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Topological spin textures exhibit a hierarchical nature. For instance, magnetic skyrmions, which possess a particle-like nature, can aggregate to form superstructures such as skyrmion strings and skyrmion lattices. Magnetic hopfions are also regarded as superstructures constructed from closed loops of twisted skyrmion strings, which behave as another independent particles. However, it remains elusive whether such magnetic hopfions can also aggregate to form higher-level superstructures. Here, we report a stable superstructure with three-dimensional periodic arrangement of magnetic hopfions in a frustrated spin model with easy-plane anisotropy. By comprehensively examining effective interactions between two hopfions, we construct the hopfion superstructure by a staggered arrangement of one-dimensional hopfion chains with Hopf number $H=+1$ and $H=-1$ running perpendicular to the easy plane. Each hopfion chain is threaded by a magnetic meron string, resulting in a nontrivial topological texture with skyrmion number $N_{\rm sk}=2$ per magnetic unit cell on any two-dimensional cut parallel to the easy plane. We show that the hopfion superstructure remains robust as a metastable state across a range of the hopfion density. Furthermore, we demonstrate that superstructures with higher Hopf number can also be stabilized. Our findings extend the existing hierarchy of topological magnets and pave the way for exploring new quantum phenomena and spin dynamics., Comment: 15 pages, 9 figures

We study a flaring activity of the HSP Mrk421 that was characterized from radio to very-high-energy (VHE; E $>0.1$TeV) gamma rays with MAGIC, Fermi-LAT, Swift, XMM-Newton and several optical and radio telescopes. These observations included, for the first time for a gamma-ray flare of a blazar, simultaneous X-ray polarization measurements with IXPE. We find substantial variability in both X-rays and VHE gamma rays throughout the campaign, with the highest VHE flux above 0.2 TeV occurring during the IXPE observing window, and exceeding twice the flux of the Crab Nebula. However, the VHE and X-ray spectra are on average softer, and the correlation between these two bands weaker that those reported in previous flares of Mrk421. IXPE reveals an X-ray polarization degree significantly higher than that at radio and optical frequencies. The X-ray polarization angle varies by $\sim$100$^\circ$ on timescales of days, and the polarization degree changes by more than a factor 4. The highest X-ray polarization degree reaches 26%, around which a X-ray counter-clockwise hysteresis loop is measured with XMM-Newton. It suggests that the X-ray emission comes from particles close to the high-energy cutoff, hence possibly probing an extreme case of the Turbulent Extreme Multi-Zone model. We model the broadband emission with a simplified stratified jet model throughout the flare. The polarization measurements imply an electron distribution in the X-ray emitting region with a very high minimum Lorentz factor, which is expected in electron-ion plasma, as well as a variation of the emitting region size up to a factor of three during the flaring activity. We find no correlation between the fluxes and the evolution of the model parameters, which indicates a stochastic nature of the underlying physical mechanism. Such behaviour would be expected in a highly turbulent electron-ion plasma crossing a shock front., Comment: Submitted to Astronomy and Astrophysics. Corresponding authors: Axel Arbet-Engels, Lea Heckmann, David Paneque

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

Multimodal sentiment analysis (MSA) systems leverage information from different modalities to predict human sentiment intensities. Incomplete modality is an important issue that may cause a significant performance drop in MSA systems. By generative imputation, i.e., recovering the missing data from available data, systems may achieve robust performance but will lead to high computational costs. This paper introduces a knowledge distillation method, called `Multi-Modal Contrastive Knowledge Distillation' (MM-CKD), to address the issue of incomplete modality in video sentiment analysis with lower computation cost, as a novel non-imputation-based method. We employ Multi-view Supervised Contrastive Learning (MVSC) to transfer knowledge from a teacher model to student models. This approach not only leverages cross-modal knowledge but also introduces cross-sample knowledge with supervision, jointly improving the performance of both teacher and student models through online learning. Our method gives competitive results with significantly lower computational costs than state-of-the-art imputation-based methods.

