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A search for proton decay into $e^+/\mu^+$ and a $\eta$ meson has been performed using data from a 0.373 Mton$\cdot$year exposure (6050.3 live days) of Super-Kamiokande. Compared to previous searches this work introduces an improved model of the intranuclear $\eta$ interaction cross section, resulting in a factor of two reduction in uncertainties from this source and $\sim$10\% increase in signal efficiency. No significant data excess was found above the expected number of atmospheric neutrino background events resulting in no indication of proton decay into either mode. Lower limits on the proton partial lifetime of $1.4\times\mathrm{10^{34}~years}$ for $p\rightarrow e^+\eta$ and $7.3\times\mathrm{10^{33}~years}$ for $p\rightarrow \mu^+\eta$ at the 90$\%$ C.L. were set. These limits are around 1.5 times longer than our previous study and are the most stringent to date.

We extend the previously published model that distinguishes between the diffusive motion of diamagnetic muons and the dynamics of ions around the muon in matter, and propose a generalized model for {\sl paramagnetic muons} (Mu$^0$s, bound states of a muon and an unpaired electron) observed in non-metallic host materials. The new model distinguishes among the independent motion of unpaired electron associated with Mu$^0$, the self-diffusive motion of Mu$^0$ as single atomic entity, and that of the ions surrounding Mu$^0$, where the muon spin relaxation is induced by dynamical fluctuations of the hyperfine (HF) field exerted from the unpaired electron (e.g., due to spin/charge exchange reaction) and/or that of the nuclear hyperfine (NHF) interactions between the unpaired electron and the surrounding ions. We have applied this model to the muonated radicals (Mu$^0$s in a polaron state) in conducting polymers, and examined the validity of the interpretations claimed in the earlier literature that the spin relaxation is induced by quasi-one dimensional motion of the unpaired electron. The result suggests that experimental support for such a claim is still inadequate and needs to be reexamined, including the possibility of other origins for the fluctuations. It is expected that our model will prove a useful guide for $\mu$SR studies of various local dynamics involving paramagnetic muon states., Comment: 11 pages, 12 figures

Thermodynamic force and irreversible current are the foundational concepts of classical nonequilibrium thermodynamics. Entropy production rate is provided by their product in classical systems, ranging from mesoscopic to macroscopic systems. However, there is no complete quantum extension of such a structure that respects quantum mechanics. In this paper, we propose anti-Hermitian operators that represent currents and forces accompanied by a gradient structure in open quantum systems described by the quantum master equation. We prove that the entropy production rate is given by the product of the force and current operators, which extends the canonical expression of the entropy production rate in the classical systems. The framework constitutes a comprehensive analogy with the nonequilibrium thermodynamics of discrete classical systems. We also show that the structure leads to the extensions of some results in stochastic thermodynamics: the geometric housekeeping-excess decomposition of entropy production and thermodynamic trade-off relations such as the thermodynamic uncertainty relation and the dissipation-time uncertainty relation. In discussing the trade-off relations, we will introduce a measure of fluctuation, which we term the quantum diffusivity., Comment: 24 pages, 5 figures

Measurements of the response function of the PIENU NaI(T$\ell$) and CsI crystal calorimeter using a monochromatic 70 MeV/c positron beam at various incidence angles are described. The experimental setup and relevant physical processes involved were simulated using Geant4 to reproduce positron energy spectra. Monte Carlo simulations were compared with experimental data across ten calorimeter-beam angles and showed good agreement. This allowed the validation of simulation parameters that were essential for precise measurements of pion decays., Comment: 7 pages, 9 figures

