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Hyperspectral image (HSI) classification is a cornerstone of remote sensing, enabling precise material and land-cover identification through rich spectral information. While deep learning has driven significant progress in this task, small patch-based classifiers, which account for over 90% of the progress, face limitations: (1) the small patch (e.g., 7x7, 9x9)-based sampling approach considers a limited receptive field, resulting in insufficient spatial structural information critical for object-level identification and noise-like misclassifications even within uniform regions; (2) undefined optimal patch sizes lead to coarse label predictions, which degrade performance; and (3) a lack of multi-shape awareness around objects. To address these challenges, we draw inspiration from large-scale image segmentation techniques, which excel at handling object boundaries-a capability essential for semantic labeling in HSI classification. However, their application remains under-explored in this task due to (1) the prevailing notion that larger patch sizes degrade performance, (2) the extensive unlabeled regions in HSI groundtruth, and (3) the misalignment of input shapes between HSI data and segmentation models. Thus, in this study, we propose a novel paradigm and baseline, HSIseg, for HSI classification that leverages segmentation techniques combined with a novel Dynamic Shifted Regional Transformer (DSRT) to overcome these challenges. We also introduce an intuitive progressive learning framework with adaptive pseudo-labeling to iteratively incorporate unlabeled regions into the training process, thereby advancing the application of segmentation techniques. Additionally, we incorporate auxiliary data through multi-source data collaboration, promoting better feature interaction. Validated on five public HSI datasets, our proposal outperforms state-of-the-art methods.

We analyze convergence of the Levenberg-Marquardt method for solving nonlinear inverse problems in Hilbert spaces. Specifically, we establish local convergence and convergence rates for a class of inverse problems that satisfy H\"{o}lder stability estimate. Furthermore, based on what we found in the mentioned analysis, we develop global reconstruction algorithms for solving inverse problems with finite measurements for exact and noisy data, respectively.

We have newly developed a Cockcroft-Walton (CW) multiplier that can be used in a gas time projection chamber (TPC). TPC requires a high voltage to form an electric field that drifts ionization electrons. Supplying the high voltage from outside the pressure vessel requires a dedicated high-voltage feedthrough. An alternative approach is to generate the high voltage inside the pressure vessel with a relatively low voltage introduced from outside. CW multiplier can convert a low AC voltage input to a high DC voltage output, making it suitable for this purpose. We have integrated the CW multiplier into a high-pressure xenon gas TPC, called AXEL (A Xenon ElectroLuminescence detector), which have been developed to search for neutrinoless double beta decay of $^{136}$Xe. It detects ionization electrons by detecting electroluminescence with silicon photomultipliers, making it strong against electrical noises. An operation with the CW multiplier was successfully demonstrated; the TPC was operated for 77 days at 6.8 bar, and an energy resolution as high as (0.67 $\pm$ 0.08) % (FWHM) at 2615 keV was obtained., Comment: 23 pages, 21 figures, preprint for PTEP submission, typos corrected

A Resistive Plate Chamber using Diamond-Like Carbon electrodes (DLC-RPC) has been developed as a background tagging detector in the MEG$~$II experiment. The DLC-RPC is planned to be installed in a high-intensity and low-momentum muon beam. This detector is required to have a detection efficiency above 90 % with four active gaps in the muon beam due to the limitation of the material budget. In such an environment, the high current flowing through the resistive electrodes causes a voltage drop, which reduces the performance of the DLC-RPC. This voltage drop can be suppressed by implementing a current evacuation pattern, though discharges are more likely to occur near the pattern. Therefore the pattern must be covered by a protection cover made of an insulator. In this study, electrode samples with a current evacuation pattern and different widths of protection cover (0.2 mm and 0.8 mm) have been produced, and their performance and stability were measured. The detection efficiency of a single-gap chamber for $\beta$-rays from a $^{90}$Sr source was measured to be up to approximately 60 % in both electrode samples. The target efficiency can be achieved even with a drop of 100 $-$ 150 V. On the other hand, after more than a dozen hours of operation, discharges suddenly occurred and the detector was prevented from further operation. These discharges created current paths on the spacing pillars. This serious problem must be investigated and solved in the future., Comment: 4 pages, 3 figures. Contribution to 8th International Conference on Micro-Pattern Gaseous Detectors, October 14-18 2024. Submitted to JINST Proceedings

Modern high-throughput biological datasets with thousands of perturbations provide the opportunity for large-scale discovery of causal graphs that represent the regulatory interactions between genes. Differentiable causal graphical models have been proposed to infer a gene regulatory network (GRN) from large scale interventional datasets, capturing the causal gene regulatory relationships from genetic perturbations. However, existing models are limited in their expressivity and scalability while failing to address the dynamic nature of biological processes such as cellular differentiation. We propose PerturbODE, a novel framework that incorporates biologically informative neural ordinary differential equations (neural ODEs) to model cell state trajectories under perturbations and derive the causal GRN from the neural ODE's parameters. We demonstrate PerturbODE's efficacy in trajectory prediction and GRN inference across simulated and real over-expression datasets.

