Search

In recent years, the lack of successors for traditional skills has become an issue. To solve this problem, we propose a skill transfer system that presents tactile information in spatial tasks as a color map on an AR space. We believe that providing the operator with feedback of the force and tactile information during the work is useful for learning skills that require time to master. Furthermore, by following the operator's hand and presenting tactile information, we expect to accelerate the learning of skills by not only presenting tactile information as a physical sensation, but also by making the operator associate tactile information with position., Comment: Part of proceedings of 6th International Conference AsiaHaptics 2024

The quantum error-correcting code in the continuous-variable (CV) system attracts much attention due to its flexibility and high resistance against specific noise. However, the theory of fault tolerance in CV systems is premature and lacks the general strategy to translate the noise in CV systems into the noise in logical qubits, leading to severe restrictions on the correctable noise models. In this paper, we show that the Markovian-type noise in CV systems is translated into the Markovian-type noise in the logical qubits through the Gottesman-Kitaev-Preskill code with an explicit bound on the noise strength. Combined with the established threshold theorem of the concatenated code against Markovian-type noise, we show that CV quantum computation has a fault-tolerant threshold against general Markovian-type noise, closing the existing crucial gap in CV quantum computation. We also give a new insight into the fact that careful management of the energy of the state is required to achieve fault tolerance in the CV system., Comment: 12 pages with 4 figures for main text, 34 pages with 1 figure for supplementary information

We present X-ray observations of the upper atmospheric density disturbance caused by the explosive eruption of the Hunga Tonga-Hunga Ha'apai (HTHH) volcano on 15 January 2022. From 14 January to 16 January, the Chinese X-ray astronomy satellite, Insight-HXMT, was observing the supernova remnant Cassiopeia A. The X-ray data obtained during Earth's atmospheric occultations allowed us to measure neutral densities in the altitude range of ~90-150 km. The density profiles above 110 km altitude obtained before the major eruption are in reasonable agreement with expectations by both GAIA and NRLMSIS 2.0 models. In contrast, after the HTHH eruption, a severe density depletion was found up to ~1,000 km away from the epicenter, and a relatively weak depletion extending up to ~7,000 km for over 8 hr after the eruption. In addition, density profiles showed wavy structures with a typical length scale of either ~20 km (vertical) or ~1,000 km (horizontal). This may be caused by Lamb waves or gravity waves triggered by the volcanic eruption., Comment: 14 pages, 4 figures, accepted for publication in Geophysical Research Letters

We report a significant enhancement of superconducting transition temperature ($\textit{T}_\textrm{c}$) of transition metal dichalcogenide (TMD) superconductor $\textrm{NbTe}_2$ from 0.56 K to 2.8 K. Detailed x-ray structure analysis reveals that our $\textit{T}_\textrm{c}$-enhanced sample has an anisotropic lattice distortion inducing ~1% expansion of the unit cell volume and multi-domain formation in the $\textit{ab}$ planes. Despite the unit cell expansion, the distorted 1T structure, closely related to the charge density wave (CDW) order in this material, persists. Hall measurements show almost identical behaviors for both samples indicating that electronic structure does not change much due to the unit cell expansion. These results suggest that the CDW still coexists with the enhanced superconductivity unlike the other TMD superconductors.

We prove the second adjointness in the setting of the categorical local Langlands correspondence. Moreover, we study the relation between Eisenstein series and cuspidal supports and present a conjectural characterization of irreducible smooth representations with supercuspidal $L$-parameters regarding geometric constant terms. The main technical ingredient is an induction principle for geometric Eisenstein series which allows us to reduce to the situations already treated in the literature., Comment: 22 pages

High-rate quantum error correcting codes mitigate the imposing scale of fault-tolerant quantum computers but require the efficient generation of non-local many-body entanglement. We provide a linear-optical architecture with these properties, compatible with arbitrary codes and Gottesman-Kitaev-Preskill qubits on generic lattices, and featuring a natural way to leverage physical noise bias. Simulations involving hyperbolic surface codes, promising quantum low-density parity-check codes, reveal a threshold comparable to the 2D surface code at about a ten-fold improvement in encoding rate., Comment: 20 pages, 4 figures, comments welcome

GaN is expected to be a key material for next-generation electronics due to its interesting properties. However, the current collapse poses a challenge to the application of GaN FETs to electronic devices. In this study, we investigate the formation of quantum dots in GaN FETs under the current collapse. By comparing the Coulomb diamond between standard measurements and those under current collapse, we find that the gate capacitance is significantly decreased by the current collapse. This suggests that the current collapse changes the distribution of trapped electrons at the device surface, which is reported in the previous study by operando X-ray spectroscopy. Also, we show external control of quantum dot formation, previously challenging in an FET structure, by using current collapse., Comment: 11 pages, 4 figures

