe the excited-state properties in quantum many-body systems. Quantum algorithms have been proposed to evaluate the…
Light-cone feature selection for quantum machine learning
Yudai Suzuki, Rei Sakuma, Hideaki Kawaguchi
Feature selection plays an essential role in improving the predictive performance and interpretability of trained models in classical machine learning. On the other hand, the usabi…
Quantum Computed Green's Functions using a Cumulant Expansion of the Lanczos Method
Gabriel Greene-Diniz, David Zsolt Manrique, Kentaro Yamamoto +5
In this paper, we present a quantum computational method to calculate the many-body Green's function matrix in a spin orbital basis. We apply our approach to finite-sized fermionic…