Determining the spatial curvature ($\Omega_k$) independent of cosmic microwave background observations plays a key role in revealing the physics of the early universe. The Hubble tension is one of the most serious issues in modern cosmology. We investigate halo catalogs identified from $N$-body simulations at $z=2$ and 3, mimicking high-redshift galaxy surveys. We measure redshift-space correlation functions of halos from the two snapshots. We detect clear features of baryon acoustic oscillations and redshift-space distortions. We find that we can obtain a few percent constraints on both the geometric distances and growth of structure at the distant universe in future surveys. By taking into account the information of the underlying matter power spectrum, we demonstrate that we can also achieve constraint on the Hubble constant $H_0$ with a few percent as well as the spatial curvature with $|\Omega_k|\lesssim 0.1$ by observing galaxies with the number density with $\bar{n}_{\rm g}\simeq 10^{-4} (~h^3{\rm ~Mpc}^{-3})$. Our analysis provides a timely forecast for the upcoming spectroscopic surveys, which target emission line galaxy or dusty star-forming galaxy samples., Comment: 8 pages, 4 figures, 3 tables; references and results updated; typos corrected

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.

Instruments for gamma-ray astronomy at Very High Energies ($E>100\,{\rm GeV}$) have traditionally derived their scientific results through proprietary data and software. Data standardisation has become a prominent issue in this field both as a requirement for the dissemination of data from the next generation of gamma-ray observatories and as an effective solution to realise public data legacies of current-generation instruments. Specifications for a standardised gamma-ray data format have been proposed as a community effort and have already been successfully adopted by several instruments. We present the first production of standardised data from the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) telescopes. We converted $166\,{\rm h}$ of observations from different sources and validated their analysis with the open-source software Gammapy. We consider six data sets representing different scientific and technical analysis cases and compare the results obtained analysing the standardised data with open-source software against those produced with the MAGIC proprietary data and software. Aiming at a systematic production of MAGIC data in this standardised format, we also present the implementation of a database-driven pipeline automatically performing the MAGIC data reduction from the calibrated down to the standardised data level. In all the cases selected for the validation, we obtain results compatible with the MAGIC proprietary software, both for the manual and for the automatic data productions. Part of the validation data set is also made publicly available, thus representing the first large public release of MAGIC data. This effort and this first data release represent a technical milestone toward the realisation of a public MAGIC data legacy., Comment: Accepted for publication in the Journal of High Energy Astrophysics

We present the updated constraints on cosmological parameters in a 12 parameter cosmology extended with dynamical dark energy parameters ($w_0$, $w_a$), sum of neutrino masses ($\sum m_{\nu}$), effective number of neutrinos ($N_{\rm eff}$), scaling of the lensing amplitude ($A_{\rm lens}$), and running of the scalar spectral index ($\alpha_s$). For 'CMB' data, we use the latest Planck PR4 (2020) HiLLiPoP and LoLLiPoP likelihoods, Planck PR4+ACT DR6 lensing, and Planck 2018 lowl-$l$ TT likelihoods. Also, we use the latest DESI DR1 BAO likelihoods and SNeIa likelihoods from the Pantheon+ and DESY5 samples. We find: i) Contrary to the findings of DESI collaboration, we find that the CMB+BAO+Pantheon+ leads to the inclusion of cosmological constant within $2\sigma$, while CMB+BAO+DESY5 excludes the same at more than 2$\sigma$. Thus, the dynamical nature of dark energy cannot yet be considered a robust cosmological signature. As pointed out in earlier literature, the DESY5 SNe sample might have systematics which are driving the exclusion of cosmological constant. ii) We find that for certain data combinations lead to a 1$\sigma$+ detection of $\sum m_{\nu}$, and we get a posterior peak in all dataset combinations, which is an encouraging trend towards future detection. We also provide a robust bound of $\sum m_{\nu} \lesssim 0.3$ eV (95%). Given the current uncertainty in determining the correct underlying cosmological model, we prescribe this bound for the cosmology and particle physics community. iii) With CMB+BAO+SNe, we find that $A_{\rm lens}=1$ is included at 2$\sigma$ but not at $1\sigma$. This indicates that with Planck PR4 likelihoods, there is currently no lensing anomaly in a dynamical dark energy cosmology. iv) We find that even in this largely extended cosmology, the Hubble tension persists at the level of 3.2-3.9$\sigma$. (truncated), Comment: 17 pages, 10 figures