A recent report on the detection of very-high-energy gamma rays from V4641 Sagittarii (V4641 Sgr) up to ~0.8 peta-electronvolt has made it the second confirmed "PeVatron" microquasar. Here we report on the observation of V4641 Sgr with X-Ray Imaging and Spectroscopy Mission (XRISM) in September 2024. Thanks to the large field of view and low background, the CCD imager Xtend successfully detected for the first time X-ray extended emission around V4641 Sgr with a significance of > 4.5 sigma and > 10 sigma based on our imaging and spectral analysis, respectively. The spatial extent is estimated to have a radius of $7 \pm 3$ arcmin ($13 \pm 5$ pc at a distance of 6.2 kpc) assuming a Gaussian-like radial distribution, which suggests that the particle acceleration site is within ~10 pc of the microquasar. If the X-ray morphology traces the diffusion of accelerated electrons, this spatial extent can be explained by either an enhanced magnetic field (~80 uG) or a suppressed diffusion coefficient (~$10^{27}$ cm$^2$ s$^{-1}$ at 100 TeV). The integrated X-ray flux, (4-6)$\times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ (2-10 keV), would require a magnetic field strength higher than the galactic mean (> 8 uG) if the diffuse X-ray emission originates from synchrotron radiation and the gamma-ray emission is predominantly hadronic. If the X-rays are of thermal origin, the measured extension, temperature, and plasma density can be explained by a jet with a luminosity of ~$2\times 10^{39}$ erg s$^{-1}$, which is comparable to the Eddington luminosity of this system., Comment: 9 pages, 5 figures, accepted for publication in ApJL

We propose an optical tactile sensor using self-healing materials. The proposed tactile sensor consists of a structure that includes a diode, a phototransistor, and an optical waveguide made from self-healing materials. This design offers the advantage of being less susceptible to electromagnetic noise compared to traditional tactile sensors based on electrical detection principles. The sensor estimates the applied force by detecting changes in the total internal reflection caused by deformation due to contact force. In this study, we first established a fabrication method for the optical waveguide-based tactile sensor using self-healing materials. Subsequently, we measured the sensor output when a static load was applied to the fabricated tactile sensor and evaluated its characteristics. The results confirmed that the sensor output decreases in response to the applied load., Comment: Part of proceedings of 6th International Conference AsiaHaptics 2024

The isotopic compositions of samples returned from Cb-type asteroid Ryugu and Ivuna-type (CI) chondrites are distinct from other carbonaceous chondrites, which has led to the suggestion that Ryugu and CI chondrites formed in a different region of the accretion disk, possibly around the orbits of Uranus and Neptune. We show that, like for Fe, Ryugu and CI chondrites also have indistinguishable Ni isotope anomalies, which differ from those of other carbonaceous chondrites. We propose that this unique Fe and Ni isotopic composition reflects different accretion efficiencies of small FeNi metal grains among the carbonaceous chondrite parent bodies. The CI chondrites incorporated these grains more efficiently, possibly because they formed at the end of the disk's lifetime, when planetesimal formation was also triggered by photoevaporation of the disk. Isotopic variations among carbonaceous chondrites may thus reflect fractionation of distinct dust components from a common reservoir, implying CI chondrites and Ryugu may have formed in the same region of the accretion disk as other carbonaceous chondrites., Comment: Published open access in Science Advances

Preceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande, both located in the Kamioka mine in Japan, have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance., Comment: Resubmitted to ApJ. 22 pages, 16 figures, for more information about the combined pre-supernova alert system, see https://www.lowbg.org/presnalarm/

This work is concerned with interconnected networks with non-identical subsystems. We investigate the output consensus of the network where the dynamics are subject to external disturbance and/or reference input. For a network of output-feedback passive subsystems, we first introduce an index that characterises the gap between a pair of adjacent subsystems by the difference of their input-output trajectories. The set of these indices quantifies the level of heterogeneity of the networks. We then provide a condition in terms of the level of heterogeneity and the connectivity of the networks for ensuring the output consensus of the interconnected network.

