Takao Tomono

Scopus Publications

A Quadratic Unconstrained Binary Optimization (QUBO) Model for Elevation-Aware Vehicle Routing: Optimizing Fuel Consumption and Traffic Congestion
Tsubasa Suzuki, Takao Tomono
Advanced Quantum Technologies, 2026
This study formulates a novel, elevation‐aware Quadratic Unconstrained Binary Optimization (QUBO) model for multi‐vehicle route optimization that simultaneously reduces fuel consumption and traffic congestion. Candidate routes are generated using a gradient‐corrected Dijkstra algorithm, and route selection is optimized by minimizing a rigorously constructed QUBO Hamiltonian that incorporates fuel cost, route overlap, and constraint satisfaction. Extensive numerical validation is performed using classical annealing simulations across multiple regions with diverse topographical and road network characteristics, including San Francisco. The results demonstrate that incorporating elevation information significantly reduces fuel consumption, while the proposed overlap penalty effectively mitigates congestion. A clear trade‐off between overlap reduction and fuel efficiency is quantitatively characterized. The mathematical consistency of the formulation is ensured through a theoretically derived penalty coefficient, which guarantees constraint satisfaction and stable optimization behavior. Scaling experiments further reveal the limitations of classical solvers as the number of candidate routes increases, highlighting the importance of robust QUBO formulations and motivating future implementation on quantum processing units. Overall, this work establishes a validated and theoretically sound QUBO framework for sustainable transportation optimization and provides a reliable performance baseline for future quantum hardware–based investigations.
Genetic-multi-initial generalized VQE: Advanced VQE method using genetic algorithms then local search
Hikaru Wakaura, Takao Tomono
International Journal of Quantum Information, 2026
Variational-Quantum-Eigensolver(VQE) method has been known as chemical calculation using quantum computers and classical computers. This method also can derive the energy levels of excited states by Variational-Quantum-Deflation(VQD) method. Although the parameter landscape of the excited state has many local minimums, the results tend to be trapped by them. Therefore, we apply Genetic Algorithms and then Local Search (GA then LS) as the classical optimizer of the VQE method. We calculated ground and excited states and their energies on hydrogen molecules by modifying GA then LS. Here, we used Powell, Broyden–Fletcher–Goldferb–Shanno, Nelder–Mead and Newton’s method as an optimizer of LS. We obtained that Newton’s method can derive ground and excited states of hydrogen and helium hydride molecules and their energies with higher accuracy than others.
The discriminative ability on anomaly detection using quantum kernels for shipping inspection
Takao Tomono, Kazuya Tsujimura
EPJ Quantum Technology, 2025
We aim to use quantum machine learning to detect various anomalies in image inspection by using small size data. Assuming the possibility that the expressive power of the quantum kernel space is superior to that of the classical kernel space, we are studying a quantum machine learning model. Through trials of image inspection processes not only for factory products but also for products including agricultural products, the importance of trials on real data is recognized. In this study, training was carried out on SVMs embedded with various quantum kernels on a small number of agricultural product image data sets collected in the markets. The quantum kernels prepared in this study consisted of a smaller number of rotating gates and control gates. The F1 scores for each quantum kernel showed a significant effect of using CNOT gates. After confirming the results with a quantum simulator, the usefulness of the quantum kernels was confirmed on a quantum computer. Learning with SVMs embedded with specific quantum kernels showed significantly higher values of the AUC compared to classical kernels. The reason for the lack of learning in quantum kernels is considered to be due to kernel concentration or exponential concentration similar to the Baren plateau. The reason why the F1 score does not increase as the number of features increases is suggested to be due to exponential concentration, while at the same time it is possible that only certain features have discriminative ability. Furthermore, it is suggested that controlled Toffoli gate may be a promising quantum kernel component.
FPT-EMS: An FPGA Implementation Using NB-LDPC Code for Continuous-Variable Quantum Key Distribution
Kaijie Wei, Devanshu Garg, Ryutaro Nagai, Takao Tomono, Hideharu Amano
Proceedings of the 15th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies Heart 2025, 2025
The Continuous-Variable Quantum Key Distribution (CV-QKD) is a groundbreaking technology that enables two parties, Alice and Bob, to share secret cryptographic keys with security guaranteed by the fundamental principle of quantum mechanics. The optical signal’s amplitude and phase quadratures are transmitted through a quantum channel and measured by the receiver (Bob). Due to channel noise, loss, and other imperfections, error correction is necessary to ensure both parties share identical raw key bits while minimizing information leakage to potential eavesdroppers (Eve). Non-Binary Low-Density Parity-Check (NB-LDPC) codes are well-suited for CV-QKD because they achieve high reconciliation efficiency, particularly in low-SNR scenarios. However, the intensive computational complexity hinders its further deployment in real-world applications. In this paper, we present an HLS-based decoder system, FPT-EMS (Field-Programmable T-EMS), which consists of six submodules aligning with the construction of the base design, Trellis-Based Extended Min-Sum (T-EMS). After the dedicated design of each submodule considering algorithm properties and FPGA characteristics, we ultimately achieved a 9.36 × speedup compared with ARM cores of the target platform, RFSoC 4x2, at the throughput of 0.89 Mbps over one iteration.
