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We present a detailed study of the MASTER OT J030227.28+191754.5 outburst in 2021-2022, reaching an amplitude of 10.2 mag and a duration of 60 d. The detections of (1) the double-peaked optical emission lines, and (2) the early and ordinary superhumps, established that MASTER OT J030227.28+191754.5 is an extremely energetic WZ Sge-type dwarf nova (DN). Based on the superhump observations, we obtained its orbital period and mass ratio as 0.05986(1) d and 0.063(1), respectively. These are within a typical range of low-mass-ratio DNe. According to the binary parameters derived based on the thermal-tidal instability model, our analyses showed that (1) the standard disk model requires an accretion rate $\simeq$ 10$^{20}$ g s$^{-1}$ to explain its peak optical luminosity and (2) large mass was stored in the disk at the outburst onset. These cannot be explained solely by the impact of its massive ($\gtrsim$ 1.15 M$_\odot$) primary white dwarf implied by Kimura et al. (2023). Instead, we propose that the probable origin of this enormously energetic DN outburst is the even lower quiescence viscosity than other WZ Sge-type DNe. This discussion is qualitatively valid for most possible binary parameter spaces unless the inclination is low ($\lesssim 40^\circ$) enough for the disk to be bright explaining the outburst amplitude. Such low inclinations, however, would not allow detectable amplitude of early superhumps in the current thermal-tidal instability model. The optical spectra at outburst maximum showed the strong emission lines of Balmer, He I, and He II series whose core is narrower than $\sim 800$ km s$^{-1}$. Considering its binary parameters, a Keplerian disk cannot explain this narrow component, but the presumable origin is disk winds., Comment: 23 pages, 13 figures, 2 tables. Accepted by PASJ. Part of the online supplemental information is included

We prove the uniqueness in determining a spatially varying zeroth-order coefficient of a one-dimensional time-fractional diffusion equation by initial value and Cauchy data at one end point of the spatial interval.

Most exoplanets with a few Earth radii are more inflated than bare-rock planets with the same mass, indicating a substantial volatile amount. Neither the origin of the volatiles nor the planet's bulk composition can be constrained from the mass-radius relation alone, and the spectral characterization of their atmospheres is needed to solve this degeneracy. Previous studies showed that chemical interaction between accreted volatile and possible molten rocky surface (i.e., magma ocean) can greatly affects the atmospheric composition. However, a variety in the atmospheric compositions of such planets with different properties remains elusive. In this work, we examine the dependence of atmospheric H, O, and C on planetary parameters (atmospheric thickness, planetary mass, equilibrium temperature, and magma properties such as redox state) assuming nebula gas accretion on an Earth-like core, using an atmosphere-magma chemical equilibrium model. Consistent with previous work, we show that atmospheric $\rm H_{2}O$ fraction on a fully molten rocky interior with an Earth-like redox state is on the order of $10^{-2}$-$10^{-1}$ regardless of other planetary parameters. Despite the solubility difference between H- and C-bearing species, C/H increases only a few times above the nebula value except for atmospheric pressure $\lesssim$1000 bar and $\rm H_{2}O$ fraction $\gtrsim$10\%. This results in a negative O/H-C/O trend and depleted C/O below one-tenth of the nebula gas value under an oxidized atmosphere, which could provide a piece of evidence of rocky interior and endogenic water. We also highlight the importance of constraints on the high-pressure material properties for interpreting the magma-atmospheric interaction of inflated planets., Comment: 30 pages, 15 figures

High-precision displacement control for water-hydraulic artificial muscles is a challenging issue due to its strong hysteresis characteristics that is hard to be modelled precisely, and many control methods have been proposed. Recently, data-driven control methods have attracted much attention because they do not explicitly use mathematical models, making design much easier. In our previous work, we proposed fictitious reference iterative tuning (FRIT)-based model predictive control (FMPC), which combines data-driven and model-based methods for the muscle and showed its effectiveness because it can consider input constraints as well. However, the problem in which control performance strongly depends on prior input-output data remains still unsolved. Adaptive FRIT based on directional forgetting has also been proposed; however, it is difficult to achieve the desired transient performance because it cannot consider input constraints and there are no design parameters that directly determine the control performance, such as MPC. In this study, we propose a novel data-driven adaptive model matching-based controller that combines these methods. Experimental results show that the proposed method could significantly improve the control performance and achieve high robustness against inappropriate initial experimental data , while considering the input constraints in the design phase., Comment: 14 pages, 17 figures

Learning from label proportions (LLP) is a kind of weakly supervised learning that trains an instance-level classifier from label proportions of bags, which consist of sets of instances without using instance labels. A challenge in LLP arises when the number of instances in a bag (bag size) is numerous, making the traditional LLP methods difficult due to GPU memory limitations. This study aims to develop an LLP method capable of learning from bags with large sizes. In our method, smaller bags (mini-bags) are generated by sampling instances from large-sized bags (original bags), and these mini-bags are used in place of the original bags. However, the proportion of a mini-bag is unknown and differs from that of the original bag, leading to overfitting. To address this issue, we propose a perturbation method for the proportion labels of sampled mini-bags to mitigate overfitting to noisy label proportions. This perturbation is added based on the multivariate hypergeometric distribution, which is statistically modeled. Additionally, loss weighting is implemented to reduce the negative impact of proportions sampled from the tail of the distribution. Experimental results demonstrate that the proportion label perturbation and loss weighting achieve classification accuracy comparable to that obtained without sampling. Our codes are available at https://github.com/stainlessnight/LLP-LargeBags., Comment: Accepted at ECAI2024

