Search

We have performed differential scanning calorimetric and synchrotron x-ray diffraction studies to elucidate the nature of vapor-deposited ultrastable phenolphthalein glass. As a result, we found that phenolphthalein forms the ultrastable glass by depositing at 313 K, which is about 0.86 times the ordinal glass transition temperature of 361 K. As previous ultrastable glass studies reported, this ultrastable state involved an anisotropic structure. In addition, we found that a large endotherm (sub-$T_\mathrm{g}$ endotherm) was observed in the temperature range between deposition and ordinal glass transition temperatures. We have assessed the stability of deposited states thermodynamically and found that those states are much more stable than those crystalline states when the deposition rate is small enough. The total enthalpies associated with the sub-$T_\mathrm{g}$ endotherm are roughly proportional to the powers of the inversed thickness of the deposited glass. Despite the thermodynamical evidence, wide-angle x-ray diffraction of the structure associated with the sub-$T_\mathrm{g}$ endotherm was unchanged. Following our findings, we have proposed a scenario in which ultrastable vapor-deposited phenolphthalein glass is rooted in locally superstable structure. Our locally oriented scenario would be universal for forming stable structures in other vapor-deposited glasses., Comment: 36 pages, 14 figures

We demonstrate that the search space of the quadratic assignment problem (QAP), known as an NP-hard combinatorial optimization problem, can be reduced using Grover adaptive search (GAS) with Dicke state operators. To that end, we first revise the traditional quadratic formulation of the QAP into a higher-order formulation, introducing a binary encoding method ordered by a descending Hamming weight, such that the number of terms in the objective function is reduced. We also show that the phase gate in the GAS can be replaced by a rotation gate about the Z axis, simplifying the quantum circuit without any penalty. Algebraic analyses in terms of the number of qubits, quantum gates, and query complexity are performed, which indicate that our proposed approach significantly reduces the search space size, improving convergence performance to the optimal solution compared to the conventional one. Interestingly, it is suggested that the higher-order formulation is effective for problems whose size are powers of two, while the quadratic formulation is more effective for other sizes, indicating that switching between the two formulations can enhance the feasibility of the GAS-solved QAP., Comment: 12 pages, 6 figures

This paper presents a novel approach to Grover adaptive search (GAS) for a combinatorial optimization problem whose objective function involves spin variables. While the GAS algorithm with a conventional design of a quantum dictionary subroutine handles a problem associated with an objective function with binary variables $\{0,1\}$, we reformulate the problem using spin variables $\{+1,-1\}$ to simplify the algorithm. Specifically, we introduce a novel quantum dictionary subroutine that is designed for this spin-based formulation. A key benefit of this approach is the substantial reduction in the number of CNOT gates required to construct the quantum circuit. We theoretically demonstrate that, for certain problems, our proposed approach can reduce the gate complexity from an exponential order to a polynomial order, compared to the conventional binary-based approach. This improvement has the potential to enhance the scalability and efficiency of GAS, particularly in larger quantum computations., Comment: 12 pages, 9 figures

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

Dynamic quantum dots are known to generate very accurate currents and can be used as a source of single electron wavepackets for use in quantum metrology, sensing or information processing. To realise their full technological potential, it is desirable to maximise the frequency of operation to increase the current. However, it has been observed that the mechanism of electron transfer across the quantum dot consistently breaks down for GHz frequencies, and this remains unexplained. Here, we present a novel analysis technique, combined with detailed modelling, to present a mechanism of high frequency breakdown in quantum dots as a rapidly-imparted momentum impulse. Such understanding aids future design and operation protocols, allowing their use in high frequency and real time quantum measurements and technologies., Comment: 8 pages, 3 figures

In this paper, we propose a novel method for interfering frequency-multiplexed photonic quantum states without the use of optical nonlinear effects, and experimentally demonstrate this technique via frequency-domain Hong-Ou-Mandel (HOM) interference. By cascading the generation of quantum states onto arbitrary orthogonal modes, we can induce interference across any desired frequency mode. Following the generation of quantum states onto the frequency modes, performing measurements in independent frequency bands enables the realisation of a frequency-domain linear optical circuit analogous to linear interference in the spatial domain. We successfully demonstrated programmable quantum interference by controlling the spectral mode functions and measurement bases. Our method offers a new approach to harness the full potential of light's temporal-frequency degrees of freedom, providing a path towards scalable and programmable photonic quantum computing architectures without the need for optical nonlinearities or spatial-mode beam splitters., Comment: 11 pages, 10 figures

