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We study theoretically the thermoelectric effect in a superconducting state having the Bogoliubov-Fermi surfaces which stays in a thin superconducting layer between a conventional superconductor and an insulator. The thermoelectric coefficients calculated based on the linear response theory show the remarkable anisotropy in real space, which are explained well by the anisotropic shape of the Bogoliubov-Fermi surface in momentum space. Our results indicate a way to check the existence of the Bogoliubov-Fermi surfaces in a stable superconducting state because the anisotropy is controlled by the direction of an applied magnetic field., Comment: 9 pages, 6 figures

We investigate the unusual H$\alpha$ features found towards the Scutum Supershell via recent arc-minute and arc-second resolution imaging. These multi-degree features resemble a long central spine ending in a bow-shock morphology. We performed a multi-wavelength study in [SII] optical, radio continuum, infrared continuum, HI, CO, X-ray and gamma-ray emissions. Interestingly, we found the Galactic worm GW16.9$-$3.8 HI feature appears within the Scutum Supershell, and likely influences the spine morphology. Furthermore, the rightmost edge of the bow-shock H$\alpha$ emission overlaps with [S II] line emission, 4.85 GHz radio, and both 60$\mu$m and 100$\mu$m infrared continuum emissions, suggesting some potential for excitation by shock heating. We estimated the photo-ionisation from O-type and B-type stars in the region (including those from the OB associations Ser OB1B, Ser OB2 and Sct OB3) and found that this mechanism could supply the excitation to account for the observed H$\alpha$ luminosity of the spine and bow-shock of $\sim$1e36 - 2e36 erg/s (d/2.5 kpc)$^2$. Recent MHD simulations by Drozdov et al. (2022) demonstrate the potential for supernova events to drive outflow and bow-shock types of features of the same energetic nature and physical scale as the H$\alpha$ emission we observe here. While this clearly requires many supernova events over time, we speculate that one contributing event could have come from the presumably energetic supernova (hypernova) birth of the magnetar tentatively identified in the X-ray binary LS 5039., Comment: Accepted to be published by Astronomical Society of Australia (PASA)

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gamma-ray sources and precise measurements of the already discovered ones. To achieve these goals, both hardware and data analysis must employ cutting-edge techniques. This also applies to the LST-1, the first IACT built for the CTAO, which is currently taking data on the Canary island of La Palma. This paper introduces a new event reconstruction technique for IACT data, aiming to improve the image reconstruction quality and the discrimination between the signal and the background from misidentified hadrons and electrons. The technique models the development of the extensive air shower signal, recorded as a waveform per pixel, seen by CTAO telescopes' cameras. Model parameters are subsequently passed to random forest regressors and classifiers to extract information on the primary particle. The new reconstruction was applied to simulated data and to data from observations of the Crab Nebula performed by the LST-1. The event reconstruction method presented here shows promising performance improvements. The angular and energy resolution, and the sensitivity, are improved by 10 to 20% over most of the energy range. At low energy, improvements reach up to 22%, 47%, and 50%, respectively. A future extension of the method to stereoscopic analysis for telescope arrays will be the next important step., Comment: Accepted in A&A

Knitted fabrics are two-dimensional-like structures formed by stitching one-dimensional yarn into three-dimensional curves. Plain stitch or stockinette stitch, one of the most fundamental knitting stitches, consists of periodic lattices of bent yarns, where three-dimensional (3D) curling behavior naturally emerges at the edges. The elasticity and geometry of knitted fabrics have been studied in previous studies, primarily based on 2D modeling. Still, the relation between 3D geometry and the mechanics of knitted fabrics has not been clarified so far. The curling behavior of knits is intricately related to the forces and moments acting on the yarns, geometry of the unit knitted loops, mechanical properties, and contacts, hence requiring a 3D analysis. Here, we show that the curling of plain knits emerges through the elasticity and geometry of the knitted loops, combining desktop-scale experiments and reduced elasticity-based simulations. We find that by changing the horizontal and vertical knitting numbers, three types of curl shapes emerge: side curl and top/bottom curl shapes, which are curled only horizontally and vertically, and double curl shape, in which both curl shapes appear together. The fundamental mechanism of intricate shape deformation is clarified through the force and moment balance along yarn whose centerline shape is discretized through the B-spline curves where elastic stretching, bending, and contact mechanics are taken into account. We reveal that the 3D structure of the single-knitted loop plays a critical role in the curling behavior. Our results imply that the change in shape per a single knitted loop has the potential to control the 3D natural overall shape of knitted fabrics, and could be applied in predicting or designing more complex 3D shapes made of knitted fabrics., Comment: 8 pages, 6 figures

This paper explores the concept of reflexive actuation, examining how robots may leverage both internal and external stimuli to trigger changes in the motion, performance, or physical characteristics of the robot, such as its size, shape, or configuration, and so on. These changes themselves may in turn be sequentially re-used as input to drive further adaptations. Drawing inspiration from biological systems, where reflexes are an essential component of the response to environmental changes, reflexive actuation is critical to enable robots to adapt to diverse situations and perform complex tasks. The underlying principles of reflexive actuation are analyzed, with examples provided from existing implementations such as contact-sensitive reflexive arms, physical counters, and their applications. The paper also outlines future directions and challenges for advancing this research area, emphasizing its significance in the development of adaptive, responsive robotic systems., Comment: 9 pages, 5 figures