We confirm for the first time the existence of distinctive halo bias associated with the quadrupolar type of statistical anisotropy (SA) of the linear matter density field using cosmological $N$-body simulations. We find that the coefficient of the SA-induced bias for cluster-sized halos takes negative values and exhibits a decreasing trend with increasing halo mass. This results in the quadrupole halo power spectra in a statistically anisotropic universe being less amplified compared to the monopole spectra. The anisotropic feature in halo bias that we found presents a promising new tool for testing the hypothesis of a statistically anisotropic universe, with significant implications for the precise verification of anisotropic inflation scenarios and vector dark matter and dark energy models., Comment: 6 pages, 3 figures, submitted to PRL

The magnetic solitons such as chiral solitons, magnetic skyrmions, and magnetic hopfions, exhibiting particlelike nature widely emerge in magnets depending on spatial dimension. As their number directly gives rise to an impact on magnetic properties and electronic properties, it is of great importance to control the number of solitons. However, a systematic study on dynamical processes to control the number of solitons, particularly by adding the desired number of solitons to the ground state exhibiting periodic arrangements of solitons, has been limited thus far. Here, we theoretically perform the systematic analysis for the dynamical control of the number of chiral solitons in monoaxial chiral magnets by effectively utilizing the edge modes whose excitation is localized near the edges. By studying the dynamical process associated with this edge mode in an applied rotating magnetic field by using the Landau-Lifshitz-Gilbert equation, we show that multiple soliton penetrations can take place until the system reaches the nonequilibrium steady state, and the number of infiltrated solitons successively increases with the amplitude of the rotating magnetic field after surpassing the threshold. We also clarify that the threshold amplitude of the rotating magnetic field can be reduced through the static magnetic field. Our results reveal that the desired number of solitons can be added within a certain range by taking advantage of the edge modes that appear without any special processing at the edges of the system. These results contribute to the development of an experimental way to control the number of solitons and are expected to be further applied to a wide range of magnetic solitons, not limited to chiral solitons.

We theoretically study nonlinear processes driven by a DC spin-electric field in the antiferromagnetic spin-1 Heisenberg model starting from the ground state in the Haldane phase. The DC spin-electric field generates finite spin current and accumulation since the symmetry protected topological order is destroyed by the field. We find two microscopic mechanisms responsible for the breakdown and a crossover between them: In weak fields, tripron-antitripron pair creation occurs through the tunneling mechanism, and in strong fields, the system is described by an effective Hamiltonian breaking the protecting symmetries. We analyze the numerically obtained results in terms of the Dykhne--Davis--Pechukas theory and Floquet theory, verifying the universal picture of the many-body Keldysh crossover in the DC-driven quantum spin systems., Comment: 8pages, 5figures

We study Dirac fermions in the presence of a space-dependent chiral gauge field and thermodynamic gradients, establishing a connection to the inverse spin Hall effect. The chiral gauge field induces a chiral magnetic field, resulting in a surface Fermi arc state and a chiral Landau level state which, although is delocalized in the bulk, we show to be more robust against impurities. By applying chemical potential and temperature gradients, we achieve nonzero charge currents, with each gradient leading to distinct Fermi level dependencies, both of which have been observed in a recent experiment. Unlike the conventional mixed axial-gravitational anomaly, our currents require a noncollinear chiral magnetic field and thermodynamic gradient. We further derive low-energy transport formulas and demonstrate the importance of carefully treating the ultraviolet cutoff for understanding our lattice calculations., Comment: 7 pages, 3 figures

Intrinsic alignments (IAs) of galaxies/halos observed via galaxy imaging survey, combined with redshift information, offer a novel probe of cosmology as a tracer of tidal force field of large-scale structure. In this paper, we present a perturbation theory based model for the redshift-space power spectra of galaxy/halo IAs that can keep the impact of Finger-of-God damping effect, known as a nonlinear systematics of redshift-space distortions, under control. Focusing particularly on galaxy/halo density and IA cross power spectrum, we derive analytically the explicit expressions for the next-to-leading order corrections. Comparing the model predictions with $N$-body simulations, we show that these corrections indeed play an important role for an unbiased determination of the growth-rate parameter, and hence the model proposed here can be used for a precision test of gravity on cosmological scales., Comment: 21 pages, 8 figures