We study the ODE/IM correspondence between two-dimensional $WA_{r}$/$WD_{r}$-type conformal field theories and the higher-order ordinary differential equations (ODEs) obtained from the affine Toda field theories associated with $A_r^{(1)}/D_r^{(1)}$-type affine Lie algebras. We calculate the period integrals of the WKB solution to the ODE along the Pochhammer contour, where the WKB expansions correspond to the classical conserved currents of the Drinfeld-Sokolov integrable hierarchies. We also compute the integrals of motion for $WA_{r}$($WD_{r}$) algebras on a cylinder. Their eigenvalues on the vacuum state are confirmed to agree with the period integrals up to the sixth order. These results generalize the ODE/IM correspondence to higher-order ODEs and can be used to predict higher-order integrals of motion., Comment: 1+47 pages, 1 figure

Visual cues play crucial roles in the collective motion of animals, birds, fish, and insects. The interaction mediated by visual information is essentially non-local and has many-body nature due to occlusion, which poses a challenging problem in modeling the emergent collective behavior. In this Letter, we introduce a Boltzmann-equation approach incorporating non-local visual interaction. Occlusion is treated in a self-consistent manner via a coarse-grained density field, which renders the interaction effectively pairwise. Our model also incorporates the recent finding that each organism stochastically selects a neighbor to interact at each instant. We analytically derive the order-disorder transition point, and show that the visual screening effect substantially raises the transition threshold, which does not vanish when the density of the agents or the range of the intrinsic interaction is taken to infinity. Our analysis suggests that the model exhibits a discontinuous transition as in the local interaction models, and but the discontinuity is weakened by the non-locality. Our study clarifies the essential role of non-locality in the visual interactions among moving organisms., Comment: 5 pages, 2 figures

We report a characterization of an X-ray-detected quiescent galaxy at $z=2.09$, named COS-XQG1, using JWST/NIRCam and NIRSpec data. This galaxy is detected in Chandra imaging, suggesting the presence of an AGN with a high black hole accretion rate of $\dot{M}_{\rm BH}=0.22\pm0.03\, {\rm M_\odot yr^{-1}}$. Using multi-wavelength photometry from X-ray to sub-millimeter, including the latest JWST imaging, we confirm that COS-XQG1 is massive ($M_\star = (1.6\pm0.2)\times10^{11}\, M_\odot$) and quiescent (${\rm sSFR}=(0.9\pm 1.8)\times10^{-11}\, {\rm yr^{-1}}$) as reported previously, even considering the contribution from AGN emission. Noticeably, COS-XQG1 displays a broad line H$\alpha$ emission component with a full width at half maximum of $4491^{+118}_{-110}\, {\rm km\, s^{-1}}$ in its NIRSpec spectrum. The line width and luminosity of the broad H$\alpha$ emission give a black hole mass of $\log{(M_{\rm BH}/M_\odot)} = 8.45\pm0.02\, (\pm 0.5)$. With a stellar velocity dispersion measurement ($\sigma_\star=235\pm35\, {\rm km\, s^{-1}}$), we find that this galaxy is consistent with the local relations in the $M_{\rm BH} - \sigma_\star$ and $M_{\rm BH}- M_\star$ planes, which might suggest that massive quiescent galaxies at $z\geq2$ have already been mature in terms of both stellar and black hole masses and will not evolve significantly. In addition, image 2D-decomposition analysis finds that this galaxy comprises disk and point source components. The latter is likely the composition of an AGN and a stellar bulge. Based on a comparison with numerical simulations, we expect that COS-XQG1 will evolve into a typical bulge-dominated quiescent galaxy with lower AGN activity by redshift 0. This study shows the usefulness of X-ray-detected quiescent galaxies in investigating the co-evolution between SMBHs and galaxies in the early Universe., Comment: 15 pages, 15 figures, 2 tables, submitted to MNRAS

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

We develop a complete stationary scattering theory for Schr\"odinger operators on $\mathbb R^d$, $d\ge 2$, with $C^2$ long-range potentials. This extends former results in the literature, in particular [Is1, Is2, II, GY], which all require a higher degree of smoothness. In this sense the spirit of our paper is similar to [H\"o2, Chapter XXX], which also develops a scattering theory under the $C^2$ condition, however being very different from ours. While the Agmon-H\"ormander theory is based on the Fourier transform, our theory is not and may be seen as more related to our previous approach to scattering theory on manifolds [IS1,IS2,IS3]. The $C^2$ regularity is natural in the Agmon-H\"ormander theory as well as in our theory, in fact probably being `optimal' in the Euclidean setting. We prove equivalence of the stationary and time-dependent theories by giving stationary representations of associated time-dependent wave operators. Furthermore we develop a related stationary scattering theory at fixed energy in terms of asymptotics of generalized eigenfunctions of minimal growth. A basic ingredient of our approach is a solution to the eikonal equation constructed from the geometric variational scheme of [CS]. Another key ingredient is strong radiation condition bounds for the limiting resolvents originating in [HS]. They improve formerly known ones [Is1, Sa] and considerably simplify the stationary approach. We obtain the bounds by a new commutator scheme whose elementary form allows a small degree of smoothness.