Grip, walk, crawl, and jump. Soft robots are integrated functional structures composed of compliant mechanisms, whose activity spans various industrial applications such as surgery, healthcare, surveillance, and even planetary exploration. One of their promising mobility mechanism is snap-buckling; the instability mode of flexible structures passing from one equilibrium state to another can instantaneously generate large power for its motion. Predicting their performance with even simple geometry requires disentangling material, geometric nonlinearity, and contact, thereby still being a challenging problem to date. Here, we study the jumping dynamics of hemispherical elastic shells driven by snap-buckling, as a model system of soft jumping mechanisms, combining experiments, simulations, and analytical theory. We find that the contact transition dynamics trigger the jumping phenomenon upon snap-buckling by constructing the analytical predictions with shell elasticity in excellent agreement with both experiments and simulations. Despite the simple geometry of the shell, its dynamical performance primarily relies on a complex interplay between elasticity, geometry, and contact friction. By elucidating the dynamics of the building blocks of soft robots that undergo large deformations, we can build their predictive experimental and numerical framework. Our research paves the way for designing soft robots suitable for the required loading conditions or structural requirements without empirical methods., Comment: Main text: 16 pages, 4 figures. Supplementary Information: 7 pages, 3 figures

We introduce PLaMo-100B, a large-scale language model designed for Japanese proficiency. The model was trained from scratch using 2 trillion tokens, with architecture such as QK Normalization and Z-Loss to ensure training stability during the training process. Post-training techniques, including Supervised Fine-Tuning and Direct Preference Optimization, were applied to refine the model's performance. Benchmark evaluations suggest that PLaMo-100B performs well, particularly in Japanese-specific tasks, achieving results that are competitive with frontier models like GPT-4. The base model is available at https://huggingface.co/pfnet/plamo-100b.

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 give a simple proof of the existence of a minimizer for the Sobolev inequality. Our proof is based on a representation formula via a cut-off fundamental solution., Comment: 6 pages

In their comment (1), Hawreliak et al. claims that our observation of stacking fault formation and transonic dislocation propagation in diamond (2) is not valid as they interpret the observed features as cracks. In this response letter, we describe our rationale for interpreting the observed features as stacking faults. We also address other points raised in their comments, including the clarifications of how the results of Makarov et al. (3) are not in conflict with our study., Comment: Comment on arXiv:2401.04213. 10 pages, 2 figures

Nonreciprocal transport, characterized by its direction-selective nature, holds significant potential for applications in various devices. In this study, we investigate nonreciprocal heat transport in Majorana systems, specifically focusing on the Kitaev chiral spin liquid under external magnetic fields. Our theoretical examination focuses on effects of open boundaries in which the Majorana edge modes exist, and the inversion symmetry is broken, which leads to the Dzyaloshinskii-Moriya interaction (DMI). Through perturbation theory, we demonstrate that DMI induces asymmetric hopping, resulting in the asymmetry of the Majorana band. The results of nonreciprocal heat currents are presented for various directions of external magnetic fields, and we discuss the relation between the current and the field-directions. The potential exists to manipulate both of the directions and magnitude of the non-dissipative current by varying external magnetic fields and apply to non-dissipative heat transfer devices., Comment: 8 pages, 9 figures

Cell layers are often categorized as contractile or extensile active nematics but recent experiments on neural progenitor cells with induced $+1$ topological defects challenge this classification. In a bottom-up approach, we first study a relevant particle-level model and then analyze a continuous theory derived from it. We show that both model and theory account qualitatively for the main experimental result, i.e. accumulation of cells at the core of any type of +1 defect. We argue that cell accumulation is essentially due to two generally ignored 'effective active forces'. We finally discuss the relevance and consequences of our findings in the context of other cellular active nematics experiments and previously proposed theories., Comment: 7 pages, 5 figures, plus Supplemental Information, in revision: typo corrected, references added, Figure 5a corrected, Supplement III modified

Nanosatellites are proliferating as low-cost dedicated sensing systems with lean development cycles. Kyushu Institute of Technology and collaborators have launched a joint venture for a nanosatellite mission, VERTECS. The primary mission is to elucidate the formation history of stars by observing the optical-wavelength cosmic background radiation. The VERTECS satellite will be equipped with a small-aperture telescope and a high-precision attitude control system to capture the cosmic data for analysis on the ground. However, nanosatellites are limited by their onboard memory resources and downlink speed capabilities. Additionally, due to a limited number of ground stations, the satellite mission will face issues meeting the required data budget for mission success. To alleviate this issue, we propose an on-orbit system to autonomously classify and then compress desirable image data for data downlink prioritization and optimization. The system comprises a prototype Camera Controller Board (CCB) which carries a Raspberry Pi Compute Module 4 which is used for classification and compression. The system uses a lightweight Convolutional Neural Network (CNN) model to classify and determine the desirability of captured image data. The model is designed to be lean and robust to reduce the computational and memory load on the satellite. The model is trained and tested on a novel star field dataset consisting of data captured by the Sloan Digital Sky Survey (SDSS). The dataset is meant to simulate the expected data produced by the 6U satellite. The compression step implements GZip, RICE or HCOMPRESS compression, which are standards for astronomical data. Preliminary testing on the proposed CNN model results in a classification accuracy of about 100\% on the star field dataset, with compression ratios of 3.99, 5.16 and 5.43 for GZip, RICE and HCOMPRESS that were achieved on tested FITS image data., Comment: 14 pages

An experimental investigation of collisionless shock ion acceleration is presented using a multicomponent plasma and a high-intensity picosecond duration laser pulse. Protons are the only accelerated ions when a near-critical-density plasma is driven by a laser with a modest normalized vector potential. The results of particle-in-cell simulations imply that collisionless shock may accelerate protons alone selectively, which can be an important tool for understanding the physics of inaccessible collisionless shocks in space and astrophysical plasma.