The upper atmosphere at the altitude of 60-110 km, the mesosphere and lower thermosphere (MLT), has the least observational data of all atmospheres due to the difficulties of in-situ observations. Previous studies demonstrated that atmospheric occultation of cosmic X-ray sources is an effective technique to investigate the MLT. Aiming to measure the atmospheric density of the MLT continuously, we are developing an X-ray camera, "Soipix for observing Upper atmosphere as Iss experiment Mission (SUIM)", dedicated to atmospheric observations. SUIM will be installed on the exposed area of the International Space Station (ISS) and face the ram direction of the ISS to point toward the Earth rim. Observing the cosmic X-ray background (CXB) transmitted through the atmosphere, we will measure the absorption column density via spectroscopy and thus obtain the density of the upper atmosphere. The X-ray camera is composed of a slit collimator and two X-ray SOI-CMOS pixel sensors (SOIPIX), and will stand on its own and make observations, controlled by a CPU-embedded FPGA "Zynq". We plan to install the SUIM payload on the ISS in 2025 during the solar maximum. In this paper, we report the overview and the development status of this project., Comment: 5 pages, 2 figures, Proceedings of SPIE Astronomical Telescopes and Instrumentation 2024

The decomposition of oceanic flow into its balanced and unbalanced motions carries theoretical and practical significance for the oceanographic community. These two motions have distinct dynamical characteristics and affect the transport of tracers differently from one another. The launch of Surface Water and Ocean Topography (SWOT) satellite provides a prime opportunity to diagnose the surface balanced and unbalanced motions on a global scale at an unprecedented spatial resolution. Here, we apply dynamic-mode decomposition (DMD), a linear-algebraic data-driven method, to a tidally-forced numerical simulation and one-day-repeat SWOT observations of sea-surface height (SSH) in the Gulf Stream extension. DMD is able to separate out the spatial modes associated with sub-inertial periods from super-inertial periods. The sub-inertial modes of DMD can be used to extract geostrophically balanced motions from SSH fields, which have an imprint of internal tides and gravity waves. We utilize the statistical relation between relative vorticity and strain rate as the metric to gauge the extraction of geostrophy.

Successive image generation using cyclic transformations is demonstrated by extending the CycleGAN model to transform images among three different categories. Repeated application of the trained generators produces sequences of images that transition among the different categories. The generated image sequences occupy a more limited region of the image space compared with the original training dataset. Quantitative evaluation using precision and recall metrics indicates that the generated images have high quality but reduced diversity relative to the training dataset. Such successive generation processes are characterized as chaotic dynamics in terms of dynamical system theory. Positive Lyapunov exponents estimated from the generated trajectories confirm the presence of chaotic dynamics, with the Lyapunov dimension of the attractor found to be comparable to the intrinsic dimension of the training data manifold. The results suggest that chaotic dynamics in the image space defined by the deep generative model contribute to the diversity of the generated images, constituting a novel approach for multi-class image generation. This model can be interpreted as an extension of classical associative memory to perform hetero-association among image categories., Comment: submitted to PLOS Complex Systems

Extracting table contents from documents such as scientific papers and financial reports and converting them into a format that can be processed by large language models is an important task in knowledge information processing. End-to-end approaches, which recognize not only table structure but also cell contents, achieved performance comparable to state-of-the-art models using external character recognition systems, and have potential for further improvements. In addition, these models can now recognize long tables with hundreds of cells by introducing local attention. However, the models recognize table structure in one direction from the header to the footer, and cell content recognition is performed independently for each cell, so there is no opportunity to retrieve useful information from the neighbor cells. In this paper, we propose a multi-cell content decoder and bidirectional mutual learning mechanism to improve the end-to-end approach. The effectiveness is demonstrated on two large datasets, and the experimental results show comparable performance to state-of-the-art models, even for long tables with large numbers of cells., Comment: ICDAR 2024

Advanced biological intelligence learns efficiently from an information-rich stream of stimulus information, even when feedback on behaviour quality is sparse or absent. Such learning exploits implicit assumptions about task domains. We refer to such learning as Domain-Adapted Learning (DAL). In contrast, AI learning algorithms rely on explicit externally provided measures of behaviour quality to acquire fit behaviour. This imposes an information bottleneck that precludes learning from diverse non-reward stimulus information, limiting learning efficiency. We consider the question of how biological evolution circumvents this bottleneck to produce DAL. We propose that species first evolve the ability to learn from reward signals, providing inefficient (bottlenecked) but broad adaptivity. From there, integration of non-reward information into the learning process can proceed via gradual accumulation of biases induced by such information on specific task domains. This scenario provides a biologically plausible pathway towards bottleneck-free, domain-adapted learning. Focusing on the second phase of this scenario, we set up a population of NNs with reward-driven learning modelled as Reinforcement Learning (A2C), and allow evolution to improve learning efficiency by integrating non-reward information into the learning process using a neuromodulatory update mechanism. On a navigation task in continuous 2D space, evolved DAL agents show a 300-fold increase in learning speed compared to pure RL agents. Evolution is found to eliminate reliance on reward information altogether, allowing DAL agents to learn from non-reward information exclusively, using local neuromodulation-based connection weight updates only. Code available at github.com/aislab/dal., Comment: Camera ready version. 9 pages, 5 figures