The requirement-driven performance evaluation of a black-box cyber-physical system (CPS) that utilizes machine learning methods has proven to be an effective way to assess the quality of the CPS. However, the distributional evaluation of the performance has been poorly considered. Although many uncertainty estimation methods have been advocated, they have not successfully estimated highly complex performance distributions under small data. In this paper, we propose a method to distributionally evaluate the performance under complex requirements using small input-trajectory data. To handle the unknown complex probability distributions under small data, we discretize the corresponding performance measure, yielding a discrete random process over an input region. Then, we propose a semiparametric Bayesian model of the discrete process based on a Dirichlet random field whose parameter function is represented by multiple logistic Gaussian processes (LGPs). The Dirichlet posterior parameter function is estimated through the LGP posteriors in a reasonable and conservative fashion. We show that the proposed Bayesian model converges to the true discrete random process as the number of data becomes large enough. We also empirically demonstrate the effectiveness of the proposed method by simulation., Comment: 7 pages, 5figures. This paper has been accepted the 27th European Conference on Artificial Intelligence

Achieving both high speed and precision in robot operations is a significant challenge for social implementation. While factory robots excel at predefined tasks, they struggle with environment-specific actions like cleaning and cooking. Deep learning research aims to address this by enabling robots to autonomously execute behaviors through end-to-end learning with sensor data. RT-1 and ACT are notable examples that have expanded robots' capabilities. However, issues with model inference speed and hand position accuracy persist. High-quality training data and fast, stable inference mechanisms are essential to overcome these challenges. This paper proposes a motion generation model for high-speed, high-precision tasks, exemplified by the sports stacking task. By teaching motions slowly and inferring at high speeds, the model achieved a 94% success rate in stacking cups with a real robot., Comment: 2 pages, 2 figures

We construct TBA equations for D-type Argyres-Douglas theories with an SU(2) flavor symmetry based on their spectral networks. We show that the solutions of these TBA equations agree with the quantum periods of the corresponding quantum Seiberg-Witten curves defined in the Nekrosov-Shatashvili limit of the Omega background, including a centrifugal correction. We study the variety of TBA systems across the Coulomb branch moduli space and find that they correspond to the Dynkin diagrams of $D_n$ Lie algebras in the minimal chamber, and reproduce the TBA equations for reflectionless D scattering theories at the maximally symmetric point. Numerical computations demonstrate that the quantum periods obtained from the Borel-Pad\'e resummation and their WKB expansions are in agreement with the solutions of the TBA equations., Comment: 41 pages, 39 figures, 3 tables

We report the detection of 239 trans-Neptunian Objects discovered through the on-going New Horizons survey for distant minor bodies being performed with the Hyper Suprime-Cam mosaic imager on the Subaru Telescope. These objects were discovered in images acquired with either the r2 or the recently commissioned EB-gri filter using shift and stack routines. Due to the extremely high stellar density of the search region down stream of the spacecraft, new machine learning techniques had to be developed to manage the extremely high false positive rate of bogus candidates produced from the shift and stack routines. We report discoveries as faint as r2$\sim26.5$. We highlight an overabundance of objects found at heliocentric distances $R\gtrsim70$~au compared to expectations from modelling of the known outer Solar System. If confirmed, these objects betray the presence of a heretofore unrecognized abundance of distant objects that can help explain a number of other observations that otherwise remain at odds with the known Kuiper Belt, including detections of serendipitous stellar occultations, and recent results from the Student Dust Counter on-board the New Horizons spacecraft., Comment: Accepted for publication in the Planetary Science Journal, 28 pages, 7 figures, 3 tables

Measurements of the upper atmosphere at ~100 km are important to investigate climate change, space weather forecasting, and the interaction between the Sun and the Earth. Atmospheric occultations of cosmic X-ray sources are an effective technique to measure the neutral density in the upper atmosphere. We are developing the instrument SUIM dedicated to continuous observations of atmospheric occultations. SUIM will be mounted on a platform on the exterior of the International Space Station for six months and pointed at the Earth's rim to observe atmospheric absorption of the cosmic X-ray background (CXB). In this paper, we conducted a feasibility study of SUIM by estimating the CXB statistics and the fraction of the non-X-ray background (NXB) in the observed data. The estimated CXB statistics are enough to evaluate the atmospheric absorption of CXB for every 15 km of altitude. On the other hand, the NXB will be dominant in the X-ray spectra of SUIM. Assuming that the NXB per detection area of SUIM is comparable to that of the soft X-ray Imager onboard Hitomi, the NXB level will be much higher than the CXB one and account for ~80% of the total SUIM spectra., Comment: 5 pages, 5 figures, Proceedings of SPIE Astronomical Telescopes and Instrumentation 2024

Human perception integrates multisensory information, with tactile perception playing a key role in object and surface recognition. While human-machine interfaces with haptic modalities offer enhanced system performance, existing datasets focus primarily on visual data, overlooking comprehensive haptic information. Previous haptic texture databases have recorded sound and acceleration signals, but often ignore the nuanced differences between probe-texture and finger-texture interactions. Recognizing this shortcoming, we present the Cluster Haptic Texture Database, a multimodal dataset that records visual, auditory, and haptic signals from an artificial urethane rubber fingertip interacting with different textured surfaces. This database, designed to mimic the properties of the human finger, includes five velocity levels and eight directional variations, providing a comprehensive study of tactile interactions. Our evaluations reveal the effectiveness of classifiers trained on this dataset in identifying surfaces, and the subtleties of estimating velocity and direction for each surface.