Quantum navigation system considering the fuel consumption due to elevation difference
Tsubasa Suzuki, Takao Tomono
International Conference on Electrical Computer Communications and Mechatronics Engineering Iceccme 2025, 2025
In this study, experiments were conducted to mitigate traffic congestion by applying quantum annealing that takes road elevation changes into account, with the aim of reducing carbon dioxide emissions from automobiles. While similar studies have been widely conducted in the past, few have considered the significant impact of road gradients on carbon dioxide emissions. This study was validated in San Francisco, a city with a diverse elevation distribution and well-developed road networks. The effect of elevation changes was incorporated into the results by converting them into equivalent distances using a correction formula. Driving routes were determined using candidate route extraction based on Dijkstra’s algorithm and a quantum annealing simulator. The validation results showed that this method could reduce carbon dioxide emissions by up to 27% compared to previous methods. Furthermore, when the effects of traffic congestion were included in the carbon dioxide emissions, it was confirmed that the carbon dioxide emissions were minimized when the number of candidate routes extracted by Dijkstra’s algorithm was set to 20. This result indicates that the conditions of Dijkstra’s algorithm are also an important factor. For future work, efforts will focus on improving practicality by optimizing the cost functions and other computation conditions in quantum annealing, as well as expanding the computational model to account for factors such as vehicle weight.
Quantum Kernel Anomaly Detection Using AR-Derived Features from Non-Contact Acoustic Monitoring for Smart Manufacturing
Takao Tomono, Kazuya Tsujimura
Proceedings IEEE Quantum Week 2025 Qce 2025, 2025
The evolution of manufacturing toward Smart Factories has highlighted critical challenges in equipment maintenance, particularly the reliance on numerous contact sensors for anomaly detection, resulting in escalating sensor and computational costs. This study investigates the application of quantum kernels to enhance anomaly detection using non-contact sensors. We hypothesized that quantum computing's expressive power could effectively discriminate among multiple anomaly types using fewer sensors. Our experimental setup involved detecting and classifying anomalies from two distinct manufacturing equipment: a conveyor and a chain belt machine using a single directional microphone positioned at varying distances (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0-3 ~\mathrm{m}$</tex>). Audio data was processed through Autoregressive (AR) models to extract coefficient features, which were then mapped into quantum feature space using quantum kernels for one-class SVM classification. Results demonstrated that quantum kernel implementations maintained near-perfect accuracy and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{F} 1$</tex>-scores (consistently <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{> 0. 9 2}$</tex>) across all distances, while classical approaches showed significant performance degradation beyond the 0 m position. Feature space visualization revealed that quantum kernels effectively separated different anomaly types into distinct quadrants within a two-dimensional representation, enabling not only detection but also classification of multiple equipment failures. Specifically, under the third and fourth features space, conveyor anomalies consistently appeared in the second quadrant, while chain belt anomalies clustered in the fourth quadrant. This study demonstrates that quantum kernel methods enable significant anomaly detection in noisy factory environments using fewer non-contact sensors, representing an important step toward realizing quantum-enhanced smart factories with reduced infrastructure requirements and improved maintenance efficiency.
3D Optical Switch for Quantum Communication
Takao Tomono, Rumiko Yamaguchi
2025 IEEE Photonics Conference IPC 2025 Proceedings, 2025
A novel 3D liquid crystal optical switch is proposed, enabling waveguide formation in planar and vertical directions. Simulation results demonstrate successful light confinement and switching capabilities. Although the speed is slower than other switches, the LCD switch has significant advantages in miniaturization.