Defects in semiconductors, traditionally seen as detrimental to electronic device performance, have emerged as potential assets in quantum technologies due to their unique quantum properties. This study investigates the interaction between defects and quantum electron transport in GaN/AlGaN field-effect transistors, highlighting the observation of Fano resonances at low temperatures. We observe the resonance spectra and their dependence on gate voltage and magnetic fields. To explain the observed behavior, we construct the possible scenario as a Fano interferometer with finite width. Our findings reveal the potential of semiconductor defects to contribute to the development of quantum information processing, providing their role to key components in next-generation quantum devices., Comment: 14 pages, 6 figures

We developed new concentration inequalities for a quantum state on an $N$-qudit system or measurement outcomes on it that apply to an adversarial setup, where an adversary prepares the quantum state. Our one-sided concentration inequalities for a quantum state require the $N$-qudit system to be permutation invariant and are thus de-Finetti type, but they are tighter than the one previously obtained. We show that the bound can further be tightened if each qudit system has an additional symmetry. Furthermore, our concentration inequality for the outcomes of independent and identical measurements on an $N$-qudit quantum system has no assumption on the adversarial quantum state and is much tighter than the conventional one obtained through Azuma's inequality. We numerically demonstrate the tightness of our bounds in simple quantum information processing tasks., Comment: 29 pages, 4 figures, published version

We consider the flat moduli space of parahoric level structures on a local shtuka and show that it is representable over a smooth $p$-adic formal scheme by establishing the dilatation theory of $v$-sheaves. We apply this result to the canonical integral model of a Shimura variety at hyperspecial level and identify the flat moduli space of parahoric level structures with the canonical integral model at the corresponding parahoric level. We prove a similar result for integral models of local Shimura varieties., Comment: 17 pages

[Purpose] To develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensemble learning. [Methods] A total of 218 pregnant women with suspected placental anomalies who underwent magnetic resonance imaging (MRI) were enrolled, yielding 1090 annotated images for developing a deep learning model for placental segmentation. The images were standardized and divided into training and test sets. The performance of PlaNet-S, which integrates U-Net and SegNeXt within an ensemble framework, was assessed using Intersection over Union (IoU) and counting connected components (CCC) against the U-Net model. [Results] PlaNet-S had significantly higher IoU (0.73 +/- 0.13) than that of U-Net (0.78 +/- 0.010) (p<0.01). The CCC for PlaNet-S was significantly higher than that for U-Net (p<0.01), matching the ground truth in 86.0\% and 56.7\% of the cases, respectively. [Conclusion]PlaNet-S performed better than the traditional U-Net in placental segmentation tasks. This model addresses the challenges of time-consuming physician-assisted manual segmentation and offers the potential for diverse applications in placental imaging analyses., Comment: 11 pages, 5 figures, Shinnosuke Yamamoto and Isso Saito equally contributed to this work. In the original submission, there was a typographical error in the reported standard deviation for the Intersection over Union (IoU) values of the PlaNet-S model. The standard deviation was incorrectly listed as 0.01 instead of the correct value of 0.1. This has been corrected in the revised version

Spin-orbit coupling (SOC) of light plays a fundamental photophysics that is important for various fields such as materials science, optics, and quantum technology, contributing to the elucidation of new physical phenomena and the development of innovative applications. In this study, we investigate the impact of SOC in a microcavity system using the highly oriented molecular crystal. The unique molecular alignment of our crystal creates substantial optical anisotropy, enabling the observation of significant SOC effects within a microcavity form. Through angle-resolved photoluminescence measurements and theoretical calculations, the presence of Rashba-Dresselhaus (RD) SOC in the lower branch of polariton modes is revealed. We have observed for the first time polarization-coupled emission from polariton modes due to the RD-SOC effect in a microcavity with a medium having both strong light-matter coupling and strong optical anisotropy. Theoretical investigations further elucidate the intricate interplay between the RD-SOC effect and anisotropic light-matter coupling, leading to the emergence of both circularly and diagonally polarized mode splittings. This study not only advances our understanding of optical SOC in microcavities but also highlights the potential of highly oriented molecular crystals in manipulating SOC effects without external electric or magnetic fields. These findings offer greatly promising platforms for developing topological photonics and quantum technologies.

This paper aims to shed light on the evolutionary dynamics of diverse and social populations by introducing the rich expressiveness of generative models into the trait expression of social agent-based evolutionary models. Specifically, we focus on the evolution of personality traits in the context of a game-theoretic relationship as a situation in which inter-individual interests exert strong selection pressures. We construct an agent model in which linguistic descriptions of personality traits related to cooperative behavior are used as genes. The deterministic strategies extracted from Large Language Model (LLM) that make behavioral decisions based on these personality traits are used as behavioral traits. The population is evolved according to selection based on average payoff and mutation of genes by asking LLM to slightly modify the parent gene toward cooperative or selfish. Through preliminary experiments and analyses, we clarify that such a model can indeed exhibit the evolution of cooperative behavior based on the diverse and higher-order representation of personality traits. We also observed the repeated intrusion of cooperative and selfish personality traits through changes in the expression of personality traits, and found that the emerging words in the evolved gene well reflected the behavioral tendency of its personality in terms of their semantics., Comment: 7 pages, 4 figures and 1 table