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

This paper surveys products and studies on cryptoeconomics and tokenomics from an economic perspective, as these terms are still (i) ill-defined and (ii) disconnected from economic disciplines. We first suggest that they can be novel when integrated; we then conduct a literature review and case study following consensus-building for decentralization and token value for autonomy. Integration requires simultaneous consideration of strategic behavior, spamming, Sybil attacks, free-riding, marginal cost, marginal utility and stabilizers. This survey is the first systematization of knowledge on cryptoeconomics and tokenomics, aiming to bridge the contexts of economics and blockchain., Comment: 18 pages, 9 figures

The discovery of small organic compounds for inducing stem cell differentiation is a time- and resource-intensive process. While data science could, in principle, facilitate the discovery of these compounds, novel approaches are required due to the difficulty of acquiring training data from large numbers of example compounds. In this paper, we demonstrate the design of a new compound for inducing cardiomyocyte differentiation using simple regression models trained with a data set containing only 80 examples. We introduce decorated shape descriptors, an information-rich molecular feature representation that integrates both molecular shape and hydrophilicity information. These models demonstrate improved performance compared to ones using standard molecular descriptors based on shape alone. Model overtraining is diagnosed using a new type of sensitivity analysis. Our new compound is designed using a conservative molecular design strategy, and its effectiveness is confirmed through expression profiles of cardiomyocyte-related marker genes using real-time polymerase chain reaction experiments on human iPS cell lines. This work demonstrates a viable data-driven strategy for designing new compounds for stem cell differentiation protocols and will be useful in situations where training data is limited., Comment: 26 pages (main paper), including 7 figures and 3 tables. 23 pages of supporting information. To be submitted to a journal

Animals flexibly change their behaviour depending on context. In theory, such context-dependent behaviour can be explained by model-based reinforcement learning models. However, existing models lack structure underlying context-dependent model selection and thus, a correspondence to neural activity and brain regions. Here, we employ interacting sequential and context-inference modules to drive model-based learning as a means to better understand experimental neuronal activity data, lesion studies, and clinical research. We propose a neural circuit implementation of the sequential module by the hippocampus and the context-inference module by the cortex that together enable flexible behaviour. Our model explains a variety of experimental findings, including impairments in model-based reasoning reported in lesion studies. Furthermore, our model predicts the relationship between deficits in model-based learning and sensory processing, which often co-occur in psychoses such as schizophrenia (SZ) or autism spectrum disorder (ASD).

We study two-field inflation derived from a single complex scalar with a nonzero vacuum expectation value. Inflation is characterized by two parameters, the vacuum expectation value and the mass parameter of the phase mode, which give rise to a variety of inflationary structures. We categorize the potential trajectories of the two inflaton fields and determine the parameter regions consistent with current observational data. Furthermore, we examine the reheating process through the inflaton decay to right-handed neutrinos and the subsequent lepton number generation within these parameter regions. Our finding suggests that the existence of multiple fields can significantly alter the possibilities for inflaton oscillations and reheating., Comment: 39 pages, 9 figures

The independent set reconfiguration problem (ISReconf) is the problem of determining, for given independent sets I_s and I_t of a graph G, whether I_s can be transformed into I_t by repeatedly applying a prescribed reconfiguration rule that transforms an independent set to another. As reconfiguration rules for the ISReconf, the Token Sliding (TS) model and the Token Jumping (TJ) model are commonly considered. While the TJ model admits the addition of any vertex (as far as the addition yields an independent set), the TS model admits the addition of only a neighbor of the removed vertex. It is known that the complexity status of the ISReconf differs between the TS and TJ models for some graph classes. In this paper, we analyze how changes in reconfiguration rules affect the computational complexity of reconfiguration problems. To this end, we generalize the TS and TJ models to a unified reconfiguration rule, called the k-Jump model, which admits the addition of a vertex within distance k from the removed vertex. Then, the TS and TJ models are the 1-Jump and D(G)-Jump models, respectively, where D(G) denotes the diameter of a connected graph G. We give the following three results: First, we show that the computational complexity of the ISReconf under the k-Jump model for general graphs is equivalent for all k >= 3. Second, we present a polynomial-time algorithm to solve the ISReconf under the 2-Jump model for split graphs. We note that the ISReconf under the 1-Jump (i.e., TS) model is PSPACE-complete for split graphs, and hence the complexity status of the ISReconf differs between k = 1 and k = 2. Third, we consider the optimization variant of the ISReconf, which computes the minimum number of steps of any transformation between Is and It. We prove that this optimization variant under the k-Jump model is NP-complete for chordal graphs of diameter at most 2k + 1, for any k >=3., Comment: 16 pages, 6 figures

Magnetic Johnson noise is an important consideration for many applications involving precision magnetometry, and its significance will only increase in the future with improvements in measurement sensitivity. The fluctuation-dissipation theorem can be utilized to derive analytic expressions for magnetic Johnson noise in certain situations. But when used in conjunction with commercially available finite element analysis tools, the combined approach is particularly powerful as it provides a practical means to calculate the magnetic Johnson noise arising from conductors of arbitrary geometry and permeability. In this paper, we demonstrate this method to be one of the most comprehensive approaches presently available to calculate thermal magnetic noise. In particular, its applicability is shown to not be limited to cases where the noise is evaluated at a point in space but also can be expanded to include cases where the magnetic field detector has a more general shape, such as a finite size loop, a gradiometer, or a detector that consists of a polarized atomic species trapped in a volume. Furthermore, some physics insights gained through studies made using this method are discussed.