Place names, or toponyms, play an integral role in human representation and communication of geographic space. In particular, how people relate each toponym with particular locations in geographic space should be indicative of their spatial perception. Here, we make use of an extensive dataset of georeferenced social media posts, retreived from Twitter, to perform a statistical analysis of the geographic distribution of toponyms and uncover the relationship between toponyms and geographic space. We show that the occurrence of toponyms is characterized by spatial inhomogeneity, giving rise to patterns that are distinct from the distribution of common nouns. Using simple models, we quantify the spatial specificity of toponym distributions and identify their core-periphery structures. In particular, we find that toponyms are used with a probability that decays as a power law with distance from the geographic center of their occurrence. Our findings highlight the potential of social media data to explore linguistic patterns in geographic space, paving the way for comprehensive analyses of human spatial representations., Comment: Main text: 13 pages, 7 figures. Supporting information: 5 pages, 5 figures

We investigate the relationship between rigid motions and relative equilibria in the N-body problem on the two-dimensional sphere, S2. We prove that any rigid motion of the N-body system on S2 must be a relative equilibrium. Our approach extends the classical study of rigid body dynamics by Euler and utilizes a rotating frame attached to the particles to derive the corresponding equations of motion. We further show that our results can be extended to the N-body gravitational system in R3. The results are oriented to a broader understanding of the dynamics of N-body systems on curved surfaces and provide a novel perspective on classical results in rigid body dynamics., Comment: 25 pages, 1 figure

GRAMS (Gamma-Ray and AntiMatter Survey) is a next-generation balloon/satellite experiment utilizing a LArTPC (Liquid Argon Time Projection Chamber), to simultaneously target astrophysical observations of cosmic MeV gamma-rays and conduct an indirect dark matter search using antimatter. While LArTPCs are widely used in particle physics experiments, they have never been operated at balloon altitudes. An engineering balloon flight with a small-scale LArTPC (eGRAMS) was conducted on July 27th, 2023, to establish a system for safely operating a LArTPC at balloon altitudes and to obtain cosmic-ray data from the LArTPC. The flight was launched from the Japan Aerospace Exploration Agency's (JAXA) Taiki Aerospace Research Field in Hokkaido, Japan. The total flight duration was 3 hours and 12 minutes, including a level flight of 44 minutes at a maximum altitude of 28.9~km. The flight system was landed on the sea and successfully recovered. The LArTPC was successfully operated throughout the flight, and about 0.5 million events of the cosmic-ray data including muons, protons, and Compton scattering gamma-ray candidates, were collected. This pioneering flight demonstrates the feasibility of operating a LArTPC in high-altitude environments, paving the way for future GRAMS missions and advancing our capabilities in MeV gamma-ray astronomy and dark matter research.

We settle the problem of determining the asymptotic behavior of the parameters of optimal difference systems of sets, or DSSes for short, which were originally introduced for computationally efficient frame synchronization under the presence of additive noise. We prove that the lowest achievable redundancy of a DSS asymptotically attains Levenshtein's lower bound for any alphabet size and relative index, answering the question of Levenshtein posed in 1971. Our proof is probabilistic and gives a linear-time randomized algorithm for constructing asymptotically optimal DSSes with high probability for any alphabet size and information rate. This provides efficient self-synchronizing codes with strong noise resilience. We also point out an application of DSSes to phase detection., Comment: 6 pages, accepted for presentation at the 2023 IEEE International Symposium on Information Theory (ISIT)

Weak superimposed codes are combinatorial structures related closely to generalized cover-free families, superimposed codes, and disjunct matrices in that they are only required to satisfy similar but less stringent conditions. This class of codes may also be seen as a stricter variant of what are known as locally thin families in combinatorics. Originally, weak superimposed codes were introduced in the context of multimedia content protection against illegal distribution of copies under the assumption that a coalition of malicious users may employ the averaging attack with adversarial noise. As in many other kinds of codes in information theory, it is of interest and importance in the study of weak superimposed codes to find the highest achievable rate in the asymptotic regime and give an efficient construction that produces an infinite sequence of codes that achieve it. Here, we prove a tighter lower bound than the sharpest known one on the rate of optimal weak superimposed codes and give a polynomial-time randomized construction algorithm for codes that asymptotically attain our improved bound with high probability. Our probabilistic approach is versatile and applicable to many other related codes and arrays., Comment: 6 pages, accepted for presentation at the 2022 IEEE International Symposium on Information Theory (ISIT)