We present new Australia Telescope Compact Array (ATCA) radio observations toward N49, one of the brightest extragalactic Supernova remnants (SNRs) located in the Large Magellanic Cloud. Our new and archival ATCA radio observations were analysed along with $Chandra$ X-ray data. These observations show a prominent `bullet' shaped feature beyond the southwestern boundary of the SNR. Both X-ray morphology and radio polarisation analysis support a physical connection of this feature to the SNR. The 'bullet' feature's apparent velocity is estimated at $\sim$1300 km s$^{-1}$, based on its distance ($\sim$10 pc) from the remnant's geometric centre and estimated age ($\sim$7600 yrs). we estimated the radio spectral index, $\alpha= -0.55 \pm 0.03$ which is typical of middle-age SNRs. Polarisation maps created for N49 show low to moderate levels of mean fractional polarisation estimated at 7$\pm$1% and 10$\pm$1% for 5.5 and 9 GHz, respectively. These values are noticeably larger than found in previous studies. Moreover, the mean value for the Faraday rotation of SNR N49 from combining CABB data is 212$\pm$65 rad m$^{-2}$ and the maximum value of RM is 591$\pm$103 rad m$^{-2}$., Comment: 16 pages, accepted for publication in Publications of the Astronomical Society of Australia

The performance of ChatGPT\copyright{} and other LLMs has improved tremendously, and in online environments, they are increasingly likely to be used in a wide variety of situations, such as ChatBot on web pages, call center operations using voice interaction, and dialogue functions using agents. In the offline environment, multimodal dialogue functions are also being realized, such as guidance by Artificial Intelligence agents (AI agents) using tablet terminals and dialogue systems in the form of LLMs mounted on robots. In this multimodal dialogue, mutual emotion recognition between the AI and the user will become important. So far, there have been methods for expressing emotions on the part of the AI agent or for recognizing them using textual or voice information of the user's utterances, but methods for AI agents to recognize emotions from the user's facial expressions have not been studied. In this study, we examined whether or not LLM-based AI agents can interact with users according to their emotional states by capturing the user in dialogue with a camera, recognizing emotions from facial expressions, and adding such emotion information to prompts. The results confirmed that AI agents can have conversations according to the emotional state for emotional states with relatively high scores, such as Happy and Angry., Comment: 4 pages, 5 figures, 1 table, The 1st InterAI: Interactive AI for Human-Centered Robotics workshop in conjuction with IEEE Ro-MAN 2024, Pasadona, LA, USA, Aug. 2024

Massive star-forming regions (MSFRs) are commonly associated with hub-filament systems (HFSs) and sites of cloud-cloud collision (CCC). Recent observational studies of some MSFRs suggest a possible connection between CCC and the formation of HFSs. To understand this connection, we analyzed the magneto-hydrodynamic simulation data from Inoue et al. (2018). This simulation involves the collision of a spherical turbulent molecular cloud with a plane-parallel sea of dense molecular gas at a relative velocity of about 10 km/s. Following the collision, the turbulent and non-uniform cloud undergoes shock compression, rapidly developing filamentary structures within the compressed layer. We found that CCC can lead to the formation of HFSs, which is a combined effect of turbulence, shock compression, magnetic field, and gravity. The collision between the cloud components shapes the filaments into a cone and drives inward flows among them. These inward flows merge at the vertex of the cone, rapidly accumulating high-density gas, which can lead to the formation of massive star(s). The cone acts as a mass-collecting machine, involving a non-gravitational early process of filament formation, followed by gravitational gas attraction to finalize the HFS. The gas distribution in the position-velocity (PV) and position-position spaces highlights the challenges in detecting two cloud components and confirming their complementary distribution if the colliding clouds have a large size difference. However, such CCC events can be confirmed by the PV diagrams presenting gas flow toward the vertex of the cone, which hosts gravitationally collapsing high-density objects, and by the magnetic field morphology curved toward the direction of the collision., Comment: 30 pages, 15 figures, 4 table, Accepted for publication in The Astrophysical Journal

Morton and Vivaldi defined the polynomials whose roots are parabolic parameters for a one-parameter family of polynomial maps. We call these polynomials delta factors. They conjectured that delta factors are irreducible for the family $z\mapsto z^2+c$. One can easily show the irreducibility for periods $1$ and $2$ by reducing it to the irreducibility of cyclotomic polynomials. However, for periods $3$ and beyond, this becomes a challenging problem. This paper proves the irreducibility of delta factors for the period $3$ and demonstrates the existence of infinitely many irreducible delta factors for periods greater than $3$., Comment: 12 pages, 4 figures, 2 tables

We give a lower bound for the delta invariant of the fundamental divisor of a quasi-smooth weighted hypersurface. As a consequence, we prove K-stability of a large class of quasi-smooth Fano hypersurfaces of index 1 and of all smooth Fano weighted hypersurfaces of index 1 and 2. The proofs are based on the Abban--Zhuang method and on the study of linear systems on flags of weighted hypersurfaces., Comment: 30 pages

We explore the application of large language models (LLMs), pre-trained models with massive textual data for detecting and improving these altered states. We investigate the use of LLMs to estimate attention states, sleep stages, and sleep quality and generate sleep improvement suggestions and adaptive guided imagery scripts based on electroencephalogram (EEG) and physical activity data (e.g. waveforms, power spectrogram images, numerical features). Our results show that LLMs can estimate sleep quality based on human textual behavioral features and provide personalized sleep improvement suggestions and guided imagery scripts; however detecting attention, sleep stages, and sleep quality based on EEG and activity data requires further training data and domain-specific knowledge.