Neutrinos are known to undergo flavor conversion among their three flavors. In the theoretical modeling of core-collapse supernova (CCSN), there has been a great deal of attention to recent discoveries of a new type of neutrino flavor conversions, namely collisional flavor instability (CFI), in which the instability is induced by the flavor-dependent decoherence due to the disparity of neutrino-matter interactions among flavors. In this paper, we study how the appearance of on-shell muons and associated neutrino-matter interactions can impact CFIs based on linear stability analysis of flavor conversions. Some striking results emerge from the present study. First, we analytically show that breaking beta- and pair equilibrium is a necessary condition to trigger CFIs. This also indicates that CFIs with on-shell muons could appear in $e \tau$ and $\mu \tau$ neutrino mixing sectors in very high-density region ($\gtrsim 10^{13} {\rm g/cm^{3}}$), exhibiting a possibility of large impacts of CFIs on CCSN. Second, resonance-like CFIs, having a much higher growth rate than normal CFIs, can be triggered by muons. The resonance point of CFIs is different between $e \tau$ and $\mu \tau$ sectors; the former (latter) occurs at $\mu_{e (\mu)} = \mu_{n} - \mu_{p}$, where $\mu_{i}$ denotes the chemical potential of $i$ constitute ($n$ and $p$ represent neutrons and protons, respectively). Our result suggests that the non-linear evolution of CFI with on-shell muons would induce flavor conversions with the complex interplay among all three different neutrino-mixing sectors.

NanoTerasu, a new 3 GeV synchrotron light source in Japan, began user operation in April 2024. It provides high-brilliance soft to tender X-rays and covers a wide spectral range from ultraviolet to tender X-rays. Its compact storage ring with a circumference of 349 m is based on a four-bend achromat lattice to provide two straight sections in each cell for insertion devices with a natural horizontal emittance of 1.14 nm rad, which is small enough for soft X-rays users. The NanoTerasu accelerator incorporates several innovative technologies, including a full-energy injector C-band linear accelerator with a length of 110 m, an in-vacuum off-axis injection system, a four-bend achromat with B-Q combined bending magnets, and a TM020 mode accelerating cavity with built-in higher-order-mode dampers in the storage ring. This paper presents the accelerator machine commissioning over a half-year period and our model-consistent ring optics correction. The first user operation with a stored beam current of 160 mA is also reported. We summarize the storage ring parameters obtained from the commissioning. This is helpful for estimating the effective optical properties of synchrotron radiation at NanoTerasu., Comment: 30 pages, 24 figures, submitted to the journal

This paper proposes a deep feature extractor for iris recognition at arbitrary resolutions. Resolution degradation reduces the recognition performance of deep learning models trained by high-resolution images. Using various-resolution images for training can improve the model's robustness while sacrificing recognition performance for high-resolution images. To achieve higher recognition performance at various resolutions, we propose a method of resolution-adaptive feature extraction with automatically switching networks. Our framework includes resolution expert modules specialized for different resolution degradations, including down-sampling and out-of-focus blurring. The framework automatically switches them depending on the degradation condition of an input image. Lower-resolution experts are trained by knowledge-distillation from the high-resolution expert in such a manner that both experts can extract common identity features. We applied our framework to three conventional neural network models. The experimental results show that our method enhances the recognition performance at low-resolution in the conventional methods and also maintains their performance at high-resolution.

Crowdsourcing is an easy, cheap, and fast way to perform large scale quality assessment; however, human judgments are often influenced by cognitive biases, which lowers their credibility. In this study, we focus on cognitive biases associated with a multi-criteria assessment in crowdsourcing; crowdworkers who rate targets with multiple different criteria simultaneously may provide biased responses due to prominence of some criteria or global impressions of the evaluation targets. To identify and mitigate such biases, we first create evaluation datasets using crowdsourcing and investigate the effect of inter-criteria cognitive biases on crowdworker responses. Then, we propose two specific model structures for Bayesian opinion aggregation models that consider inter-criteria relations. Our experiments show that incorporating our proposed structures into the aggregation model is effective to reduce the cognitive biases and help obtain more accurate aggregation results.

We investigate the pattern dynamics of the one-dimensional non-reciprocal Swift-Hohenberg model. Characteristic spatiotemporal patterns, such as disordered, aligned, swap, chiral-swap, and chiral phases, emerge depending on the parameters. We classify the characteristic spatiotemporal patterns obtained in the numerical simulations by focusing on the spatiotemporal Fourier spectrum of the order parameters. We derive a reduced dynamical system by using the spatial Fourier series expansion. We analyze the bifurcation structure around the fixed points corresponding to the aligned and chiral phases and explain the transitions between them. The disordered phase is destabilized either to the aligned phase or to the chiral phase by the Turing bifurcation or the wave bifurcation, and the aligned phase and the chiral phase are connected by the pitchfork bifurcation., Comment: 9 pages, 6 figures

Observation datasets acquired by the Hyper Suprime-Cam (HSC) on the Subaru Telescope for NASA's New Horizons mission target search were analyzed through a method devised by JAXA. The method makes use of Field Programmable Gate arrays and was originally used to detect fast-moving objects such as space debris or near-Earth asteroids. Here we present an application of the method to detect slow-moving Kuiper Belt Objects (KBOs) in the New Horizons target search observations. A cadence that takes continuous images of one HSC field of view for half a night fits the method well. The observations for the New Horizons Kuiper Belt Extended Mission (NH/KEM) using HSC began in May 2020, and are ongoing. Here we show our result of the analysis of the dataset acquired from May 2020 through June 2021 that have already passed the proprietary period and are open to the public. We detected 84 KBO candidates in the June 2020 and June 2021 datasets, when the observation field was close to opposition., Comment: 21 pages, 9 figures, 5 tables, accepted for publication on Publications of the Astronomical Society of Japan

Open data is an important basis for open science and evidence-based policymaking. Governments of many countries disclose government-related statistics as open data. Some of these data are provided as CSV files. However, since CSV files are plain texts, we cannot ensure the integrity of a downloaded CSV file. A popular way to prove the data's integrity is a digital signature; however, it is difficult to embed a signature into a CSV file. This paper proposes a method for embedding a digital signature into a CSV file using a data hiding technique. The proposed method exploits a redundancy of the CSV format related to the use of double quotes. The experiment revealed we could embed a 512-bit signature into actual open data CSV files.