Angular distributions of the elastic and inelastic deuteron-nucleus scattering off $^{24}$Mg, $^{28}$Si, $^{58}$Ni, $^{90}$Zr, $^{116}$Sn, and $^{208}$Pb have been measured at a beam energy of 98 MeV/nucleon, with the goal of constraining the deuteron optical potential in this kinematical regime, and to extract the reduced transition probabilities for the ground-state transitions to low-lying excited states of these nuclei. Two potential models were used in the analysis of the measured $(d,d)$ and $(d,d')$ data within the optical model and the distorted-wave Born approximation: the phenomenological optical model potential associated with the collective model of nuclear scattering, and the semi-microscopic double-folding model of the deuteron-nucleus potential based on a realistic density-dependent M3Y interaction. The deuteron optical potential and inelastic $(d,d')$ scattering form factors were calculated using these two potential models, allowing for a direct comparison between the potential models as well as the validation of the deduced $E\lambda$ transition rates., Comment: Accepted for publication in Phys. Rev. C

Research in ML4VIS investigates how to use machine learning (ML) techniques to generate visualizations, and the field is rapidly growing with high societal impact. However, as with any computational pipeline that employs ML processes, ML4VIS approaches are susceptible to a range of ML-specific adversarial attacks. These attacks can manipulate visualization generations, causing analysts to be tricked and their judgments to be impaired. Due to a lack of synthesis from both visualization and ML perspectives, this security aspect is largely overlooked by the current ML4VIS literature. To bridge this gap, we investigate the potential vulnerabilities of ML-aided visualizations from adversarial attacks using a holistic lens of both visualization and ML perspectives. We first identify the attack surface (i.e., attack entry points) that is unique in ML-aided visualizations. We then exemplify five different adversarial attacks. These examples highlight the range of possible attacks when considering the attack surface and multiple different adversary capabilities. Our results show that adversaries can induce various attacks, such as creating arbitrary and deceptive visualizations, by systematically identifying input attributes that are influential in ML inferences. Based on our observations of the attack surface characteristics and the attack examples, we underline the importance of comprehensive studies of security issues and defense mechanisms as a call of urgency for the ML4VIS community., Comment: This version of the article has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s12650-024-01029-2

The mechanism of single-charge pumping using a dynamic quantum dot needs to be precisely understood for high-accuracy and universal operation toward applications to quantum current standards and quantum information devices. The type of charge carrier (electron or hole) is an important factor for determining the pumping accuracy, but it has been so far compared just using different devices that could have different potential landscapes. Here, we report measurements of a silicon ambipolar single-charge pump. It allows a comparison between the single-electron and single-hole pumps that share the entrance tunnel barrier, which is a critical part of the pumping operation. By changing the frequency and temperature, we reveal that the entrance barrier has a better energy selectivity in the single-hole pumping, leading to a pumping error rate better than that in the single-electron pumping up to 400 MHz. This result implies that the heavy effective mass of holes is related to the superior characteristics in the single-hole pumping, which would be an important finding for stably realizing accurate single-charge pumping operation.

We measured the electrical resistivity and the $^{121}$Sb nuclear quadrupole resonance (NQR) spectra of La$_3$TiSb$_5$, which is a nonmagnetic reference system for a locally noncentrosymmetric antiferromagnet Ce$_3$TiSb$_5$, in order to determine its physical properties. The resistivity exhibited a hump anomaly at 120 K, suggesting a phase transition. The NQR spectra split below 110 K, whereas the nuclear spin-lattice relaxation exhibited no anomalies. These results can be explained by the incommensurate charge-density-wave (CDW) transition. This finding suggests the importance of quasi-one-dimensional characteristics and CDW instability in these systems., Comment: 6 pages, 6 figures

We present an analysis of a stellar occultation event caused by a near-Earth asteroid (98943) 2001 CC21, an upcoming flyby target in the Hayabusa2 extended mission, on March 5, 2023. To accurately determine the asteroid's shape from diffraction-affected light curves, we developed a novel data reduction technique named the Diffracted Occultation's United Simulator for Highly Informative Transient Explorations (DOUSHITE). Using DOUSHITE-generated synthetic models, we derived constraints on (98943) 2001 CC21's shadow shape from the single-chord occultation data. Our results suggest a significant elongation of the shadow with an axis ratio of $b/a = 0.37\pm0.09$. This shape can be crucial for planning Hayabusa2's high-speed flyby to optimise the limited imaging opportunities., Comment: 10 pages, 9 figures, PASJ accepted

