2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of TokyoJP426 papers
- Nagoya UniversityJP384 papers
- Osaka City UniversityJP368 papers
- High Energy Accelerator Research OrganizationJP366 papers
- National Taiwan UniversityTW365 papers
- The University of SydneyAU365 papers
- Nara Women's UniversityJP362 papers
- Korea UniversityKR361 papers
- Sungkyunkwan UniversityKR361 papers
- Virginia TechUS361 papers
- Tohoku Gakuin UniversityJP358 papers
- Yonsei UniversityKR358 papers
643 papers
Spin--orbit-enhanced correlation sensitivity and anomalous magnetic response in non-dimerized ilmenite CdRuO
Yuya Haraguchi, Hayato Yatsuzuka, Hiroko Aruga Katori
We report the synthesis and physical properties of CdRuO, a nominal Ru ilmenite with edge-sharing RuO honeycomb layers. Powder X-ray diffraction establishes a…
A Search for helium in the atmospheres of three sub-Neptunes and a super-Earth around M-dwarfs
Kiyoe Kawauchi, Norio Narita, Yuichi Ito +26
Thousands of sub-Neptunes have been discovered mainly through space-based surveys such as Kepler and TESS. Their bulk compositions and internal structures are thought to reflect th…
All-valid-state HOBO encoding for constrained combinatorial optimization on NISQ devices
Juncheng Wang, Takumi Kanezashi, Daisuke Tsukayama +5
Continued advancements in quantum computing have stimulated growing interest in translating quantum technologies into real-world applications. Consequently, the investigation of pr…
Development of an electrodynamic balance to study single levitated particles exposed to alkali-metal vapor
Akira Kamada, Borjid Jiyatai, Atsushi Hatakeyama
Electrodynamic balances (EDBs) have been widely used to investigate reactions between levitated particles and background gases. In this paper, we report the development of an EDB t…
Utility of NISQ devices: optimizing experimental parameters for the fabrication of Au atomic junction using gate-based quantum computers
Takumi Kanezashi, Daisuke Tsukayama, Jun-ichi Shirakashi +2
Feedback-controlled electromigration (FCE) enables precise regulation of atomic migration by carefully optimizing multiple experimental parameters. However, manually fine-tuning th…
Evolution of crystal field and intraionic interactions in the ilmenite IrO ( = Mg, Zn, Cd) and hyperhoneycomb -ZnIrO
Yuya Haraguchi, Hiroko Aruga Katori, Kenji Ishii +1
Spin-orbit Mott insulators with the electron configuration are promising platforms for the Kitaev spin liquid, yet fine-tuning of their crystal structures is essential t…
Quantum-inspired Ising machine using sparsified spin connectivity
Moe Shimada, Koki Awaya, Ryoya Yonemoto +2
Combinatorial optimization problems become computationally intractable as these NP-hard problems scale. We previously proposed extraction-type majority voting logic (E-MVL), a quan…
Discontinuous change of viscosity in a sheared granular gas with velocity-dependent restitution
Makoto R. Kikuchi, Yuria Kobayashi, Satoshi Takada
We investigate the rheology of a sheared granular gas composed of hard spheres with a velocity-dependent restitution coefficient. Using kinetic theory, we derive the shear viscosit…
Multi-tasking through quantum annealing
Jargalsaikhan Artag, Koki Awaya, Takumi Kanezashi +3
Quantum annealing approximately solves combinatorial optimization problems by leveraging the principles of adiabatic quantum systems. In this approach, the system's Hamiltonian evo…
Kinetic theory of dilute weakly charged granular gases with hard-core and inverse power-law interactions under uniform shear flow
Yuria Kobayashi, Makoto R. Kikuchi, Shunsuke Iizuka +1
We develop a kinetic-theory framework to investigate the steady rheology of a dilute gas interacting via a repulsive potential under uniform shear flow. Starting from the Boltzmann…
Dissecting Performance Degradation in Audio Source Separation under Sampling Frequency Mismatch
Kanami Imamura, Tomohiko Nakamura, Kohei Yatabe +1
Audio processing methods based on deep neural networks are typically trained at a single sampling frequency (SF). To handle untrained SFs, signal resampling is commonly employed, b…
Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration
Sota Kumazawa, Yasuhiro Yoshida, Tomohiro Nimura +2
The spatiotemporal evolution of pulsating turbulent pipe flow was predicted by deep learning. A convolutional neural network (CNN) and long short-term memory (LSTM) were employed f…
AOAD-MAT: Transformer-based multi-agent deep reinforcement learning model considering agents' order of action decisions
Shota Takayama, Katsuhide Fujita
Multi-agent reinforcement learning focuses on training the behaviors of multiple learning agents that coexist in a shared environment. Recently, MARL models, such as the Multi-Agen…
Single-Rod Brachiation Robot: Mechatronic Control Design and Validation of Prejump Phases
Juraj Lieskovský, Hijiri Akahane, Aoto Osawa +3
A complete mechatronic design of a minimal configuration brachiation robot is presented. The robot consists of a single rigid rod with gripper mechanisms attached to both ends. The…
SingLEM: Single-Channel Large EEG Model
Jamiyan Sukhbaatar, Satoshi Imamura, Ibuki Inoue +5
Current deep learning models for electroencephalography (EEG) are often task-specific and depend on large labeled datasets, limiting their adaptability. Although EEG foundation mod…
Sibling Sub-Neptunes Around Sibling M Dwarfs: TOI-521 and TOI-912
G. Lacedelli, E. Pallé, R. Luque +47
Sub-Neptunes are absent in the Solar System, yet they are commonly found in our Galaxy. They challenge the internal structure models and prompt investigation on their formation, ev…
Extending flow birefringence analysis to combined extensional-shear flows via Jeffery-Hamel flow measurements
Miu Kobayashi, William Kai Alexander Worby, Misa Kawaguchi +3
This study investigates the relationship between phase retardation and strain rates in combined extensional-shear flows using the Jeffery-Hamel flow formalism, which yields an anal…
Stress Analysis of a Square Elastic Body Under Biaxial Loading Using Airy Stress Functions
Ryu Suzuki, Shintaro Hokada, Satoshi Takada
This study presents an analytical investigation of stress distributions in square-shaped elastic bodies subjected to concentrated compressive loads under uniaxial and biaxial condi…
Proposal for fast computational method for Hertzian contact theory
Shintaro Hokada, Shunsuke Iizuka, Satoshi Takada
Fast computational method for Hertzian contact theory is proposed. An incremental formula is introduced to calculate the ellipticity of the contact disk when two elastic bodies are…
Crystalline water intercalation into the Kitaev honeycomb cobaltate NaCoTeO
Masaaki Ito, Yuya Haraguchi, Teruki Motohashi +4
We herein report the successful intercalation of water molecules into the layered honeycomb lattice of NaCoTeO, a Kitaev-candidate compound, to obtain the hydrated phas…
Solvable Tuple Patterns and Their Applications to Program Verification
Naoki Kobayashi, Ryosuke Sato, Ayumi Shinohara +1
Despite the recent progress of automated program verification techniques, fully automated verification of programs manipulating recursive data structures remains a challenge. We in…
Observation of Uniform Supercurrent Flow in Polycrystalline K-doped Ba122 by Combined Magneto-optical Imaging and Finite-element Modeling
Shota Ishiwata, Sunseng Pyon, Tsuyoshi Tamegai +2
Macroscopic current uniformity in a (Ba,K)Fe2As2 bulk sample produced by a process that demonstrated high trapped magnetic fields was evaluated through a comparative experimental a…
Frustrated Diamond Lattice Antiferromagnet CoTiO with a Vacancy-ordered Spinel Structure Synthesized via a Topochemical Reaction
Rio Kumeda, Yuya Haraguchi, Daisuke Nishio-Hamane +3
Metastable CoTiO was synthesized through a topochemical reaction using LiCoTiO as the precursor, resulting in a vacancy-ordered spinel structure. Crystal st…
Adaptive Wiping: Adaptive contact-rich manipulation through few-shot imitation learning with Force-Torque feedback and pre-trained object representations
Chikaha Tsuji, Enrique Coronado, Pablo Osorio +1
Imitation learning offers a pathway for robots to perform repetitive tasks, allowing humans to focus on more engaging and meaningful activities. However, challenges arise from the…