We discuss a connection between a generative model, called the diffusion model, and nonequilibrium thermodynamics for the Fokker-Planck equation, called stochastic thermodynamics. Based on the techniques of stochastic thermodynamics, we derive the speed-accuracy trade-off for the diffusion models, which is a trade-off relationship between the speed and accuracy of data generation in diffusion models. Our result implies that the entropy production rate in the forward process affects the errors in data generation. From a stochastic thermodynamic perspective, our results provide quantitative insight into how best to generate data in diffusion models. The optimal learning protocol is introduced by the conservative force in stochastic thermodynamics and the geodesic of space by the 2-Wasserstein distance in optimal transport theory. We numerically illustrate the validity of the speed-accuracy trade-off for the diffusion models with different noise schedules such as the cosine schedule, the conditional optimal transport, and the optimal transport., Comment: 26 pages, 5 figures

The spin-exotic hybrid meson $\pi_{1}(1600)$ is predicted to have a large decay rate to the $\omega\pi\pi$ final state. Using 76.6~pb$^{-1}$ of data collected with the GlueX detector, we measure the cross sections for the reactions $\gamma p \to \omega \pi^+ \pi^- p$, $\gamma p \to \omega \pi^0 \pi^0 p$, and $\gamma p\to\omega\pi^-\pi^0\Delta^{++}$ in the range $E_\gamma =$ 8-10 GeV. Using isospin conservation, we set the first upper limits on the photoproduction cross sections of the $\pi^{0}_{1}(1600)$ and $\pi^{-}_{1}(1600)$. We combine these limits with lattice calculations of decay widths and find that photoproduction of $\eta'\pi$ is the most sensitive two-body system to search for the $\pi_1(1600)$., Comment: 6 pages, 3 figures plus supplemental materials

We have performed time-dependent density functional theory simulations for the neutralization process of a hydrogen ion injected at 100eV onto the (110) surface of tungsten material. We have also proposed a method for evaluating the detection probability of electrons in a small region. This probability is interpreted as that of detecting hydrogen in each state: positive ion, neutral atom, and negative ion. As a result, the probabilities of detecting hydrogen after a collision as a positive ion, neutral atom, and negative ion were approximately 30 percent, 50 percent, and 20 percent, respectively., Comment: 10 pages, 6 figures, 1 table, 26-th International Conference on Plasma Surface Interaction

This study introduces a groundbreaking approach to simultaneous interpretation by directly leveraging the predictive capabilities of Large Language Models (LLMs). We present a novel algorithm that generates real-time translations by predicting speaker utterances and expanding multiple possibilities in a tree-like structure. This method demonstrates unprecedented flexibility and adaptability, potentially overcoming the structural differences between languages more effectively than existing systems. Our theoretical analysis, supported by illustrative examples, suggests that this approach could lead to more natural and fluent translations with minimal latency. The primary purpose of this paper is to share this innovative concept with the academic community, stimulating further research and development in this field. We discuss the theoretical foundations, potential advantages, and implementation challenges of this technique, positioning it as a significant step towards democratizing multilingual communication., Comment: 7 pages

The neutralization process of an ion particle on a surface is key issue of the plasma-wall interaction (PWI). We investigated helium (He) ion injection onto a tungsten surface using time-dependent density functional theory (TDDFT) simulation. We developed the TDDFT code QUMASUN for this study, simulating the process of electron transfer from the surface to the He nucleus by solving the time evolution of electron wave function and the classical motion of nuclei simultaneously. Our results show that the probabilities of injected $\text{He}^{2+}$ changing into $\text{He}^{1+}$ and $\text{He}^{0}$ on the surface are approximately 40 percent and 13 percent, respectively. The captured electrons by $\text{He}^{1+}$ and $\text{He}^{0}$ predominantly occupy the 2s and 2p orbitals, corresponding to excited states. In addition, we stated some challenges for applying TDDFT to plasma-wall interactions., Comment: 4 figures, 1 table, resented in 26th International conference on plasma-surface interaction

Carbon-based nanostructures possessing {\pi}-electron magnetism have attracted tremendous interest due to their great potential for nano spintronics. In particular, quantum chains with magnetic molecular units synthesized by on-surface reactions provide an ideal playground for investigating magnetic exchange interactions between localized spin components. Here, we present an extensive study of antiferromagnetic nanographene chains with the diazahexabenzocoronene molecule as the repeating unit. A combination of bond-resolved scanning tunneling microscopy, density functional theory and quantum spin models revealed their detailed structures and electronic and magnetic properties. We found that the antiferromagnetic chains host a collective state featuring gapped excitations for an even number of repeating units and one featuring a Kondo excitation for an odd number. Comparing with exact many-body quantum spin models, our molecular chains provide the realization of an entangled quantum Heisenberg model. Coupled with the tunability of the molecular building blocks, these systems can act as an ideal platform for the experimental realization of topological spin lattices.

