activity
20242026
most citedHardware-efficient quantum annealing with error mitigation via classical shadow

1 citations · 1 across the 9 of their papers we have counts for

collaborators
Showing quant-phShow all

9 papers · 1 filter

quant-ph2026

Experimental Measurement and Theoretical Analysis of Energy Relaxation Rates of an Interacting Two-Qubit System on a D-Wave Quantum Annealer

Yusei Amano, Sorato Suzuki, Hiroki Kuji +3

In D-Wave quantum annealers, various properties of the ground state have been clarified, whereas the correspondence between theory and experiment for energy relaxation rates in mul…

quant-ph2026

Quantum Sensing of Non-Repeatable Events Enhanced by In-Sensor Quantum Reservoir Computing

Daiki Sasaki, Hideaki Kawaguchi, Yuichiro Matsuzaki

High-density nitrogen-vacancy (NV) ensembles in diamond enable sensitive magnetometry. Many quantum-sensing protocols rely on reproducible target fields, allowing repeated measurem…

quant-ph2026

Quantum Error Mitigation Simulates General Non-Hermitian Dynamics

Hiroki Kuji, Suguru Endo, Tetsuro Nikuni +2

While non-Hermitian Hamiltonians enable exotic dynamical phenomena, implementing their nonunitary time evolution on near-term quantum devices remains challenging. We propose a hard…

quant-ph2025

Enhancing the Dynamic Range of Quantum Sensing via Quantum Circuit Learning

Hideaki Kawaguchi, Yuichiro Mori, Takahiko Satoh +1

Quantum metrology is a promising application of quantum technologies, enabling the precise measurement of weak external fields at a local scale. In typical quantum sensing protocol…

quant-ph2025

Identification of Phase Plate Properties Using Photonic Quantum Sensor Networks

Yusuke Machida, Hiroki Kuji, Yuichiro Mori +5

Quantum sensor networks (QSNs) have been widely studied for their potential of precise measurements. While most QSN research has focused on estimating continuous variables, recent…

quant-ph2025

Quantum Circuit Learning Using Non-Integrable System Dynamics

Ryutaro Sato, Yasuhiro Aota, Takaharu Yoishida +4

Quantum machine learning is an approach that aims to improve the performance of machine learning methods by leveraging the properties of quantum computers. In quantum circuit learn…

quant-ph2025★ 1 cited

Hardware-efficient quantum annealing with error mitigation via classical shadow

Takaharu Yoshida, Yuta Shingu, Chihaya Shimada +3

Quantum annealing (QA) is an efficient method for finding the ground-state energy of the problem Hamiltonian. However, in practical implementation, the system suffers from decohere…

quant-ph2024

Robust phase estimation of the ground-state energy without controlled time evolution on a quantum device

Hiroki Kuji, Yuta Shingu, Tetsuro Nikuni +3

Estimating the ground-state energy of Hamiltonians in quantum systems is an important task. In this work, we demonstrate that the ground-state energy can be accurately estimated wi…

quant-ph2024

Characterization and generation of a SQL-beating catlike state through repetitive measurements

Mamiko Tatsuta, Yuichiro Matsuzaki, Hiroki Kuji +2

Sensitivity in metrology without entanglement is limited by the standard quantum limit (SQL). Recent studies have found that the Heisenberg-limited scaling, the ultimate sensitivit…