The evolution of galaxy sizes in different wavelengths provides unique insights on galaxy build-up across cosmic epochs. Such measurements can now finally be done at $z>3$ thanks to the exquisite spatial resolution and multi-wavelength capability of the JWST. With the public data from the CEERS, PRIMER-UDS, and PRIMER-COSMOS surveys, we measure the sizes of $\sim 3500$ star-forming galaxies at $3 \leqslant z<9$, in 7 NIRCam bands using the multi-wavelength model fitting code GalfitM. The size-mass relation is measured in four redshift bins, across all NIRCam bands. We find that, the slope and intrinsic scatter of the rest-optical size-mass relation are constant across this redshift range and consistent with previous HST-based studies at low-z. When comparing the relations across different wavelengths, the average rest-optical and rest-UV relations are consistent with each other up to $z=6$, but the intrinsic scatter is largest in rest-UV wavelengths compared to rest-optical and redder bands. This behaviour is independent of redshift and we speculate that it is driven by bursty star-formation in $z>4$ galaxies. Additionally, for $3\leqslant z<4$ star-forming galaxies at $\rm M_* > 10^{10} M_{\odot}$, we find smaller rest-$\rm 1\rm\,\mu m$ sizes in comparison to rest-optical (and rest-UV) sizes, suggestive of colour gradients. When comparing to simulations, we find agreement over $\rm M_* \approx 10^{9} - 10^{10} M_{\odot}$ but beyond this mass, the observed size-mass relation is significantly steeper. Our results show the power of JWST/NIRCam to provide new constraints on galaxy formation models., Comment: 14 pages, 9 figures, submitted to A&A

Standard approaches to quantum computing require significant overhead to correct for errors. The hardware size for conventional quantum processors in solids often increases linearly with the number of physical qubits, such as for transmon qubits in superconducting circuits or electron spin qubits in quantum dot arrays. While photonic circuits based on flying qubits do not suffer from decoherence or lack of potential scalability, they have encountered significant challenges to overcome photon loss in long delay circuits. Here, we propose an alternative approach that utilizes flying electronic wave packets propagating in solid-state quantum semiconductor circuits. Using a novel time-bin architecture for the electronic wave packets, hardware requirements are drastically reduced because qubits can be created on-demand and manipulated with a common hardware element, unlike the localized approach of wiring each qubit individually. The electronic Coulomb interaction enables reliable coupling and readout of qubits. Improving upon previous devices, we realize electronic interference at the level of a single quantized mode that can be used for manipulation of electronic wavepackets. This important landmark lays the foundation for fault-tolerant quantum computing with a compact and scalable architecture based on electron interferometry in semiconductors.

Recently, the navigation of mobile robots in unknown environments has become a particularly significant research topic. Previous studies have primarily employed real-time environmental mapping using cameras and LiDAR, along with self-localization and path generation based on those maps. Additionally, there is research on Sim-to-Real transfer, where robots acquire behaviors through pre-trained reinforcement learning and apply these learned actions in real-world navigation. However, strictly the observe action and modelling of unknown environments that change unpredictably over time with accuracy and precision is an extremely complex endeavor. This study proposes a simple navigation algorithm for traversing unknown environments by utilizes the number of swarm robots. The proposed algorithm assumes that the robot has only the simple function of sensing the direction of the goal and the relative positions of the surrounding robots. The robots can navigate an unknown environment by simply continuing towards the goal while bypassing surrounding robots. The method does not need to sense the environment, determine whether they or other robots are stuck, or do the complicated inter-robot communication. We mathematically validate the proposed navigation algorithm, present numerical simulations based on the potential field method, and conduct experimental demonstrations using developed robots based on the sound fields for navigation., Comment: 11 pages, 22 figures

For a given knot $K$ and $w>0$, we construct infinitely many mutually distinct hyperbolic knots $\{K_i\}$ such that the $P$-satellites of $K$ and $K_i$ have the same HOMFLY polynomial up to given $z$-degrees, for all braided patterns $P$ with winding number less than or equal to $w$., Comment: 5 pages, no figures

We present the analysis of three intermediate-mass quiescent galaxies (QGs) with stellar masses of $\sim10^{10}M_{\rm \odot}$ at redshifts $z\sim 3 - 4$ using NIRSpec low-resolution spectroscopy. Utilising the SED fitting code BAGPIPES, we confirm these target galaxies are consistent with quiescent population, with their specific star formation rates (sSFR) falling below 2-dex the star-forming main sequence at the same redshifts. Additionally, we identify these QGs to be less massive than those discovered in previous works, particularly prior to the JWST era. Two of our target galaxies exhibit the potentially-blended H${\alpha}$+[NII] emission line within their spectra with $S/N>5$. We discuss whether this feature comes from an Active Galactic Nucleus (AGN) or star formation although future high-resolution spectroscopy is required to reach a conclusion. One of the target galaxies is covered by JWST/NIRCam imaging of the PRIMER survey. Using the 2D profile fitting code Galfit, we examine its morphology, revealing a disc-like profile with a S\'{e}rsic index of $n=1.1 \pm 0.1$. On the size-mass relation, we find a potential distinction between less-massive ($\log_{10}{(M_*/M_\odot)}<10.3$) and massive ($\log_{10}{(M_*/M_\odot)}>10.3$) QGs in their evolutionary pathways. The derived quenching timescales for our targets are less than 1 Gyr. This may result from these galaxies being quenched by AGN feedback, supporting the AGN scenario of the emission line features., Comment: MNRAS accepted