Xtend is one of the two telescopes onboard the X-ray imaging and spectroscopy mission (XRISM), which was launched on September 7th, 2023. Xtend comprises the Soft X-ray Imager (SXI), an X-ray CCD camera, and the X-ray Mirror Assembly (XMA), a thin-foil-nested conically approximated Wolter-I optics. A large field of view of $38^{\prime}\times38^{\prime}$ over the energy range from 0.4 to 13 keV is realized by the combination of the SXI and XMA with a focal length of 5.6 m. The SXI employs four P-channel, back-illuminated type CCDs with a thick depletion layer of 200 $\mu$m. The four CCD chips are arranged in a 2$\times$2 grid and cooled down to $-110$ $^{\circ}$C with a single-stage Stirling cooler. Before the launch of XRISM, we conducted a month-long spacecraft thermal vacuum test. The performance verification of the SXI was successfully carried out in a course of multiple thermal cycles of the spacecraft. About a month after the launch of XRISM, the SXI was carefully activated and the soundness of its functionality was checked by a step-by-step process. Commissioning observations followed the initial operation. We here present pre- and post-launch results verifying the Xtend performance. All the in-orbit performances are consistent with those measured on ground and satisfy the mission requirement. Extensive calibration studies are ongoing., Comment: 10 pages, 8 figures. Proceedings of SPIE Astronomical Telescopes and Instrumentation 2024

XRISM (X-Ray Imaging and Spectroscopy Mission) is an astronomical satellite with the capability of high-resolution spectroscopy with the X-ray microcalorimeter, Resolve, and wide field-of-view imaging with the CCD camera, Xtend. The Xtend consists of the mirror assembly (XMA: X-ray Mirror Assembly) and detector (SXI: Soft X-ray Imager). The components of SXI include CCDs, analog and digital electronics, and a mechanical cooler. After the successful launch on September 6th, 2023 (UT) and subsequent critical operations, the mission instruments were turned on and set up. The CCDs have been kept at the designed operating temperature of $-110^\circ$C ~after the electronics and cooling system were successfully set up. During the initial operation phase, which continued for more than a month after the critical operations, we verified the observation procedure, stability of the cooling system, all the observation options with different imaging areas and/or timing resolutions, and operations for protection against South Atlantic Anomaly. We optimized the operation procedure and observation parameters including the cooler settings, imaging areas for the specific modes with higher timing resolutions, and event selection algorithm. We summarize our policy and procedure of the initial operations for SXI. We also report on a couple of issues we faced during the initial operations and lessons learned from them., Comment: 10 pages, 8 figures, Proceedings of SPIE Astronomical Telescopes + Instrumentation 2024

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

An Ising model is defined by a quadratic objective function known as the Hamiltonian, composed of spin variables that can take values of either $-1$ or $+1$. The goal is to assign spin values to these variables in a way that minimizes the value of the Hamiltonian. Ising models are instrumental in tackling many combinatorial optimization problems, leading to significant research in developing solvers for them. Notably, D-Wave Systems has pioneered the creation of quantum annealers, programmable solvers based on quantum mechanics, for these models. This paper introduces unit Ising models, where all non-zero coefficients of linear and quadratic terms are either $-1$ or $+1$. Due to the limited resolution of quantum annealers, unit Ising models are more suitable for quantum annealers to find optimal solutions. We propose a novel design methodology for unit Ising models to simulate logic circuits computing Boolean functions through integer linear programming. By optimizing these Ising models with quantum annealers, we can compute Boolean functions and their inverses. With a fixed unit Ising model for a logic circuit, we can potentially design Application-Specific Unit Quantum Annealers (ASUQAs) for computing the inverse function, which is analogous to Application-Specific Integrated Circuits (ASICs) in digital circuitry. For instance, if we apply this technique to a multiplication circuit, we can design an ASUQA for factorization of two numbers. Our findings suggest a powerful new method for compromising the RSA cryptosystem by leveraging ASUQAs in factorization., Comment: 16 pages, 9 figures, 2 tables

The author proves the potential modularity of K3 surfaces with complex multiplication in this paper. This is an application of the main theorem of complex multiplication for K3 surfaces by J. Rizov. As some examples, we discuss Fermat quartic and Kummer surfaces, Comment: 15 pages

Development of new functional ceramics is important for several applications, including electrochemical batteries and fuel cells. Computational prescreening and selection of such materials can help discover novel materials but is challenging due to the high cost of electronic structure calculations which would be needed to compute the structures and properties of interest such as the material's stability and ion diffusion properties. The soft bond valence (SoftBV) approach is attractive for rapid prescreening among multiple compositions and structures, but the simplicity of the approximation can make the results inaccurate. We explore the possibility of enhancing the accuracy of the SoftBV approach when estimating crystal structures by adapting the parameters of the approximation to the chemical composition. Specifically, on the examples of perovskite- and spinel-type oxides that have been proposed as promising solid-state ionic conductors, the screening factor, an independent parameter of the SoftBV approximation, is modeled using linear and non-linear methods as a function of descriptors of chemical composition. We find that making the screening factor a function of composition can noticeably improve the ability of SoftBV to correctly model structures, in particular new, putative crystal structures whose structural parameters are yet unknown. We also analyze the relative importance of nonlinearity and coupling in improving the model and find that while the quality of the model is improved by including nonlinearity, coupling is relatively unimportant. While using a neural network showed no improvement over linear regression, the recently proposed GPR-NN method that is a hybrid between a single hidden layer neural network and kernel regression showed substantial improvement, enabling the prediction of structural parameters of new ceramics with accuracy on the order of 1%.