The evolution of giant molecular clouds (GMCs), the main sites of high-mass star formation, is an essential process to unravel the galaxy evolution. Using a GMC catalogue of M33 from ALMA-ACA survey, we classified 848 GMCs into three types based on the association with HII regions and their H$\alpha$ luminosities $\textit{L}$(H$\alpha$): Type I is associated with no HII regions; Type II with HII regions of $\textit{L}$(H$\alpha$) $<$ 10$^{37.5}$ erg s$^{-1}$; and Type III with HII regions of $\textit{L}$(H$\alpha$) $\geqq$ 10$^{37.5}$ erg s$^{-1}$. These criteria yield 224 Type I GMCs, 473 Type II GMCs, and 151 Type III GMCs. GMCs show changes in their physical properties according to the types; mass, radius, velocity dispersion, and $^{13}$CO detection rate of GMCs systematically increase from Type I to Type III, and additionally, Type III GMCs are closest to virial equilibrium. Type III GMCs show the highest spatial correlation with clusters younger than 10 Myr, Type II GMCs moderate correlation, and Type I GMCs are almost uncorrelated. We interpret that these types indicate an evolutionary sequence from Type I to Type II, and then to Type III with timescales of 4 Myr, 13 Myr, and 5 Myr, respectively, indicating the GMC lifetime of 22 Myr by assuming that Type II GMC has the same timescale as the Large Magellanic Cloud. The evolved GMCs concentrate on the spiral arms, while the younger GMCs are apart from the arm both to the leading and trailing sides. This indicated that GMCs collide with each other by the spiral potential, leading to the compression of GMCs and the triggering of high-mass star formation, which may support the dynamic spiral model. Overall, we suggest that the GMC evolution concept helps illuminate the galaxy evolution, including the spiral arm formation., Comment: 29 pages, 23 figures, 5 Tables, accepted for publication in PASJ

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 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 investigate the competition of magnetic reconnections in self-generated and external magnetic fields in laser-produced plasmas. The temporal evolution of plasma structures measured with self-emission imaging shows the vertical expansions and horizontal separation of plasma, which can be signatures of reconnection outflows in self-generated and external magnetic fields, respectively. Because the outflows in self-generated magnetic fields are not clear in the presence of the external magnetic field, the external magnetic field can suppress the magnetic reconnection in self-generated magnetic fields., Comment: 8 pages, 7 figures, High Energy Density Physics, in press

Context: There are currently three pulsars firmly detected by imaging atmospheric Cherenkov telescopes (IACTs), two of them reaching TeV energies, challenging models of very-high-energy (VHE) emission in pulsars. More precise observations are needed to better characterize pulsar emission at these energies. The LST-1 is the prototype of the Large-Sized Telescope, that will be part of the Cherenkov Telescope Array Observatory (CTAO). Its improved performance over previous IACTs makes it well suited for studying pulsars. Aims: To study the Crab pulsar emission with the LST-1, improving and complementing the results from other telescopes. These observations can also be used to characterize the potential of the LST-1 to study other pulsars and detect new ones. Methods: We analyzed a total of $\sim$103 hours of gamma-ray observations of the Crab pulsar conducted with the LST-1 in the period from September 2020 to January 2023. The observations were carried out at zenith angles less than 50 degrees. A new analysis of the Fermi-LAT data was also performed, including $\sim$14 years of observations. Results: The Crab pulsar phaseogram, long-term light-curve, and phase-resolved spectra are reconstructed with the LST-1 from 20 GeV to 450 GeV for P1 and up to 700 GeV for P2. The pulsed emission is detected with a significance of 15.2$\sigma$. The two characteristic emission peaks of the Crab pulsar are clearly detected (>10$\sigma$), as well as the so-called bridge emission (5.7$\sigma$). We find that both peaks are well described by power laws, with spectral indices of $\sim$3.44 and $\sim$3.03 respectively. The joint analysis of Fermi-LAT and LST-1 data shows a good agreement between both instruments in the overlapping energy range. The detailed results obtained in the first observations of the Crab pulsar with LST-1 show the potential that CTAO will have to study this type of sources., Comment: Accepted by A&A