Mpemba effects (MPEs), where a hotter system cools faster than a colder one, present intriguing anomalies in relaxation processes. Despite their universal observation and significant fundamental and practical implications, a comprehensive theoretical understanding based on microscopic properties remains elusive. In this Letter, we introduce two universal frameworks for classical systems to address this gap. Firstly, we reveal that MPEs, traditionally defined by macroscopic temperature comparisons, can be understood through microstate comparisons. This insight offers a straightforward and universal microscopic perspective on MPEs, relevant for experiments and numerical simulations to identify their microscopic origins. Secondly, we establish a "no-Mpemba theorem," a rigorous sufficient condition for the absence of MPEs, thereby identifying specific classes of systems devoid of these effects. Our findings are exemplified using ferromagnetic Ising models and one-dimensional multiparticle systems, demonstrating the practical applicability of our theoretical advancements., Comment: 7 pages, 2 figures (main text) + 10 pages, 4 figures (supplemental material). Minor updates

Quantum signal processing (QSP) and quantum singular value transformation (QSVT) have provided a unified framework for understanding many quantum algorithms, including factorization, matrix inversion, and Hamiltonian simulation. As a multivariable version of QSP, multivariable quantum signal processing (M-QSP) is proposed. M-QSP interleaves signal operators corresponding to each variable with signal processing operators, which provides an efficient means to perform multivariable polynomial transformations. However, the necessary and sufficient condition for what types of polynomials can be constructed by M-QSP is unknown. In this paper, we propose a classical algorithm to determine whether a given pair of multivariable Laurent polynomials can be implemented by M-QSP, which returns True or False. As one of the most important properties of this algorithm, it returning True is the necessary and sufficient condition. The proposed classical algorithm runs in polynomial time in the number of variables and signal operators. Our algorithm also provides a constructive method to select the necessary parameters for implementing M-QSP. These findings offer valuable insights for identifying practical applications of M-QSP., Comment: 20 pages, 2 figures

Uncertainty of environments has long been a difficult characteristic to handle, when performing real-world robot tasks. This is because the uncertainty produces unexpected observations that cannot be covered by manual scripting. Learning based robot controlling methods are a promising approach for generating flexible motions against unknown situations, but still tend to suffer under uncertainty due to its deterministic nature. In order to adaptively perform the target task under such conditions, the robot control model must be able to accurately understand the possible uncertainty, and to exploratively derive the optimal action that minimizes such uncertainty. This paper extended an existing predictive learning based robot control method, which employ foresight prediction using dynamic internal simulation. The foresight module refines the model's hidden states by sampling multiple possible futures and replace with the one that led to the lower future uncertainty. The adaptiveness of the model was evaluated on a door opening task. The door can be opened either by pushing, pulling, or sliding, but robot cannot visually distinguish which way, and is required to adapt on the fly. The results showed that the proposed model adaptively diverged its motion through interaction with the door, whereas conventional methods failed to stably diverge. The models were analyzed on Lyapunov exponents of RNN hidden states which reflect the possible divergence at each time step during task execution. The result indicated that the foresight module biased the model to consider future consequences, which lead to embedding uncertainties at the policy of the robot controller, rather than the resultant observation. This is beneficial for implementing adaptive behaviors, which indices derivation of diverse motion during exploration.