The genus non-increasing totally positive unknotting number is the minimum number of crossing changes that transform a knot into the unknot, such that all the crossing changes are positive-to-negative crossing changes that do not increase the genus. We show that the genus non-increasing totally positive unknotting number can be arbitrary large for genus one knots., Comment: 10 pages, 3 Figures

In this paper we present a general framework to construct integrable $\mathbb{Z}_2^2$-graded extensions of classical, two-dimensional Toda and conformal affine Toda theories. The scheme is applied to define the extended Liouville and Sinh-Gordon models; they are based on $\mathbb{Z}_2^2$-graded color Lie algebras and their fields satisfy a parabosonic statististics. The mathematical tools here introduced are the $\mathbb{Z}_2^2$-graded covariant extensions of the Lax pair formalism and of the Polyakov's soldering procedure. The $\mathbb{Z}_2^2$-graded Sinh-Gordon model is derived from an affine $\mathbb{Z}_2^2$-graded color Lie algebra, mimicking a procedure originally introduced by Babelon-Bonora to derive the ordinary Sinh-Gordon model. The color Lie algebras under considerations are: the $6$-generator $\mathbb{Z}_2^2$-graded $sl_2$, the $\mathbb{Z}_2^2$-graded affine ${\widehat{sl_2}}$ algebra with two central extensions, the $\mathbb{Z}_2^2$-graded Virasoro algebra obtained from a Hamiltonian reduction., Comment: 25 pages

We measure the spin-density matrix elements (SDMEs) of the $\Delta^{++}(1232)$ in the photoproduction reaction $\gamma p \to \pi^-\Delta^{++}(1232)$ with the GlueX experiment in Hall D at Jefferson Lab. The measurement uses a linearly--polarized photon beam with energies from $8.2$ to $8.8$~GeV and the statistical precision of the SDMEs exceeds the previous measurement by three orders of magnitude for the momentum transfer squared region below $1.4$ GeV$^2$. The data are sensitive to the previously undetermined relative sign between couplings in existing Regge-exchange models. Linear combinations of the extracted SDMEs allow for a decomposition into natural and unnatural--exchange amplitudes. We find that the unnatural exchange plays an important role in the low momentum transfer region.

The past two decades have yielded several new measurements and reanalysis of older measurements of the neutron lifetime. These have led to a 4.4 standard deviation discrepancy between the most precise measurements of the neutron decay rate producing protons in cold neutron beams and the most precise lifetime measured in neutron storage experiments. Here we publish an analysis of the recently published UCN aimed a searching for an explanation of this difference using the model proposed by Koch and Hummel.

Relational reasoning refers to the ability to infer and understand the relations between multiple entities. In humans, this ability underpins many higher cognitive functions, such as problem solving and decision-making, and has been reliably linked to fluid intelligence. Despite machine learning models making impressive advances across various domains, such as natural language processing and vision, the extent to which such models can perform relational reasoning tasks remains unclear. Here we study the importance of positional encoding (PE) for relational reasoning in the Transformer, and find that a learnable PE outperforms all other commonly-used PEs (e.g., absolute, relative, rotary, etc.). Moreover, we find that when using a PE with a learnable parameter, the choice of initialization greatly influences the learned representations and its downstream generalization performance. Specifically, we find that a learned PE initialized from a small-norm distribution can 1) uncover ground-truth position information, 2) generalize in the presence of noisy inputs, and 3) produce behavioral patterns that are consistent with human performance. Our results shed light on the importance of learning high-performing and robust PEs during relational reasoning tasks, which will prove useful for tasks in which ground truth positions are not provided or not known.

This study developed a new current-readout technique capable of handling measurements with high count rates reaching 1 Gcps. By directly capturing the output current of a photomultiplier as a digitized waveform, we estimated event rates, overcoming the limitations imposed by pulse pileup constraints and deadtimes. This innovative method was applied to a muon spin rotation/relaxation/resonance experiment at the Japan Proton Accelerator Research Complex, demonstrating its anticipated performance. Furthermore, we explored methods for estimating statistical uncertainty and investigated potential applications in analog-logic OR/AND gates. Overall, our findings reveal that the developed technique opens up avenues for the development of future non-binary logic circuits operating based on n-adic numbers.

Cell-free massive MIMO (CF-mMIMO), where each user equipment (UE) is connected to multiple access points (APs), is emerging as an important component for 5G and 6G cellular systems. Accurate channel models based on measurements are required to optimize their design and deployment. This paper presents an extensive measurement campaign for CF-mMIMO in an urban environment. A new "virtual AP" technique measures channels between 80 UE locations and more than 20,000 possible microcellular AP locations. Measurements are done at 3.5 GHz carrier frequency with 350 MHz bandwidth (BW). The paper describes the measurement setup and data processing, shows sample results and their physical interpretation, and provides statistics for key quantities such as pathloss, shadowing, delay spread (DS), and delay window. We find pathloss coefficients of 2.9 and 10.4 for line-of-sight (LOS) and non line-of-sight (NLOS), respectively, where the high LOS coefficient is mainly because larger distance leads to more grazing angle of incidence and thus lower antenna gain in our setup. Shadowing standard deviations are 5.1/16.6 dB, and root mean squared (RMS) DSs of -80.6/-72.6 dBs. The measurements can also be used for parameterizing a CUNEC-type model, which will be reported in future work., Comment: submitted to IEEE TWC