The Black Hole Explorer (BHEX) is a next-generation space very long baseline interferometry (VLBI) mission concept that will extend the ground-based millimeter/submillimeter arrays into space. The mission, closely aligned with the science priorities of the Japanese VLBI community, involves an active engagement of this community in the development of the mission, resulting in the formation of the Black Hole Explorer Japan Consortium. Here we present the current Japanese vision for the mission, ranging from scientific objectives to instrumentation. The Consortium anticipates a wide range of scientific investigations, from diverse black hole physics and astrophysics studied through the primary VLBI mode, to the molecular universe explored via a potential single-dish observation mode in the previously unexplored 50-70\,GHz band that would make BHEX the highest-sensitivity explorer ever of molecular oxygen. A potential major contribution for the onboard instrument involves supplying essential elements for its high-sensitivity dual-band receiving system, which includes a broadband 300\,GHz SIS mixer and a space-certified multi-stage 4.5K cryocooler akin to those used in the Hitomi and XRISM satellites by the Japan Aerospace Exploration Agency. Additionally, the Consortium explores enhancing and supporting BHEX operations through the use of millimeter/submillimeter facilities developed by the National Astronomical Observatory of Japan, coupled with a network of laser communication stations operated by the National Institute of Information and Communication Technology., Comment: Submitted to SPIE Conference Series, 17 pages for the main text, 33 pages for the references, 4 figures, SPIE Astronomical Telescopes + Instrumentation 2024

The supernova remnant (SNR) IC 443 is one of the best-studied Galactic SNRs at many wavelengths. It is interacting with a very complex environment, including the SNR G189.6+3.3 and HII regions. In this paper, we observed IC 443 and G189.6+3.3 using 1.5- and 1-m telescopes to better understand the nature of these SNRs in the optical band. We perform H_alpha images showing both filamentary and diffuse structures, and long-slit spectra from many locations with Balmer and forbidden lines detected for IC 443 and G189.6+3.3. The [SII]/ H_alpha ratios confirm the SNR nature of G189.6+3.3. The ranges of our estimated electron density and pre-shock cloud density clearly indicate the complex structure surrounding IC 443 and G189.6+3.3. We also investigated the archival HI data and newly found some shell-like distributions of HI that are possibly associated with G189.6+3.3., Comment: 16 pages, 13 Figures, 5 Tables; Accepted for publication in MNRAS

Due to advances in observation and imaging technologies, modern astronomical satellites generate large volumes of data. This necessitates efficient onboard data processing and high-speed data downlink. Reflecting this trend is the VERTECS 6U Astronomical Nanosatellite. Designed for the observation of Extragalactic Background Light (EBL), this mission is expected to generate a substantial amount of image data, particularly within the confines of CubeSat capabilities. This paper introduces the VERTECS Camera Control Board (CCB), an open-source payload interface board leveraging Commercial Off-The-Shelf (COTS) components, with a Raspberry Pi Compute Module 4 at its core. The VERTECS CCB hardware and software have been designed from the ground up to serve as the sole interface between the VERTECS bus system and astronomical imaging payload, while providing compute capability not usually seen in nanosatellites of this class. Responsible for mission data processing, it will facilitate high-speed data transfer from the imaging payload via gigabit Ethernet, while also providing a high-bitrate serial connection to the payload X-band transmitter for mission data downlink. Additional interfaces for secondary payloads are provided via USB-C and standard 15-pin camera connectors. The Raspberry Pi embedded within the VERTECS CCB operates on a standard Linux distribution, streamlining the software development process. Beyond addressing the current mission's payload control and data handling requirements, the CCB sets the stage for future missions with heightened data demands. Furthermore, it supports the adoption of machine learning and other compute-intensive applications in orbit. This paper delves into the development of the VERTECS CCB, offering insights into the design and validation of this next-generation payload interface, to ensure that it can survive the rigors of space flight., Comment: 10 pages, to be presented at SPIE Software and Cyberinfrastructure for Astronomy VIII

We present a detailed investigation of photometric, spectroscopic, and polarimetric observations of the Type II SN 2023ixf. Earlier studies have provided compelling evidence for a delayed shock breakout from a confined dense circumstellar matter (CSM) enveloping the progenitor star. The temporal evolution of polarization in SN~2023ixf revealed three distinct peaks in polarization evolution at 1.4 d, 6.4 d, and 79.2 d, indicating an asymmetric dense CSM, an aspherical shock front and clumpiness in the low-density extended CSM, and an aspherical inner ejecta/He-core. SN 2023ixf displayed two dominant axes, one along the CSM-outer ejecta and the other along the inner ejecta/He-core, showcasing the independent origin of asymmetry in the early and late evolution. The argument for an aspherical shock front is further strengthened by the presence of a high-velocity broad absorption feature in the blue wing of the Balmer features in addition to the P-Cygni absorption post 16 d. Hydrodynamical light curve modeling indicated a progenitor of 10 solar mass with a radius of 470 solar radii and explosion energy of 2e51 erg, along with 0.06 solar mass of 56-Ni, though these properties are not unique due to modeling degeneracies. The modeling also indicated a two-zone CSM: a confined dense CSM extending up to 5e14 cm, with a mass-loss rate of 1e-2 solar mass per year, and an extended CSM spanning from 5e14 cm to at least 1e16cm with a mass-loss rate of 1e-4 solar mass per year, both assuming a wind-velocity of 10 km/s. The early nebular phase observations display an axisymmetric line profile of [OI], red-ward attenuation of the emission of Halpha post 125 days, and flattening in the Ks-band, marking the onset of dust formation., Comment: 32 pages, 15 figures, 1 Table, Accepted in the Astrophysical Journal