Major retinal layer segmentation methods from OCT images assume that the retina is flattened in advance, and thus cannot always deal with retinas that have changes in retinal structure due to ophthalmopathy and/or curvature due to myopia. To eliminate the use of flattening in retinal layer segmentation for practicality of such methods, we propose novel data augmentation methods for OCT images. Formula-driven data augmentation (FDDA) emulates a variety of retinal structures by vertically shifting each column of the OCT images according to a given mathematical formula. We also propose partial retinal layer copying (PRLC) that copies a part of the retinal layers and pastes it into a region outside the retinal layers. Through experiments using the OCT MS and Healthy Control dataset and the Duke Cyst DME dataset, we demonstrate that the use of FDDA and PRLC makes it possible to detect the boundaries of retinal layers without flattening even retinal layer segmentation methods that assume flattening of the retina., Comment: The 11th OMIA Workshop on MICCAI 2024

We prove Shafarevich-type arithmetic finiteness results for Mukai $n$-folds of genus 7 when $n=3,9,$ and $10$. Especially, for Mukai $3$-folds of genus $7$, which was one of the missing cases in the recent work of Javanpeykar--Loughran and Licht, we prove the cohomological generalization of the Shafarevich conjecture. Additionally, we show that the cohomological good reduction criteria do not hold for Mukai $3$-folds of genus $7$. Furthermore, we demonstrate that the Shafarevich conjecture fails when $n=6$. On the other hand, we show that there exists a Mukai $n$-fold of genus $7$ over $\mathbb{Z}$ if and only if $5\leq n \leq 10$. While the cases for $5 \leq n \leq 9$ provide the first non-trivial examples of smooth projective varieties over $\mathbb{Z}$, the non-existence for $n=4$ extends Fontaine and Abrashkin's results., Comment: 42 pages

Multibiometrics, which uses multiple biometric traits to improve recognition performance instead of using only one biometric trait to authenticate individuals, has been investigated. Previous studies have combined individually acquired biometric traits or have not fully considered the convenience of the system.Focusing on a single face image, we propose a novel multibiometric method that combines five biometric traits, i.e., face, iris, periocular, nose, eyebrow, that can be extracted from a single face image. The proposed method does not sacrifice the convenience of biometrics since only a single face image is used as input.Through a variety of experiments using the CASIA Iris Distance database, we demonstrate the effectiveness of the proposed multibiometrics method., Comment: APSIPA ASC 2024

Distributionally robust optimal control (DROC) is gaining interest. This study presents a reformulation method for discrete DROC (DDROC) problems to design optimal control policies under a worst-case distributional uncertainty. The reformulation of DDROC problems impacts both the utility of tractable improvements in continuous DROC problems and the inherent discretization modeling of DROC problems. DROC is believed to have tractability issues; namely, infinite inequalities emerge over the distribution space. Therefore, investigating tractable reformulation methods for these DROC problems is crucial. One such method utilizes the strong dualities of the worst-case expectations. However, previous studies demonstrated that certain non-trivial inequalities remain after the reformulation. To enhance the tractability of DDROC, the proposed method reformulates DDROC problems into one-layer smooth convex programming with only a few trivial inequalities. The proposed method is applied to a DDROC version of a patrol-agent design problem., Comment: 7 pages, 1 figure, This work has been submitted to the IEEE for possible publication

Due to scarcity of time-series data annotated with descriptive texts, training a model to generate descriptive texts for time-series data is challenging. In this study, we propose a method to systematically generate domain-independent descriptive texts from time-series data. We identify two distinct approaches for creating pairs of time-series data and descriptive texts: the forward approach and the backward approach. By implementing the novel backward approach, we create the Temporal Automated Captions for Observations (TACO) dataset. Experimental results demonstrate that a contrastive learning based model trained using the TACO dataset is capable of generating descriptive texts for time-series data in novel domains.

We characterize $B$-valued semi-circular system in terms of $B$-valued free probabilistic analogue of Poincar\'{e} inequality. This is a $B$-valued generalization of Biane's theorem \cite[Theorem 5.1]{b03}. Moreover, we prove that Voiculescu's conjecture on $B$-valued free Poincar\'{e} inequality in \cite{aim06} is not in the affirmative as it is., Comment: 28 pages; any comments are welcome!