We have developed a new set of Application-Specific Integrated Circuits (ASICs) of the TARGET family (CTC and CT5TEA), designed for the readout of signals from photosensors in cameras of Imaging Atmospheric Cherenkov Telescopes (IACTs) for ground-based gamma-ray astronomy. We present the performance and design details. Both ASICs feature 16 channels, with CTC being a Switched-Capacitor Array (SCA) sampler at 0.5 to 1 GSa/s with a 16,384 sample deep storage buffer, including the functionality to digitize full waveforms at arbitrary times. CT5TEA is its companion trigger ASIC (though may be used on its own), which provides trigger information for the analog sum of four (and 16) adjacent channels. Since sampling and triggering takes place in two separate ASICs, the noise due to interference from the SCA is suppressed, and allows a minimal trigger threshold of $\leq$ 2.5 mV (0.74 photo electrons (p.e.)) with a trigger noise of $\leq$ 0.5 mV (0.15 p.e.). For CTC, a maximal input voltage range from $-$0.5 V up to 1.7 V is achieved with an effective bit range of $>$ 11.6 bits and a baseline noise of 0.7 mV. The cross-talk improved to $\leq$ 1% over the whole $-$3 dB bandwidth of 220 MHz and even down to 0.2% for 1.5 V pulses of 10 ns width. Not only is the performance presented, but a temperature-stable calibration routine for pulse mode operation is introduced and validated. The resolution is found to be $\sim$ 2.5% at 33.7 mV (10 p.e.) and $\leq$ 0.3% at 337 mV (100 p.e.) with an integrated non-linearity of $<$ 1.6 mV. Developed for the Small-Sized Telescope (SST) and Schwarzschild-Couder Telescope (SCT) cameras of the Cherenkov Telescope Array Observatory (CTAO), CTC and CT5TEA are deployed for both prototypes and shall be integrated into the final versions., Comment: 18 pages, 26 figures, 1 table

We investigate continuous generation of bubbles from a bath of air in viscous liquid in a confined geometry. In our original setup, bubbles are spontaneously generated by virtue of buoyancy and a gate placed in the cell: the gate acts like an inverted funnel trapping air beneath it before continuously generating bubbles at the tip. The dynamics is characterized by the period of the bubble formation and the size of bubbles as a function of the amount of air under the gate. By analyzing the data obtained for various parameters, we successfully identified in a clear manner that the dynamics of the bubble formation is governed by dissipation in thin films whose thickness is determined by Derjaguin's law balanced by a gravitational energy change due to buoyancy, after examining numerous possibilities of dissipation, demonstrating the potential of scaling analysis even in extremely complex cases. Furthermore, we uncover a novel type of pinch-off condition, which convincingly explains the size of the bubble created: in the present case viscosity plays a vital role beyond the conventional mechanism of Tate in which gravity competes with capillarity, revealing a general mechanism of pinching-off at low Reynolds number. Accordingly, the present study significantly and fundamentally advance our knowledge of bubble generation and bubble pinch-off in a clear manner with the results relevant for a wide variety of applications in many fields. In particular, the present study demonstrates a new avenue in microfluidics for understanding physical principles by scaling up the system, without losing the characters of the flow at low Reynolds numbers.

We study a pathfinding problem where only locations (i.e., vertices) are given, and edges are implicitly defined by an oracle answering the connectivity of two locations. Despite its simple structure, this problem becomes non-trivial with a massive number of locations, due to posing a huge branching factor for search algorithms. Limiting the number of successors, such as with nearest neighbors, can reduce search efforts but compromises completeness. Instead, we propose a novel LaCAS* algorithm, which does not generate successors all at once but gradually generates successors as the search progresses. This scheme is implemented with k-nearest neighbors search on a k-d tree. LaCAS* is a complete and anytime algorithm that eventually converges to the optima. Extensive evaluations demonstrate the efficacy of LaCAS*, e.g., solving complex pathfinding instances quickly, where conventional methods falter., Comment: 14 pages