It has been theoretically predicted that the \ExB drift caused by the spontaneously generated potential in scrape-off-layers (SOLs) and divertors in tokamaks is of a similar size to the poloidal component of the parallel flow and turbulent flow, thereby it significantly impacts on the plasma transport there. Many experiments indeed have implied the role of the electric potential, however, its direct observation through its \ExB flow measurement has never been realized because the drift velocity ($10^2$--$10^3$ m/s) is significantly below the detection limit of existing diagnostics. To realize a cross-field ion flow measurement, variety of systematic uncertainties of the system must be narrowed down. Here, we develop a conceptual design of the Doppler spectrometry that enables to measure the impurity flows with $10^2$-m/s accuracy, based on an in-situ wavelength-calibration techniques developed in astrophysics field, the iodine-cell method. We discuss its properties and applicability. In particular, the scaling relation of the wavelength accuracy and various spectroscopic parameters is newly presented, which suggests the high importance of the wavelength resolution of the system. Based on transport simulations for the JT-60SA divertor, the feasibility of the system is assessed.

The utilization of deep learning on electrocardiogram (ECG) analysis has brought the advanced accuracy and efficiency of cardiac healthcare diagnostics. By leveraging the capabilities of deep learning in semantic understanding, especially in feature extraction and representation learning, this study introduces a new multimodal contrastive pretaining framework that aims to improve the quality and robustness of learned representations of 12-lead ECG signals. Our framework comprises two key components, including Cardio Query Assistant (CQA) and ECG Semantics Integrator(ESI). CQA integrates a retrieval-augmented generation (RAG) pipeline to leverage large language models (LLMs) and external medical knowledge to generate detailed textual descriptions of ECGs. The generated text is enriched with information about demographics and waveform patterns. ESI integrates both contrastive and captioning loss to pretrain ECG encoders for enhanced representations. We validate our approach through various downstream tasks, including arrhythmia detection and ECG-based subject identification. Our experimental results demonstrate substantial improvements over strong baselines in these tasks. These baselines encompass supervised and self-supervised learning methods, as well as prior multimodal pretraining approaches.

We present a new CO observation toward the Type Ia supernova remnant (SNR) 3C 397 using the Nobeyama 45-m radio telescope at an unprecedent angular resolution of $\sim$18''. We newly found that the CO cloud at $V_{\mathrm{LSR}}$ = 55.7-62.2 km s$^{-1}$ (60 km s$^{-1}$ cloud) shows a good spatial correspondence with the radio continuum shell. We also found an expanding gas motion of the 60 km s$^{-1}$ cloud with an expansion velocity of $\sim$3 km s$^{-1}$, which is thought to be formed by the pre-and/or post-supernova feedback. By considering the positions of Galactic spiral arms and the X-ray/HI absorption studies, we concluded that 3C 397 is physically associated with the 60 km s$^{-1}$ cloud rather than the previously known CO cloud at $V_{\mathrm{LSR}}$ $\sim$30 km s$^{-1}$. Given that the previously measured pre-shock density is $\sim$2-5 cm$^{-3}$, the expanding motion of the 60 km s$^{-1}$ cloud was likely formed by the pre-supernova feedback known as optically thick wind. The scenario is consistent with that 3C 397 exploded inside a wind-blown bubble as a single degenerate system., Comment: 11 pages, 9 figures, submitted to The Astrophysical Journal (ApJ)

Time series data analysis is a critical component in various domains such as finance, healthcare, and meteorology. Despite the progress in deep learning for time series analysis, there remains a challenge in addressing the non-stationary nature of time series data. Traditional models, which are built on the assumption of constant statistical properties over time, often struggle to capture the temporal dynamics in realistic time series, resulting in bias and error in time series analysis. This paper introduces the Adaptive Wavelet Network (AdaWaveNet), a novel approach that employs Adaptive Wavelet Transformation for multi-scale analysis of non-stationary time series data. AdaWaveNet designed a lifting scheme-based wavelet decomposition and construction mechanism for adaptive and learnable wavelet transforms, which offers enhanced flexibility and robustness in analysis. We conduct extensive experiments on 10 datasets across 3 different tasks, including forecasting, imputation, and a newly established super-resolution task. The evaluations demonstrate the effectiveness of AdaWaveNet over existing methods in all three tasks, which illustrates its potential in various real-world applications.

Multi-photon Fock states have diverse applications such as optical quantum information processing. For the implementation of quantum information processing, it is desirable that Fock states be generated within the telecommunication wavelength band, particularly in the C-band (1530-1565 nm). This is because mature optical communication technologies can be leveraged for the transmission, manipulation, and detection. Additionally, to achieve high-speed quantum information processing, it is desirable for Fock states to be generated in short optical pulses, as this allows embedding lots of information in the time domain. In this paper, we report the first generation of picosecond pulsed multi-photon Fock states (single-photon and two-photon states) in the C-band with Wigner negativities, which are verified by pulsed homodyne tomography. In our experimental setup, we utilize a single-pixel superconducting nanostrip photon-number-resolving detector (SNSPD), which is expected to facilitate the high-rate generation of various quantum states. This capability stems from the high temporal resolution of SNSPDs (50 ps in our case) allowing us to increase the repetition frequency of pulsed light from the conventional MHz range to the GHz range, although in this experiment the repetition frequency is limited to 10 MHz due to the bandwidth of the homodyne detector. Consequently, our experimental setup is anticipated to serve as a prototype of a high-speed optical quantum state generator for ultrafast quantum information processing at telecommunication wavelength., Comment: 9 pages, 4 figures