With the release of large-scale motion datasets with textual annotations, the task of establishing a robust latent space for language and 3D human motion has recently witnessed a surge of interest. Methods have been proposed to convert human motion and texts into features to achieve accurate correspondence between them. Despite these efforts to align language and motion representations, we claim that the temporal element is often overlooked, especially for compound actions, resulting in chronological inaccuracies. To shed light on the temporal alignment in motion-language latent spaces, we propose Chronologically Accurate Retrieval (CAR) to evaluate the chronological understanding of the models. We decompose textual descriptions into events, and prepare negative text samples by shuffling the order of events in compound action descriptions. We then design a simple task for motion-language models to retrieve the more likely text from the ground truth and its chronologically shuffled version. CAR reveals many cases where current motion-language models fail to distinguish the event chronology of human motion, despite their impressive performance in terms of conventional evaluation metrics. To achieve better temporal alignment between text and motion, we further propose to use these texts with shuffled sequence of events as negative samples during training to reinforce the motion-language models. We conduct experiments on text-motion retrieval and text-to-motion generation using the reinforced motion-language models, which demonstrate improved performance over conventional approaches, indicating the necessity to consider temporal elements in motion-language alignment., Comment: To appear at ECCV 2024. Project page: https://kfworks.com/CAR-WP/

The strength distributions of the Isoscalar Giant Monopole Resonance (ISGMR) and Isoscalar Giant Quadrupole Resonance (ISGQR) in 142,146-150Nd have been determined via inelastic alpha-particle scattering with the Grand Raiden (GR) Spectrometer at the Research Center for Nuclear Physics (RCNP), Japan. In the deformed nuclei 146-150Nd, the ISGMR strength distributions exhibit a splitting into two components, while the nearly spherical nucleus 142Nd displays a single peak in the ISGMR strength distribution. A noteworthy achievement in this study is the first-time detection of overtones in the Isoscalar Giant Quadrupole Resonance (ISGQR) strength distributions within Nd isotopes at an excitation energy around 25 MeV obtained through Multipole Decomposition Analysis (MDA)., Comment: Accepted for publication in Physics Letters B

This paper will examine the cognitive processes involved in palpation in order to develop an appropriate remote palpation system. In a conventional remote palpation system, the tactile condition of the patient is conveyed to the doctors using a force feedback system. A clarification of the cognitive process during palpation suggests that the purpose of palpation is to formulate a clear idea about the patient's medical problems using the tactile sensation as a trigger to combine the results of other assessments, past experience and memory, and patient reactions to the doctor's touch. This is in contrast to the objective of acquiring the detailed tactile condition of the affected body part. In order to demonstrate this purpose, we will describe the two significant signal pathways for the perception of tactile sensation, both in doctors and patients. The perception of doctors progresses as the result of active touch to the affected part, thereby implying that the simultaneous stimulation of kinaesthetic and tactile sensation is necessary. Conversely, the tactile sensation experienced by patients is the result of passive touch, which evokes a more subjective and emotional response. Patients both explicitly and implicitly perceive the stimulation, and doctors use these perceptions as reactions of the pain to the doctors' touch. This paper proposes the fundamental concept of a remote palpation system, ``Palpation Reality beyond Real'', to achieve the purpose of palpation. Palpation reality implies a system in which the whole cognitive process progresses at the same level or better than palpation in the standard examination, rather than presenting the real tactile sensation.

We propose a scar model to reproduce how double-strand breaks occur in the telomeric DNA damaged by the effect of the $\beta$-decay of tritium to helium. In this scar model, the two hydrogens bonded to the 5$^\prime$ carbon connecting the pent saccharides and phosphate are removed. Molecular dynamics simulations using the reactive force field are carried out for 10 cases for the telomeric DNA consisting of 16 base pairs (32 nucleotides). It results in double-strand breaks (DSBs) being observed for structures with more than 24 scars. For 16 scar cases, only single-strand breaks (SSB) are observed. Moreover, in the case of $\left\{16, 0 \right\}$ and $\left\{ 0, 16 \right\},$ where only one of the strands had scars, SSB occurs only in the scarred strand. Secondly, in the $\left\{16, 8 \right\}$ and $\left\{ 8, 16 \right\}$ cases, DSBs occurs. Therefore, we conclude that the following conditions are necessary for DSBs:(i) Scars must occur on both the L and R strands. (ii) A large number of scars (24 or more) must occur in close proximity to each other.