We report the first measurement of the azimuthal anisotropy of J$/\psi$ at forward rapidity ($1.2<|\eta|<2.2$) in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV at the Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The second Fourier coefficient ($v_2$) of the azimuthal distribution of $J/\psi$ is determined as a function of the transverse momentum ($p_T$) using the event-plane method. The measurements were performed for several selections of collision centrality: 0\%--50\%, 10\%--60\%, and 10\%-40\%. We find that in all cases the values of $v_2(p_T)$, which quantify the elliptic flow of J$/\psi$, are consistent with zero. The results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the J$/\psi$ within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{_{NN}}}=200$ GeV., Comment: 369 authors from 72 institutions, 12 pages, 7 figures, 5 tables. v1 is version submitted to 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 present the first forward-rapidity measurements of elliptic anisotropy of open-heavy-flavor muons at the BNL Relativistic Heavy Ion Collider. The measurements are based on data samples of Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The measurements are performed in the pseudorapidity range $1.2<|\eta|<2$ and cover transverse momenta $1

This study introduces a novel theoretical framework for analyzing heteroscedastic Gaussian processes (HGPs) that identify unknown systems in a data-driven manner. Although HGPs effectively address the heteroscedasticity of noise in complex training datasets, calculating the exact posterior distributions of the HGPs is challenging, as these distributions are no longer multivariate normal. This study derives the exact means, variances, and cumulative distributions of the posterior distributions. Furthermore, the derived theoretical findings are applied to a chance-constrained tracking controller. After an HGP identifies an unknown disturbance in a plant system, the controller can handle chance constraints regarding the system despite the presence of the disturbance., Comment: This work has been submitted to the IEEE for possible publication

This letter presents contraction analysis of continuation method for suboptimal model predictive control. A contraction metric is proposed that reflects hierarchical dynamics inherent in the continuation method and, thus, leads us to a pair of tractable matrix inequalities characterizing contraction of closed-loop system controlled by the continuation method. A numerical example verifies our contraction analysis and demonstrates the tractability of the presented matrix inequalities., Comment: Submitted to IEEE Control Systems Letters (L-CSS)

An adaptive controller design for cases with disturbances is critical in practical applications for preventing unexpected control performance degradation and instability. Recently, adaptive control systems with relaxed persistent excitation (PE) conditions have been proposed to solve this problem; however, most discussions have focused on continuous-time systems. In this study, we propose a novel adaptive control method for discrete-time systems with disturbances that combines directional forgetting and concurrent learning. The proposed method does not require the PE condition, information on disturbances, unknown parameters, or matching conditions, and it guarantees exponential uniform ultimate unbounded (UUB). It was also theoretically demonstrated that the upper bound of the UUB can be designed based on the forgetting factor, which is a design parameter. Numerical simulation results illustrate the effectiveness of the proposed method., Comment: 6 pages, 1 figure

Demographic bias is one of the major challenges for face recognition systems. The majority of existing studies on demographic biases are heavily dependent on specific demographic groups or demographic classifier, making it difficult to address performance for unrecognised groups. This paper introduces ``LabellessFace'', a novel framework that improves demographic bias in face recognition without requiring demographic group labeling typically required for fairness considerations. We propose a novel fairness enhancement metric called the class favoritism level, which assesses the extent of favoritism towards specific classes across the dataset. Leveraging this metric, we introduce the fair class margin penalty, an extension of existing margin-based metric learning. This method dynamically adjusts learning parameters based on class favoritism levels, promoting fairness across all attributes. By treating each class as an individual in facial recognition systems, we facilitate learning that minimizes biases in authentication accuracy among individuals. Comprehensive experiments have demonstrated that our proposed method is effective for enhancing fairness while maintaining authentication accuracy.

Understanding the rapid formation of supermassive black holes (SMBHs) in the early universe requires an understanding of how stellar mass grows in the host galaxies. Here, we perform an analysis of rest-frame optical spectra and imaging from JWST of two quasar host galaxies at z>6 which exhibit Balmer absorption lines. These features in the stellar continuum indicate a lack of young stars, similar to low-redshift post-starburst galaxies whose star formation was recently quenched. We find that the stellar mass (log(M_* / M_sun) > 10.6) of each quasar host grew in a starburst episode at redshift 7 or 8. One of the targets exhibits little ongoing star formation, as evidenced by the photometric signature of the Balmer break and a lack of spatially resolved H-alpha emission, placing it well below the star formation main sequence at z = 6. The other galaxy is transitioning to a quiescent phase; together, the two galaxies represent the most distant massive post-starburst galaxies known. The maturity of these two galaxies is further supported by the stellar velocity dispersions of their host galaxies, placing them slightly above the upper end of the local M_BH - sigma_* relation. The properties of our two post-starburst galaxies, each hosting an active SMBH with log(M_BH / M_sun) > 9, suggests that black holes played a major role in shaping the formation of the first massive galaxies in the Universe., Comment: 24 pages, 7 figures, submitted to a Nature journal