The galactic tidal interaction is a possible mechanism to trigger the active star formation in galaxies. The recent analyses using the HI data in the Large Magellanic Cloud (LMC) proposed that the tidally driven HI flow, the L-component, is colliding with the LMC disk, the D-component, and is triggering high-mass star formation toward the active star-forming regions R136 and N44. In order to explore the role of the collision over the entire LMC disk, we investigated the I-component, the collision-compressed gas between the L- and D-components, over the LMC disk, and found that 74% of the O/WR stars are located toward the I-component, suggesting their formation in the colliding gas. We compared four star-forming regions (R136, N44, N11, N77-N79-N83 complex). We found a positive correlation between the number of high-mass stars and the compressed gas pressure generated by collisions, suggesting that the pressure may be a key parameter in star formation., Comment: 33 pages, 18 figures, 3 Tables, accepted for publication in PASJ. arXiv admin note: text overlap with arXiv:2010.08816

Compact K\"{a}hler manifolds satisfy several nice Hodge-theoretic properties such as the Hodge symmetry, the Hard Lefschetz property and the Hodge-Riemann bilinear relations, etc. In this note, we investigate when such nice properties hold on compact complex manifolds with semistable degenerations. For compact complex manifolds which can be obtained as smoothings of SNC varieties without triple intersection locus, we show the Hodge symmetry when the monodromy logarithm induces isomorphisms on the associated graded. We also show the Hodge-Riemann relations on H^3 of compact complex 3-folds with such semistable degenerations under some conditions., Comment: 25 pages, corrected several mistakes on Proposition 2.6 in the previous version

We here present a variable-range hopping model to describe the chirality-induced spin selectivity along the DNA double helix. In this model, DNA is considered as a one-dimensional disordered system, where electrons are transported by chiral phonon-assisted hopping between localized states. Owing to the coupling between the electron spin and the vorticity of chiral phonons, electric toroidal monopole appears in the charge-to-spin conductances as a manifestation of true chirality. Our model quantitatively explains the temperature dependence of the spin polarization observed in experiments., Comment: 9 pages, 2 figures, 1 table, and the Supplemental Materials

Using the recently developed cosmological bootstrap method, we compute the exact analytical solution for the seed integral appearing in cosmological correlators with double massive scalar exchanges. The result is explicit, valid in any kinematic configuration, and free from spurious divergences. It is applicable to any number of fields' species with any masses. With an appropriate choice of variables, the results contain only single-layer summations. We also propose simple approximate formulas valid in different limits, enabling direct and instantaneous evaluation.Supported by exact numerical results using CosmoFlow, we explore the phenomenology of double massive exchange diagrams. Contrary to single-exchange diagrams with ubiquitous Lorentz-covariant interactions, the size of the cubic coupling constant can be large while respecting perturbativity bounds. Because of this property, the primordial bispectrum from double-exchange diagrams can be as large as, coincidentally, current observational constraints. In addition to being sizable on equilateral configurations, we show that the primordial bispectrum exhibits a large cosmological collider signal in the squeezed limit, making the double massive exchanges interesting channels for the detection of massive primordial fields. We propose to decisively disentangle double-exchange channels from single-exchange ones with cosmological observations by exploiting the phase information of the cosmological collider signal, the inflationary flavor oscillations from multiple fields' species exchanges and the double soft limit in the primordial trispectrum., Comment: 66 pages, 13 figures

Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10\,s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that is critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new DAQ modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit PMTs during a supernova burst and the second, the Veto module, prescales the high rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead time less than 1\,ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800~pc will trigger Veto module resulting in a prescaling of the observed neutrino data., Comment: 28 pages, 18 figures. Submitted to PTEP

We define an involutive version of Khovanov homology and a pair of integer-valued invariants $(\underline{s}, \bar{s})$ for strongly invertible knots, which is an equivariant version of the Rasmussen invariant $s$. Using these invariants, we reprove that the infinite family of knots $J_n$ introduced by Hayden each admits exotic pairs of slice disks. Our construction is intended to give a Khovanov-theoretic analogue of the formalism given by Dai, Mallick and Stoffregen in knot Floer theory., Comment: 54 pages. Revision in v3: fixed the definition of the generalized crossing change map

Diffusion models have emerged as a robust framework for various generative tasks, including tabular data synthesis. However, current tabular diffusion models tend to inherit bias in the training dataset and generate biased synthetic data, which may influence discriminatory actions. In this research, we introduce a novel tabular diffusion model that incorporates sensitive guidance to generate fair synthetic data with balanced joint distributions of the target label and sensitive attributes, such as sex and race. The empirical results demonstrate that our method effectively mitigates bias in training data while maintaining the quality of the generated samples. Furthermore, we provide evidence that our approach outperforms existing methods for synthesizing tabular data on fairness metrics such as demographic parity ratio and equalized odds ratio, achieving improvements of over $10\%$. Our implementation is available at https://github.com/comp-well-org/fair-tab-diffusion.