We study the dynamics of a single spin coupled to a bosonic bath at zero temperature driven by a ramp of the bias field. A single spin coupled to a bosonic sub-Ohmic bath exhibits a quantum phase transition at a certain strength of spin-boson coupling. When the bias field is ramped from a large value to zero at this critical coupling strength, the system initialized at the ground state ends up with a finite magnetization due to the critical slowing down near the transition. On the basis of the pulse-impulse approximation, we derive a scaling law between the residual magnetization and the ramp speed. The obtained scaling relation is examined using a numerical simulation based on the tensor network. The data are in favor of the scaling law to hold. We discuss the demonstration of our theoretical results by means of quantum simulation using the quantum annealer., Comment: 15 pages, 5 figures

The MEG II experiment searches for a charged-lepton-flavour-violating $\mu \to e \gamma$ with the target sensitivity of $6 \times 10^{-14}$. A liquid xenon calorimeter with VUV-sensitive photosensors measures photon position, timing, and energy. This paper concentrates on the precise photon energy reconstruction with the MEG II liquid xenon calorimeter. Since a muon beam rate is $3\text{-}5 \times 10^{7}~\text{s}^{-1}$, multi-photon elimination analysis is performed using waveform analysis techniques such as a template waveform fit. As a result, background events in the energy range of 48-58 MeV were reduced by 34 %. The calibration of the energy scale of the calorimeter with several calibration sources is also discussed to achieve a high resolution of 1.8 %., Comment: 5 pages, 7 figures. Contribution to 20th International Conference on Calorimetry for Particle Physics (CALOR2024). Submitted to EPJ Web of Conferences

A method of constructing Markov chains on finite state spaces is provided. The chain is specified by three constraints: stationarity, dependence and marginal distributions. The generalized Pythagorean theorem in information geometry plays a central role in the construction. An algorithm for obtaining the desired Markov chain is described. Integer-valued autoregressive processes are considered for illustration., Comment: 20 pages, 2 figures

For a bivariate probability distribution, local dependence around a single point on the support is often formulated as the second derivative of the logarithm of the probability density function. However, this definition lacks the invariance under marginal distribution transformations, which is often required as a criterion for dependence measures. In this study, we examine the \textit{relative local dependence}, which we define as the ratio of the local dependence to the probability density function, for copulas. By using this notion, we point out that typical copulas can be characterised as the solutions to the corresponding partial differential equations, particularly highlighting that the relative local dependence of the Frank copula remains constant. The estimation and visualization of the relative local dependence are demonstrated using simulation data. Furthermore, we propose a class of copulas where local dependence is proportional to the $k$-th power of the probability density function, and as an example, we demonstrate a newly discovered relationship derived from the density functions of two representative copulas, the Frank copula and the Farlie-Gumbel-Morgenstern (FGM) copula., Comment: 25 pages,6 figures

The robust instability of an unstable plant subject to stable perturbations is of significant importance and arises in the study of sustained oscillatory phenomena in nonlinear systems. This paper analyzes the robust instability of linear discrete-time systems against stable perturbations via the notion of robust instability radius (RIR) as a measure of instability. We determine the exact RIR for certain unstable systems using small-gain type conditions by formulating the problem in terms of a phase change rate maximization subject to appropriate constraints at unique peak-gain frequencies, for which stable first-order all-pass functions are shown to be optimal. Two real-world applications -- minimum-effort sampled-data control of magnetic levitation systems and neural spike generations in the FitzHugh--Nagumo model subject to perturbations -- are provided to illustrate the utility of our results.

We propose a giant graviton expansion for Wilson line operator indices in general representations. The inserted line operators are specified by power sum symmetric polynomials $p_\lambda$ labeled by partitions $\lambda$. We interpret the partitions as the structure of fundamental string worldsheets wrapping around the temporal circle. The strings may or may not end on giant gravitons, and by summing the contributions from all brane configurations consistent with the specified partitions, we obtain the finite $N$ line operator index. The proposed formula is consistent with known results and passes highly non-trivial numerical tests., Comment: 21 pages, 1 figure, v2: minor changes, a reference added, accepted for publication in JHEP

In dependence modeling, various copulas have been utilized. Among them, the Frank copula has been one of the most typical choices due to its simplicity. In this work, we demonstrate that the Frank copula is the minimum information copula under fixed Kendall's $\tau$ (MICK), both theoretically and numerically. First, we explain that both MICK and the Frank density follow the hyperbolic Liouville equation. Moreover, we show that the copula density satisfying the Liouville equation is uniquely the Frank copula. Our result asserts that selecting the Frank copula as an appropriate copula model is equivalent to using Kendall's $\tau$ as the sole available information about the true distribution, based on the entropy maximization principle., Comment: 10 pages, 3 figures