We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array surface detector by comparing it to the Large Scale Structure of the local Universe. In the case of negligible extra-galactic magnetic fields the results are consistent with a relatively heavy injected composition at E ~ 10 EeV that becomes lighter up to E ~ 100 EeV, while the composition at E > 100 EeV is very heavy. The latter is true even in the presence of highest experimentally allowed extra-galactic magnetic fields, while the composition at lower energies can be light if a strong EGMF is present. The effect of the uncertainty in the galactic magnetic field on these results is subdominant., Comment: 8 pages, 3 figures, accepted for publication in PRL

We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the Telescope Array experiment (TA) with that calculated in a given putative model of UHECR under the assumption that sources trace the large-scale structure (LSS) of the Universe. As we report in the companion letter, the TA data show large deflections with respect to the LSS which can be explained, assuming small extra-galactic magnetic fields (EGMF), by an intermediate composition changing to a heavy one (iron) in the highest energy bin. Here we show that these results are robust to uncertainties in UHECR injection spectra, the energy scale of the experiment and galactic magnetic fields (GMF). The assumption of weak EGMF, however, strongly affects this interpretation at all but the highest energies E > 100 EeV, where the remarkable isotropy of the data implies a heavy injected composition even in the case of strong EGMF. This result also holds if UHECR sources are as rare as $2 \times 10^{-5}$ Mpc$^{-3}$, that is the conservative lower limit for the source number density., Comment: 18 pages, 11 figures, accepted for publication in PRD

We propose a simple yet effective pipeline for stylizing a 3D scene, harnessing the power of 2D image diffusion models. Given a NeRF model reconstructed from a set of multi-view images, we perform 3D style transfer by refining the source NeRF model using stylized images generated by a style-aligned image-to-image diffusion model. Given a target style prompt, we first generate perceptually similar multi-view images by leveraging a depth-conditioned diffusion model with an attention-sharing mechanism. Next, based on the stylized multi-view images, we propose to guide the style transfer process with the sliced Wasserstein loss based on the feature maps extracted from a pre-trained CNN model. Our pipeline consists of decoupled steps, allowing users to test various prompt ideas and preview the stylized 3D result before proceeding to the NeRF fine-tuning stage. We demonstrate that our method can transfer diverse artistic styles to real-world 3D scenes with competitive quality. Result videos are also available on our project page: https://haruolabs.github.io/style-n2n/, Comment: 16 pages, 9 figures

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We propose a meta-learning method for positive and unlabeled (PU) classification, which improves the performance of binary classifiers obtained from only PU data in unseen target tasks. PU learning is an important problem since PU data naturally arise in real-world applications such as outlier detection and information retrieval. Existing PU learning methods require many PU data, but sufficient data are often unavailable in practice. The proposed method minimizes the test classification risk after the model is adapted to PU data by using related tasks that consist of positive, negative, and unlabeled data. We formulate the adaptation as an estimation problem of the Bayes optimal classifier, which is an optimal classifier to minimize the classification risk. The proposed method embeds each instance into a task-specific space using neural networks. With the embedded PU data, the Bayes optimal classifier is estimated through density-ratio estimation of PU densities, whose solution is obtained as a closed-form solution. The closed-form solution enables us to efficiently and effectively minimize the test classification risk. We empirically show that the proposed method outperforms existing methods with one synthetic and three real-world datasets., Comment: 21 pages

A beam profile monitor (BPM) has been developed to measure photon beams at the BM4 beamline of the Mikamine site, Research Center for Accelerator and Radioisotope Science (RARIS-Mikamine; previously known as ELPH) at Tohoku University. The BPM comprises plastic scintillation fibers and SiPMs, enabling high-precision, real-time measurements of photon beams in the 1 GeV region. Data acquisition utilized streaming TDC, a firmware commonly employed in the J-PARC Hadron-hall, enabling real-time detection of high-intensity photon beams with count rates reaching several tens of MHz. With sufficient statistical data, the BPM achieved a 1 s beam-profiling accuracy of 10 {\mu}m. The proposed BPM serves as a valuable resource for future physics experiments at the BM4 photon beamline and will contribute significantly to ongoing accelerator research endeavors.