Galaxies are known to be aligned toward specific directions within the large-scale structure. Such alignment signals become important for controlling the systematics of weak lensing surveys and for constraining galaxy formation and evolution scenarios. We measure the galaxy-ellipticity and ellipticity-ellipticity correlation functions for blue star-forming galaxies at $z=1.19$ and $z=1.47$ that are selected by detecting [OII] emission lines in narrow-band filters of the Hyper Suprime-Cam on the Subaru Telescope. Assuming that disk galaxies are thin and rotation-supported, we also measure the spin correlation function by estimating spin directions with ellipticities and position angles. Above $1 \; h^{-1}{\rm Mpc}$, we do not find significant signals for galaxy-ellipticity, ellipticity-ellipticity, or spin correlations at both redshifts. Below $1 \; h^{-1}{\rm Mpc}$, a weak deviation from zero is seen at $z=1.47$, implying weak spin-filament correlations, but it is not verified by the direct comparison between angles of spins and filaments. The linear alignment model fit yields the amplitude parameter $A_{\rm NLA}=1.38\pm2.32$ at $z=1.19$ and $0.45\pm2.09$ at $z=1.47$ ($95\%$ confidence levels). We discuss various observational and physical origins that affect the search for alignments of disk galaxies at high redshifts., Comment: 16 pages, 12 figures, submitted to PASJ

In our previous study, we demonstrated the existence of an unidentified ferroelectric smectic phase in the low-temperature region of the ferroelectric smectic A phase, where the layer spacing decreases with decreasing temperature. In the present study, we identified the phase by taking 2D X-ray diffraction images of a magnetically oriented sample while allowing it to rotate and constructed a 3D reciprocal space with the sample rotation angle as the third axis for the whole picture of the reciprocal lattice vectors originating from the smectic structure. Consequently, circular diffraction images were obtained when the reciprocal lattice vectors were evenly distributed on the conical surface at a certain inclination angle in the reciprocal space. This result provides clear evidence that the phase in question was smectic C. The polarization properties also showed that the observed smectic C phase had spontaneous polarization in the direction parallel to the director and was identified as ferroelectric smectic C. These results provide a new type of classification for liquid crystalline phases that has been established over many years and is a significant contribution to the basic science of soft matter research., Comment: 25 pages, 5 figures, Supporting Information

Dynamic graph learning aims to uncover evolutionary laws in real-world systems, enabling accurate social recommendation (link prediction) or early detection of cancer cells (classification). Inspired by the success of state space models, e.g., Mamba, for efficiently capturing long-term dependencies in language modeling, we propose DyG-Mamba, a new continuous state space model (SSM) for dynamic graph learning. Specifically, we first found that using inputs as control signals for SSM is not suitable for continuous-time dynamic network data with irregular sampling intervals, resulting in models being insensitive to time information and lacking generalization properties. Drawing inspiration from the Ebbinghaus forgetting curve, which suggests that memory of past events is strongly correlated with time intervals rather than specific details of the events themselves, we directly utilize irregular time spans as control signals for SSM to achieve significant robustness and generalization. Through exhaustive experiments on 12 datasets for dynamic link prediction and dynamic node classification tasks, we found that DyG-Mamba achieves state-of-the-art performance on most of the datasets, while also demonstrating significantly improved computation and memory efficiency.

Self-similar dynamics, often described by partial differential equations (PDEs) without noise terms, have been widely observed in nature and have attracted considerable attention from researchers in various fields, including physics, fluid mechanics, applied mathematics, and chemical engineering. The concept of universality class and the renormalization group (RG) theory, emerged from critical phenomena, which also have been widely observed in nature, are pillars of modern physics, with guiding the recent development of physics. While self-similarity appearing in fluid dynamics reminds physicists of critical phenomena, deep connections between them have not been explored. Here, we focus on a variation of a daily phenomenon, a drop falling from a faucet, and demonstrate self-similar dynamics for the shape of liquid-air interface in confined space with a scaling law for a characteristic length scale, which leads to a clear correspondence between the present self-similar dynamics and critical phenomena by identifying critical exponents, which define a universality class. We not only show that the observed master curve describing the self-similar shape is a solution to the Navier-Stokes equations, but also develop a renormalization group (RG) theory for the governing PDE to show the fixed point of RG corresponds to the solution, which becomes stable with time due to a scaling crossover. Our results will impact on our understanding of critical, scaling, and singular behaviors widely observed in nature.

