35 citations · 36 across the 14 of their papers we have counts for
15 papers
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…
QuBridge: Layer-wise Fidelity Decomposition in Quantum Computation Pipeline
Kisho Sotokawa, Hideaki Kawaguchi, Shin Nishio +1
Running a quantum circuit on current hardware involves a sequence of engineering decisions, each with tunable parameters and distinct error characteristics. Existing tools optimize…
Digital Annealer-Assisted CNOT Oriented Quantum Circuit Transpilation with Integrated QUBO Mapping and Routing
Kazuma Watanabe, Hideaki Kawaguchi, Shin Nishio +1
Limited qubit counts and two-qubit gate errors motivate reducing CNOT overhead in noisy intermediate-scale quantum (NISQ) transpilation. In circuit-partitioning workflows, repeated…
Quantum-Enhanced Processing with Tensor-Network Frontends for Privacy-Aware Federated Medical Diagnosis
Hiroshi Yamauchi, Anders Peter Kragh Dalskov, Hideaki Kawaguchi +1
We propose a privacy-aware hybrid framework for federated medical image classification that combines tensor-network representation learning, MPC-secured aggregation, and post-aggre…
Practical Quantum Federated Learning for Privacy-Sensitive Healthcare: Communication Efficiency and Noise Resilience
Suzukaze Kamei, Hideaki Kawaguchi, Takahiko Satoh
AI-driven medical diagnostics increasingly requires collaborative model training across institutions, yet centralizing patient data conflicts with privacy regulations. Federated Le…
Telemetry-Based Server Selection in the Quantum Internet via Cross-Layer Runtime Estimation
Masaki Nagai, Hideaki Kawaguchi, Shin Nishio +1
The Quantum Internet will allow clients to delegate quantum workloads to remote servers over heterogeneous networks, but choosing the server that minimizes end-to-end execution tim…
Dense packing of the surface code: code deformation procedures and hook-error-avoiding gate scheduling
Kohei Fujiu, Shota Nagayama, Shin Nishio +2
The surface code is one of the leading quantum error correction codes for realizing large-scale fault-tolerant quantum computing (FTQC). One major challenge in realizing surface-co…
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…
Extension of Dynamic Network Biomarker using the propensity score method: Simulation of causal effects on variance and correlation coefficient
Satoru Shinoda, Hideaki Kawaguchi
In clinical biomarker studies, the Dynamic Network Biomarker (DNB) is sometimes used. DNB is a composite variable derived from the variance and the Pearson correlation coefficient…
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…
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…
Quantitative Evaluation of Quantum/Classical Neural Network Using a Game Solver Metric
Suzukaze Kamei, Hideaki Kawaguchi, Shin Nishio +1
To evaluate the performance of quantum computing systems relative to classical counterparts and explore the potential, we propose a game-solving benchmark based on Elo ratings in t…
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…
Towards quantum computing for clinical trial design and optimization: A perspective on new opportunities and challenges
Hakan Doga, M. Emre Sahin, Joao Bettencourt-Silva +10
Clinical trials are pivotal in the drug discovery process to determine the safety and efficacy of a drug candidate. The high failure rates of these trials are attributed to deficie…
Estimation of mutual information via quantum kernel method
Yota Maeda, Hideaki Kawaguchi, Hiroyuki Tezuka
Recently, the importance of analysing data and collecting valuable insight efficiently has been increasing in various fields. Estimating mutual information (MI) plays a critical ro…