We study the evolution of primordial magnetic fields until the recombination epoch, which is constrained by the conservation of magnetic helicity density if they are maximally helical and by the Hosking integral if they are non-helical. We combine these constraints with conditions obtained by estimating time scales of energy dissipation processes to describe the evolution of magnetic field strength and magnetic coherence length analytically. The dissipation processes depend on whether magnetic or kinetic energy is dominant, whether the decay dynamics is linear or not, and whether the dominant dissipation term is shear viscosity or drag force. We apply the description to compare constraints on primordial magnetic fields at different epochs in the early universe and argue that magnetogenesis before the electroweak symmetry breaking is not feasible., Comment: 59 pages, 13 figures, 4 tables

To build a cross-modal latent space between 3D human motion and language, acquiring large-scale and high-quality human motion data is crucial. However, unlike the abundance of image data, the scarcity of motion data has limited the performance of existing motion-language models. To counter this, we introduce "motion patches", a new representation of motion sequences, and propose using Vision Transformers (ViT) as motion encoders via transfer learning, aiming to extract useful knowledge from the image domain and apply it to the motion domain. These motion patches, created by dividing and sorting skeleton joints based on body parts in motion sequences, are robust to varying skeleton structures, and can be regarded as color image patches in ViT. We find that transfer learning with pre-trained weights of ViT obtained through training with 2D image data can boost the performance of motion analysis, presenting a promising direction for addressing the issue of limited motion data. Our extensive experiments show that the proposed motion patches, used jointly with ViT, achieve state-of-the-art performance in the benchmarks of text-to-motion retrieval, and other novel challenging tasks, such as cross-skeleton recognition, zero-shot motion classification, and human interaction recognition, which are currently impeded by the lack of data., Comment: Accepted to CVPR 2024, Project website: https://yu1ut.com/MotionPatches-HP/

The ground structure can substantially influence seismic ground motion underscoring the need to develop a ground structure model with sufficient reliability in terms of ground motion estimation for earthquake damage mitigation. While many methods for generating ground structure models have been proposed and used in practice, there remains room for enhancing their reliability. In this study, amid many candidate 3D ground structure models generated from geotechnical engineering knowledge, we propose a method for selecting a credible 3D ground structure model capable of reproducing observed earthquake ground motion, utilizing seismic ground motion data solely observed at the ground surface and employing 3D seismic ground motion analysis. Through a numerical experiment, we illustrate the efficacy of this approach. By conducting $10^2$-$10^3$ cases of fast 3D seismic wave propagation analyses using graphic processing units (GPUs), we demonstrate that a credible 3D ground structure model is selected according to the quantity of seismic motion information. We show the effectiveness of the proposed method by showing that the accuracy of seismic motions using ground structure models that were selected from the pool of candidate models is higher than that using ground structure models that were not selected from the pool of candidate models., Comment: 16 pages, 10 figures, accepted for IHPCES/ICCS 2024 (14th International Workshop on Advances in High-Performance Computational Earth Sciences: NumericalMethods, Frameworks & Applications / 24th International Conference on Computational Science)

Hierarchically modular organization is a canonical network topology that is evolutionarily conserved in the nervous systems of animals. Within the network, neurons form directional connections defined by the growth of their axonal terminals. However, this topology is dissimilar to the network formed by dissociated neurons in culture because they form randomly connected networks on homogeneous substrates. In this study, we fabricated microfluidic devices to reconstitute hierarchically modular neuronal networks in culture (in vitro) and investigated how non-random structures, such as directional connectivity between modules, affect global network dynamics. Embedding directional connections in a pseudo-feedforward manner suppressed excessive synchrony in cultured neuronal networks and enhanced the integration-segregation balance. Modeling the behavior of biological neuronal networks using spiking neural networks (SNNs) further revealed that modularity and directionality cooperate to shape such network dynamics. Finally, we demonstrate that for a given network topology, the statistics of network dynamics, such as global network activation, correlation coefficient, and functional complexity, can be analytically predicted based on eigendecomposition of the transition matrix in the state-transition model. Hence, the integration of bioengineering and cell culture technologies enables us not only to reconstitute complex network circuitry in the nervous system but also to understand the structure-function relationships in biological neuronal networks by bridging theoretical modeling with in vitro experiments., Comment: 42 pages, 5 figures, 8 supplementary figures, 2 supplementary tables