Leveraging Quantum Feature Spaces for Industrial Time-Series Anomaly Detection
Takao Tomono, Kazuya Tsujimura
Proceedings 2025 IEEE International Conference on Quantum Artificial Intelligence Qai 2025, 2025
Maintenance of production equipment is vital in modern manufacturing. Traditional anomaly detection methods apply machine learning to vibration data, but their scalability is limited due to sensor complexity and computational constraints. In contrast, human operators often rely on auditory cues and intuition. We propose a quantum kernel-based anomaly detection method using quantum kernels in one-class SVMs to enhance feature expressiveness. Two setups were tested: (1) a miniature car track with mechanical anomalies and (2) an open-belt drive system with artificially induced anomaly sounds. Features were extracted via autoregressive (AR) model coefficients from audio. Results show quantum kernels outperform classical RBF kernels in accuracy and F1-score, particularly for varied anomalies. In one case, quantum kernels achieved sufficient classification performance, suggesting their potential for robust detection in industrial time-series data.
FP-FBEMS: FPGA-Based Optimization of Forward/Backward EMS Decoding for CV-QKD
Kaijie Wei, Devanshu Garg, Ryutaro Nagai, Takao Tomono, Hideharu Amano
Proceedings 2025 IEEE 18th International Symposium on Embedded Multicore Many Core Systems on Chip Mcsoc 2025, 2025
Quantum Key Distribution (QKD) offers unconditional security for symmetric key exchange by leveraging fundamental quantum principles such as the no-cloning theorem and measurement disturbance. In recent years, continuous-variable QKD (CV-QKD) protocols have gained prominence because of their compatibility with standard optical components, higher key rates over short distances, lower cost, and potential for photonic integration. However, their performance deteriorates over long distances due to increased sensitivity to channel loss and noise. To mitigate this, non-binary Low-Density Parity Check (NB-LDPC) codes have emerged as an effective error correction strategy during the reconciliation phase. The Extended Min-Sum (EMS) algorithm is a well-suited decoding technique for NB-LDPC codes over Galois Fields (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{GF}(q)$</tex>). However, its high computational complexity poses significant challenges for real-time deployment. Forward/backward EMS (FB-EMS), a scheduling-optimized variant of EMS, substantially reduces complexity and improves the feasibility of hardware implementation. This paper presents a flexible High-level Synthesis (HLS)-based implementation of FBEMS, accompanied by a comprehensive design space exploration on the Zynq Ultrascale+ RFSoC <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$4 \times 2$</tex> platform. The proposed architecture, FP-FBEMS, achieves a balance between on-chip resource usage and throughput, providing more than 2.48 Mbps over GF(64) with high scalability. Furthermore, our design achieves up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{4 2. 0 3} \boldsymbol{\times}$</tex> higher throughput than a software implementation on the Ryzen Threadripper 3960X. Extensive designspace exploration confirms the system's flexibility, robustness, and state-of-the-art performance.
Tensor Network-Based Continuous Variable Quantum Circuit Optimization for Preparation of GKP State
Ryutaro Nagai, Takao Tomono
Proceedings 2023 IEEE International Conference on Quantum Computing and Engineering Qce 2023, 2023
Tensor networks are highly promising methods for efficiently simulating quantum systems using classical computers. In recent years, the efficiency of tensor networks has been eagerly harnessed to simulate NISQ devices in the era of quantum supremacy. However, as of now, quantum advantage with NISQ devices has not been clearly demonstrated in practical applications. This provide impetus for us to intensify our effort in fault tolerant quantum computation (FTQC). Various physical systems and schemes for FTQC have been proposed, with GKP encoding in bosonic systems being one such example. The preparation of GKP states serves as an important building block for realizing FTQC with the GKP code. We introduce tensor networks for simulating and optimizing the GKP state preparation circuit. It is known that the generation of approximated GKP states is achievable through photon counting and post-selection applied to properly prepared multimode Gaussian states. However, it requires optimization of numerous circuit parameters, which is typically computationally challenging on classical computers due to the involvement of the photon counting measurement process. We attempt to utilize tensor networks for more efficient parameter optimization. Additionally, we explore further efficient approach in terms of tensor network structure. We propose a multi-cutoff dimension approach combined with a tree tensor network structure.