Here we publish three years of data for the UCNtau experiment performed at the Los Alamos Ultra Cold Neutron Facility at the Los Alamos Neutron Science Center. These data are in addition to our previously published data. Our goals in this paper are to better understand and quantify systematic uncertainties and to improve the lifetime statistical precision. We report a measured value for these runs from 2020-2022 for the neutron lifetime of 877.94+/-0.37 s; when all the data from UCNtau are averaged we report an updated value for the lifetime of 877.82+/-0.22 (statistical)+0.20-0.17 (systematic) s. We utilized improved monitor detectors, reduced our correction due to UCN upscattering on ambient gas, and employed four different main UCN detector geometries both to reduce the correction required for rate dependence and explore potential contributions due to phase space evolution.

The in vivo circadian clock in single cyanobacteria is studied here by time-lapse fluorescence microscopy when the temperature is lowered below 25{\deg}C . We first disentangle the circadian clock behavior from the bacterial cold shock response by identifying a sequence of "death steps" based on cellular indicators. By analyzing only "alive" tracks, we show that the dynamic response of individual oscillatory tracks to a step-down temperature signal is described by a simple Stuart-Landau oscillator model. The same dynamical analysis applied to in vitro data (KaiC phosphorylation level following a temperature step-down) allows for extracting and comparing both clock's responses to a temperature step down. It appears, therefore, that both oscillators go through a similar supercritical Hopf bifurcation. Finally, to quantitatively describe the temperature dependence of the resulting in vivo and in vitro Stuart-Landau parameters $\mu(T)$ and $\omega_c(T)$, we propose two simplified analytical models: temperature-dependent positive feedback or time-delayed negative feedback that is temperature compensated. Our results provide strong constraints for future models and emphasize the importance of studying transitory regimes along temperature effects in circadian systems.

Chiral superconductivity exhibits the formation of novel electron pairs that breaks the time-reversal symmetry and has been actively studied in various quantum materials in recent years. However, despite its potential to provide definitive information, effects of disorder in the crystal structure on the chiral superconductivity has not yet been clarified, and therefore the investigation using a solid-solution system is desirable. We report muon-spin-relaxation (muSR) results of layered pnictide BaPtAs_1-x_Sb_x_ with a honeycomb network composed of Pt and (As, Sb). We observed an increase of the zero-field muon-spin relaxation rate in the superconducting (SC) state at the Sb end of x=1.0, suggesting the occurrence of spontaneous magnetic field due to the time-reversal symmetry breaking in the SC state. On the other hand, spontaneous magnetic field was almost and completely suppressed for the As-Sb mixed samples of x=0.9 and 0.2, respectively, suggesting that the time-reversal symmetry breaking SC state in x=1.0 is sensitive to disorder. The magnetic penetration depth estimated from transverse-field muSR measurements at x=1.0 and 0.2 behaved like weak-coupling s-wave superconductivity. These seemingly incompatible zero-field and transverse-field muSR results of BaPtAs_1-x_Sb_x_ with x=1.0 could be understood in terms of chiral d-wave superconductivity with point nodes on the three-dimensional Fermi surface., Comment: 6 pages, 3 figures, 1 table

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.

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

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

Computer-generated holography (CGH) is a promising technology for augmented reality displays, such as head-mounted or head-up displays. However, its high computational demand makes it impractical for implementation. Recent efforts to integrate neural networks into CGH have successfully accelerated computing speed, demonstrating the potential to overcome the trade-off between computational cost and image quality. Nevertheless, deploying neural network-based CGH algorithms on computationally limited embedded systems requires more efficient models with lower computational cost, memory footprint, and power consumption. In this study, we developed a lightweight model for complex hologram generation by introducing neural network quantization. Specifically, we built a model based on tensor holography and quantized it from 32-bit floating-point precision (FP32) to 8-bit integer precision (INT8). Our performance evaluation shows that the proposed INT8 model achieves hologram quality comparable to that of the FP32 model while reducing the model size by approximately 70% and increasing the speed fourfold. Additionally, we implemented the INT8 model on a system-on-module to demonstrate its deployability on embedded platforms and high power efficiency., Comment: 11 pages, 4 figures

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 paper, 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 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: 13 pages, 3 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.