Hyperspectral image (HSI) classification is pivotal in the remote sensing (RS) field, particularly with the advancement of deep learning techniques. Sequential models, adapted from the natural language processing (NLP) field such as Recurrent Neural Networks (RNNs) and Transformers, have been tailored to this task, offering a unique viewpoint. However, several challenges persist 1) RNNs struggle with centric feature aggregation and are sensitive to interfering pixels, 2) Transformers require significant computational resources and often underperform with limited HSI training samples, and 3) Current scanning methods for converting images into sequence-data are simplistic and inefficient. In response, this study introduces the innovative Mamba-in-Mamba (MiM) architecture for HSI classification, the first attempt of deploying State Space Model (SSM) in this task. The MiM model includes 1) A novel centralized Mamba-Cross-Scan (MCS) mechanism for transforming images into sequence-data, 2) A Tokenized Mamba (T-Mamba) encoder that incorporates a Gaussian Decay Mask (GDM), a Semantic Token Learner (STL), and a Semantic Token Fuser (STF) for enhanced feature generation and concentration, and 3) A Weighted MCS Fusion (WMF) module coupled with a Multi-Scale Loss Design to improve decoding efficiency. Experimental results from three public HSI datasets with fixed and disjoint training-testing samples demonstrate that our method outperforms existing baselines and state-of-the-art approaches, highlighting its efficacy and potential in HSI applications.

We report the H, C, and N isotopic compositions of microscale (0.2 to 2$\mu$m) organic matter in samples of asteroid Ryugu and the Orgueil CI carbonaceous chondrite. Three regolith particles of asteroid Ryugu, returned by the Hayabusa2 spacecraft, and several fragments of Orgueil were analyzed by NanoSIMS isotopic imaging. The isotopic distributions of the Ryugu samples from two different collection spots are closely similar to each other and to the Orgueil samples, strengthening the proposed Ryugu-CI chondrite connection. Most individual sub-$\mu$m organic grains have isotopic compositions within error of bulk values, but 2-8% of them are outliers exhibiting large isotopic enrichments or depletions in D, $^{15}$N, and/or $^{13}$C. The H, C and N isotopic compositions of the outliers are not correlated with each other: while some C-rich grains are both D- and $^{15}$N-enriched, many are enriched or depleted in one or the other system. This most likely points to a diversity in isotopic fractionation pathways and thus diversity in the local formation environments for the individual outlier grains. The observation of a relatively small population of isotopic outlier grains can be explained either by escape from nebular and/or parent body homogenization of carbonaceous precursor material or addition of later isotopic outlier grains. The strong chemical similarity of isotopically typical and isotopically outlying grains, as reflected by synchrotron x-ray absorption spectra, suggests a genetic connection and thus favors the former, homogenization scenario. However, the fact that even the least altered meteorites show the same pattern of a small population of outliers on top of a larger population of homogenized grains indicates that some or most of the homogenization occurred prior to accretion of the macromolecular organic grains into asteroidal parent bodies., Comment: Accepted for publication in Earth and Planetary Science Letters. 8 figures (plus 3 supplementary figs), two tables

H-poor superluminous supernovae (SLSNe-I) are characterized by O II lines around 4,000 - 4,500 A in pre-/near-maximum spectra, so-called W-shaped O II lines. As these lines are from relatively high excitation levels, they have been considered a sign of non-thermal processes, which may give a hint of power sources of SLSNe-I. However, the conditions for these lines to appear have not been understood well. In this work, we systematically calculate synthetic spectra to reproduce observed spectra of eight SLSNe-I, parameterizing departure coefficients from the nebular approximation in the SN ejecta (expressed as b_neb). We find that most of the observed spectra can be reproduced well with b_neb ~< 10, which means that no strong departure is necessary for the formation of the W-shaped O II lines. We also show that the appearance of the W-shaped O II lines is sensitive to temperature; only spectra with temperatures T ~ 14,000 - 16,000 K can produce the W-shaped O II lines without large departures. Based on this, we constrain the non-thermal ionization rate near the photosphere. Our results suggest that spectral features of SLSNe-I can give independent constraints on the power source through the non-thermal ionization rates., Comment: 19 pages, 11 figures, accepted for publication in ApJ