Bias originates from both data and algorithmic design, often exacerbated by traditional fairness methods that fail to address the subtle impacts of protected attributes. This study introduces an approach to mitigate bias in machine learning by leveraging model uncertainty. Our approach utilizes a multi-task learning (MTL) framework combined with Monte Carlo (MC) Dropout to assess and mitigate uncertainty in predictions related to protected labels. By incorporating MC Dropout, our framework quantifies prediction uncertainty, which is crucial in areas with vague decision boundaries, thereby enhancing model fairness. Our methodology integrates multi-objective learning through pareto-optimality to balance fairness and performance across various applications. We demonstrate the effectiveness and transferability of our approach across multiple datasets and enhance model explainability through saliency maps to interpret how input features influence predictions, thereby enhancing the interpretability of machine learning models in practical applications., Comment: Under review at Journal of Artificial Intelligence Research

We investigate the arithmetic properties of the multiplier polynomials for certain $1$-parameter families of polynomials. In particular, we prove integrality theorems of multiplier polynomials for $z^d+c$, $(z-c)z^d + c$ and $z^{d+1}+cz$. As a corollary, we obtain the uniform upper bound of the naive height of parabolic parameters of unicritical polynomials. Moreover, we determined the quadratic parabolic parameters for $z^2 + c$. We also conditionally list parabolic parameters for $z^2 + c$ of fixed degrees., Comment: 31pages, 10 figures

Quantum circuits for loading probability distributions into quantum states are essential subroutines in quantum algorithms used in physics, finance engineering, and machine learning. The ability to implement these with high accuracy in shallow quantum circuits is a critical issue. We propose a novel quantum state preparation method for probability distribution with mirror symmetry using matrix product states. By considering mirror symmetry, our method reduces the entanglement of probability distributions and improves the accuracy of approximations by matrix product states. As a result, we improved the accuracy by two orders of magnitude over existing methods using matrix product states. Our approach, characterized by a shallow quantum circuit primarily comprising nearest-neighbor qubit gates and linear scalability with qubit count, is highly advantageous for noisy quantum devices. Also, our experimental findings reveal that the approximation accuracy in tensor networks depends heavily on the bond dimension, with minimal reliance on the number of qubits. Our method is experimentally demonstrated for a normal distribution encoded into 10 and 20 qubits on a real quantum processor., Comment: 13 pages, 6 figures, some of the English expressions were corrected

Locality sensitive hashing (LSH) is one of the widely-used approaches to approximate nearest neighbor search (ANNS) in high-dimensional spaces. The first work on LSH for the Euclidean distance, E2LSH, showed how ANNS can be solved efficiently at a sublinear query time in the database size with theoretically-guaranteed accuracy, although it required a large hash index size. Since then, several LSH variants having much smaller index sizes have been proposed. Their query time is linear or superlinear, but they have been shown to run effectively faster because they require fewer I/Os when the index is stored on hard disk drives and because they also permit in-memory execution with modern DRAM capacity. In this paper, we show that E2LSH is regaining the advantage in query speed with the advent of modern flash storage devices such as solid-state drives (SSDs). We evaluate E2LSH on a modern single-node computing environment and analyze its computational cost and I/O cost, from which we derive storage performance requirements for its external memory execution. Our analysis indicates that E2LSH on a single consumer-grade SSD can run faster than the state-of-the-art small-index methods executed in-memory. It also indicates that E2LSH with emerging high-performance storage devices and interfaces can approach in-memory E2LSH speeds. We implement a simple adaptation of E2LSH to external memory, E2LSH-on-Storage (E2LSHoS), and evaluate it for practical large datasets of up to one billion objects using different combinations of modern storage devices and interfaces. We demonstrate that our E2LSHoS implementation runs much faster than small-index methods and can approach in-memory E2LSH speeds, and also that its query time scales sublinearly with the database size beyond the index size limit of in-memory E2LSH.

The theory behind the Lights Out game has been developed by several authors. The aim of this work is to present some results related to this game using Linear Algebra. We establish a criterion for the solubility of this game in the case of an $m$ by $n$ grid, which depends on the invertibility of a matrix, and we present the conditions for this to occur, easily verifiable from $m$ and $n$. Furthermore, we explicitly determine the value of the determinant for a particular case., Comment: in Spanish language

We present the results of the charge ratio ($R$) and polarization ($P^{\mu}_{0}$) measurements using the decay electron events collected from 2008 September to 2022 June by the Super-Kamiokande detector. Because of its underground location and long operation, we performed high precision measurements by accumulating cosmic-ray muons. We measured the muon charge ratio to be $R=1.32 \pm 0.02$ $(\mathrm{stat.}{+}\mathrm{syst.})$ at $E_{\mu}\cos \theta_{\mathrm{Zenith}}=0.7^{+0.3}_{-0.2}$ $\mathrm{TeV}$, where $E_{\mu}$ is the muon energy and $\theta_{\mathrm{Zenith}}$ is the zenith angle of incoming cosmic-ray muons. This result is consistent with the Honda flux model while this suggests a tension with the $\pi K$ model of $1.9\sigma$. We also measured the muon polarization at the production location to be $P^{\mu}_{0}=0.52 \pm 0.02$ $(\mathrm{stat.}{+}\mathrm{syst.})$ at the muon momentum of $0.9^{+0.6}_{-0.1}$ $\mathrm{TeV}/c$ at the surface of the mountain; this also suggests a tension with the Honda flux model of $1.5\sigma$. This is the most precise measurement ever to experimentally determine the cosmic-ray muon polarization near $1~\mathrm{TeV}/c$. These measurement results are useful to improve the atmospheric neutrino simulations., Comment: 29 pages, 45 figures

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.