Quantum Kernels for Difficult Visual Discrimination
Takao Tomono, Kazuya Tsujimura, Takumi Godo
Proceedings 2023 IEEE International Conference on Quantum Computing and Engineering Qce 2023, 2023
Performance of quantum kernel on initial learning process
Takao Tomono, Satoko Natsubori
EPJ Quantum Technology, 2022
Proposal of Ultra-thin AR wearable display film using liquid crystal waveguide
Proceedings of the International Display Workshops, 2022
Optimization of non-Gaussian state generation using tensor networks and automatic differentiation
Ryutaro Nagai, Takao Tomono
Proceedings 2022 IEEE International Conference on Quantum Computing and Engineering Qce 2022, 2022
The characteristic of Quantum Kernel in initial learning process
Takao Tomono, Satoko Natsubori
Proceedings 2022 IEEE International Conference on Quantum Computing and Engineering Qce 2022, 2022
Reconstruction of Geometric and Optical Parameters of Non-Planar Objects with Thin Film
Yoshie Kobayashi, Tetsuro Morimoto, Imari Sato, Yasuhiro Mukaigawa, Takao Tomono, Katsushi Ikeuchi
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Simulation of Continuous-Variable Quantum Systems with Tensor Network
Ryutaro Nagai, Takao Tomono, Yuichiro Minato
Proceedings 2021 IEEE International Conference on Quantum Computing and Engineering Qce 2021, 2021
A new way to control the internal structure of microneedles: a case of chitosan lactate
T. Tomono
Materials Today Chemistry, 2019
A new approach for body heat energy harvesting
Takao Tomono
International Journal of Energy Research, 2019
Puncture performance of sharpen microneedles by using inclined contact UV lithography
Takao Tomono
Microsystem Technologies, 2018
Flexible self-sufficient energy system for wearable electronics
Proceedings of the International Display Workshops, 2018
Reconstructing Shapes and Appearances of Thin Film Objects Using RGB Images
Yoshie Kobayashi, Tetsuro Morimoto, Imari Sato, Yasuhiro Mukaigawa, Takao Tomono, Katsushi Ikeuchi
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016
Design consideration of sustainable self-sufficient energy system using ferroelectric material for wearable healthcare
Takao Tomono
International Journal of Energy Research, 2016
Normal and reverse mode light scattering properties in nematic liquid crystal cell using polymer stabilized effect
Rumiko Yamaguchi, Koichiro Goto, Shintaro Sakurai, Likun Xiong, Takao Tomono
Journal of Photopolymer Science and Technology, 2015
Potential of P1 organic crystal for compact SHG green laser
Takao Tomono
Optics and Laser Technology, 2015
Potential of nonlinear optical organic material for green light source in laser projector
Proceedings of the International Display Workshops, 2013
Diffraction efficiency simulation for large off-axis HOEs
Takao Tomono
Proceedings of SPIE the International Society for Optical Engineering, 2003
Autostereoscopic display with eye tracking
Takao Tomono, Kyung Hoon, Yong Soo Ha, Sung-Sik Kim, Jung-Young Son
Proceedings of SPIE the International Society for Optical Engineering, 2002
Spectacle-type wearable display
Takao Tomono
Optics Communications, 2000
Proposal of a near-field optical head using a new solid immersion mirror
Kiichi Ueyanagi, Takao Tomono
Japanese Journal of Applied Physics Part 1 Regular Papers and Short Notes and Review Papers, 2000
Proposal of a near field optical head using a new solid immersion mirror
Proceedings of SPIE the International Society for Optical Engineering, 1999
Relationship among molecular strctures, molecular hyperpolarizabilittes and crystal structures of phenylcyclobutenediones
Takao Tomono, Lyong Sun Pu
Molecular Crystals and Liquid Crystals Science and Technology Section A Molecular Crystals and Liquid Crystals, 1997
Phase-Matching Properties of A P1 Symmetry Crystal, (-)-1-(4-Dimethylaminophenyl)-2-(2-Hydropropylamino) Cyclobutene-3,4-Dione
Takao Tomono, Shinsuke Umegaki, Tomonori Usagawa, Lyong Sun Pu, Keisuke Sasaki
Molecular Crystals and Liquid Crystals Science and Technology Section A Molecular Crystals and Liquid Crystals, 1995
Characterization of a novel nonlinear optical crystal (Dad) containing cyclobutenedione as an electron acceptor
T Tomono, L S Pu, T Kinoshita, K Sasaki, S Umegaki
Journal of Physics D Applied Physics, 1993
Phase-matched second harmonic generations in poled polymer films based on poly (methyl methacrylate) containing a p-aminophenyl-cyclobutenedione moiety as the side chains
Takao Tomono, Yasunari Nishikata, Lyong Sun Pu, Takafumi Sassa, Takeshi Kinoshita, Keisuke Sasaki
Molecular Crystals and Liquid Crystals Science and Technology Section A Molecular Crystals and Liquid Crystals, 1993
Phase-matched second-harmonic generation in poled polymer waveguide based on poly(methylmethacrylate) doped with cyclobutenedione derivative
Molecular Crystals and Liquid Crystals Science and Technology Section B Nonlinear Optics, 1992
Time Dependence of the Molecular Aggregation States of Merocyanine Dye Monolayers at Air/Water Interface
Yutaka UNUMA, Takao TOMONO
Nippon Kagaku Kaishi, 1987

Takao Tomono

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