PDE-based Group Convolutional Neural Networks (PDE-G-CNNs) use solvers of evolution PDEs as substitutes for the conventional components in G-CNNs. PDE-G-CNNs can offer several benefits simultaneously: fewer parameters, inherent equivariance, better accuracy, and data efficiency. In this article we focus on Euclidean equivariant PDE-G-CNNs where the feature maps are two-dimensional throughout. We call this variant of the framework a PDE-CNN. From a machine learning perspective, we list several practically desirable axioms and derive from these which PDEs should be used in a PDE-CNN, this being our main contribution. Our approach to geometric learning via PDEs is inspired by the axioms of scale-space theory, which we generalize by introducing semifield-valued signals. Our theory reveals new PDEs that can be used in PDE-CNNs and we experimentally examine what impact these have on the accuracy of PDE-CNNs. We also confirm for small networks that PDE-CNNs offer fewer parameters, increased accuracy, and better data efficiency when compared to CNNs.

We study the expected sensitivity to the mixing between sterile and tau neutrinos directly from the tau neutrino disappearance in the high-energy fixed target experiment. Here, the beam energy is large enough to produce tau neutrinos at the target with large luminosity. During their propagation to the detector, tau neutrinos may oscillate into sterile neutrinos. By examining the energy spectrum of the observed tau neutrino events, we can probe the mixing between sterile and tau neutrinos directly. In this paper, we consider Scattering and Neutrino Detector (SND) at SHiP experiment as a showcase, which uses 400 GeV protons from SPS at CERN, and expect to observe 7,300 tau and anti-tau neutrinos from the $2\times 10^{20}$ POT for 5 years operation. Assuming the uncertainty of 10\%, we find the sensitivity $|U_{\tau 4}|^2 \sim 0.08$\, (90\% CL) for $\Delta m_{41}^2 \sim 500\ \mathrm{eV}^2$ with 10\% background to the signal. We also consider a far SND at the end of the SHiP Hidden Sector Decay Spectrometer (HSDS), in which case the sensitivity would be enhanced to $|U_{\tau 4}|^2 \sim 0.02$. Away from this mass, the sensitivity becomes lower than $|U_{\tau 4}|^2 \sim 0.15$ for $\Delta m_{41}^2 \lesssim 100\ \mathrm{eV}^2$ or $\Delta m_{41}^2\gtrsim 10^4 \mathrm{eV}^2$., Comment: 14 pages, 8 figures

A novel type of resistive plate chamber, based on diamond-like carbon (DLC) electrodes is under development for background identification in the MEG II experiment. The DLC-RPC is required to have a radiation hardness to mass irradiation since it is planned to be placed in a high-intensity and low-momentum muon beam. In this study, the aging test using a high-intensity X-ray beam was conducted to evaluate the radiation hardness of the DLC-RPC. The accumulated charge due to X-ray irradiation reached about 54 C/cm$^2$, which is approximately half of the one-year irradiation dose expected in the MEG II experiment. As a result, the degradation of the gas gain was observed due to fluorine deposition and insulators formed on the DLC electrodes. In addition, discharges via spacers were also observed repeatedly and interrupted the DLC-RPC operation., Comment: 5 pages, 10 figures. Contribution to 3rd International Conference on Detector Stability and Aging Phenomena in Gaseous Detectors, November 6-10 2023. Submitted to Nuclear Inst. and Methods in Physics Research, A

We present photometric, spectroscopic and polarimetric observations of the intermediate-luminosity Type IIP supernova (SN) 2021gmj from 1 to 386 days after the explosion. The peak absolute V-band magnitude of SN 2021gmj is -15.5 mag, which is fainter than that of normal Type IIP SNe. The spectral evolution of SN 2021gmj resembles that of other sub-luminous supernovae: the optical spectra show narrow P-Cygni profiles, indicating a low expansion velocity. We estimate the progenitor mass to be about 12 Msun from the nebular spectrum and the 56Ni mass to be about 0.02 Msun from the bolometric light curve. We also derive the explosion energy to be about 3 x 10^{50} erg by comparing numerical light curve models with the observed light curves. Polarization in the plateau phase is not very large, suggesting nearly spherical outer envelope. The early photometric observations capture the rapid rise of the light curve, which is likely due to the interaction with a circumstellar material (CSM). The broad emission feature formed by highly-ionized lines on top of a blue continuum in the earliest spectrum gives further indication of the CSM at the vicinity of the progenitor. Our work suggests that a relatively low-mass progenitor of an intermediate-luminosity Type IIP SN can also experience an enhanced mass loss just before the explosion, as suggested for normal Type IIP SNe., Comment: 18 pages, 16 figures, resubmitted to MNRAS after addressing referee comments