We present Ir $4f$ core-level hard-x-ray photoemission spectroscopy (HAXPES) experiments conducted across antiferromagnetic (AFM) ordering transition in Ruddlesden-Popper iridates Sr$_2$IrO$_4$ and Sr$_3$Ir$_2$O$_7$. The Ir $4f$ spectra exhibit distinct changes between the AFM and paramagnetic (PM) phases, with the spectral difference $I_\text{PM}-I_\text{AFM}$ showing a contrasting behavior in the two compounds. By employing computational simulations using the local-density approximation combined with the dynamical mean-field theory method, we elucidate that $I_\text{PM}-I_\text{AFM}$ primary reflects the Slater or Mott-Hubbard character of the AFM insulating state rather than material specific details. This sensitivity to fine low-energy electronic structure arises from the dependence of charge-transfer responses to the sudden creation of a localized core hole on both metal-insulator transitions and long-range AFM ordering. Our result broadens the applications of core-level HAXPES as a tool for characterization of electronic structure., Comment: Main: 7 pages, 3 figures ; SM: 4 pages, 4 figures

We study the effect of the magnon-magnon interaction on the nonlinear magnon transport. The magnon-magnon interaction induces nonreciprocal magnon decay when the time-reversal symmetry is broken, and leads to nonlinear thermal responses of magnons. We construct a theoretical framework to study the nonlinear thermal responses due to the nonreciprocal magnon decay by using the imaginary Dyson equation and quantum kinetic theory, which is then applied to a model of honeycomb ferromagnets with Dzyaloshinskii-Moriya interactions. An order estimate shows that the nonlinear thermal response from the present mechanism is feasible for experimental measurement., Comment: 7 pages, 5 figures

We conducted measurements of $K^- + {^3{\rm He}} \to \pi \!Y \!N + N'$ reactions using a $1~{\rm GeV}/c$ $K^-$-beam, with the objective of understanding the broad decay width of $\bar{K} \!N \!N$ (approximately twice as broad as that of $\Lambda(1405)$ considered to be the $\bar{K} \!N$ quasi-bound state). We successfully reproduced distributions of the $\pi \! Y \! N$ invariant mass and momentum transfer for $\pi \! Y \! N$ using model fitting functions for $\bar{K} \!N \!N$ formation and quasi-free $\bar{K}$ absorption (${\rm QF}_{\bar{K}-{\rm abs}}$) processes. The model can describe the experimental data quite well, and four $\bar{K} \! N \! N \to \pi \! Y \! N $ cross-sections were obtained. The results indicate that mesonic decay is the dominant decay branch of $\bar{K} \! N \! N$. The results also suggest that $\Gamma_{\pi \Lambda N} \sim \Gamma_{\pi \Sigma N}$, which indicates that the $I_{\bar{K} \! N}=1$ absorption channel, in addition to the $I_{\bar{K} \! N}=0$ absorption channel, substantially contribute to the $\bar{K} \! N \! N$ decay, making the $\bar{K} \! N \! N$ state approximately twice as unstable as $\Lambda$(1405).

The quantum cellular automata (QCA) effect is a transition in which multiple electron move coordinately by Coulomb interactions and observed in multiple quantum dots. This effect will be useful for realizing and improving quantum cellular automata and information transfer using multiple electron transfer. In this paper, we investigate the real-time dynamics of the QCA charge transitions in a triple quantum dot by using fast charge-state readout realized by rf reflectometry. We observe real-time charge transitions and analyze the tunneling rate comparing with the first-order tunneling processes. We also measure the gate voltage dependence of the QCA transition and show that it can be controlled by the voltage., Comment: 11pages, 4 figures

The interpolation method for mean field spin glass models developed by Guerra and Talagrand is extended to a quantum mean field spin glass model. This extension enables us to obtain both replica-symmetric (RS) and one step replica-symmetry breaking (1RSB) solutions of the free energy density in the transverse field Sherrington-Kirkpatrick model. It is shown that the RS solution is exact in the paramagnetic phase. We provide a sufficient condition on coupling constants where the 1RSB solution gives better bound than the RS one. This condition reduced to physical quantities in disordered single spin systems allows a simple computer-assisted proof for the existence of the de Almeida-Thouless-type instability., Comment: 12 pages