This study examines strategic issues in fair rank-minimizing mechanisms, which choose an assignment that minimizes the average rank of object types to which agents are assigned and satisfy a fairness property called equal treatment of equals. As one of these fair mechanisms, the uniform rank-minimizing mechanism is considered. We focus on the case where agents can refuse their assignment and obtain the outside option instead. Without the refusal option, truth-telling is not strategically dominated by any strategies if a fair rank-minimizing mechanism is used. However, if agents have the option and the uniform rank-minimizing mechanism is used, then a strategy called an outside option demotion strategy strategically dominates truth-telling. Moreover, we show that adopting this strategy may lead to inefficient assignments. To counter this, we propose a modification of the uniform rank-minimizing mechanism, though it may lead agents to strategically reduce the number of acceptable types.

Learning token embeddings based on token co-occurrence statistics has proven effective for both pre-training and fine-tuning in natural language processing. However, recent studies have pointed out that the distribution of learned embeddings degenerates into anisotropy (i.e., non-uniform distribution), and even pre-trained language models (PLMs) suffer from a loss of semantics-related information in embeddings for low-frequency tokens. This study first analyzes the fine-tuning dynamics of encoder-based PLMs and demonstrates their robustness against degeneration. On the basis of this analysis, we propose DefinitionEMB, a method that utilizes definitions to re-construct isotropically distributed and semantics-related token embeddings for encoder-based PLMs while maintaining original robustness during fine-tuning. Our experiments demonstrate the effectiveness of leveraging definitions from Wiktionary to re-construct such embeddings for two encoder-based PLMs: RoBERTa-base and BART-large. Furthermore, the re-constructed embeddings for low-frequency tokens improve the performance of these models across various GLUE and four text summarization datasets.

We explore the integration of Kolmogorov Networks (KANs) into molecular dynamics (MD) simulations to improve interatomic potentials. We propose that widely used potentials, such as the Lennard-Jones (LJ) potential, the embedded atom model (EAM), and artificial neural network (ANN) potentials, can be interpreted within the KAN framework. Specifically, we demonstrate that the descriptors for ANN potentials, typically constructed using polynomials, can be redefined using KAN's non-linear functions. By employing linear or cubic spline interpolations for these KAN functions, we show that the computational cost of evaluating ANN potentials and their derivatives is reduced., Comment: 12 pages, 11 figures

Nonlinear electrical conduction primarily mediated by an orbital texture is observed in chiral semiconductor Te. We determine the enantiospecific sign of the nonlinear conductance and identify anomalies in its carrier-density dependence. Our findings, combined with the Boltzmann equation, are attributed to a chiral orbital texture, namely a chiral distribution of the orbital magnetic moment in reciprocal space. This study underscores the efficacy of nonlinear transport measurements in probing orbital-related effects, whose differentiation from spin counterparts is often demanding in the linear response regime of electron transport., Comment: 15 pages, 10 figures, accepted for publication in Physical Review B

Electronic $K$ x rays emitted by muonic Ar atoms in the gas phase were observed using a superconducting transition-edge-sensor microcalorimeter. The high-precision energy spectra provided a clear signature of the presence of muonic atoms accompanied by a few electrons, which have never been observed before. One-, two-, and three-electron bound, i.e., H-like, He-like, and Li-like, muonic Ar atoms were identified from electronic $K$ x rays and hyper-satellite $K$ x rays. These $K$ x rays are emitted after the charge transfer process by the collisions with surrounding Ar atoms. With the aid of theoretical calculations, we confirmed that the peak positions are consistent with the x-ray energies from highly charged Cl ions, and the intensities reflecting deexcitation dynamics were successfully understood by taking into account the interaction between the muon and bound electrons.

Current-driven dynamics of spin textures plays a pivotal role in potential applications for electronic devices. While two-dimensional magnetic skyrmions with topologically nontrivial spin textures have garnered significant interest, their practical use is hindered by the skyrmion Hall effect $\unicode{x2014}$ a transverse motion to the current direction that occurs as a counteraction to the topological Hall effect of electrons by an emergent magnetic field arising from the Berry phase effect. Here, we explore current-driven dynamics of three-dimensional topological spin textures known as magnetic torons, composed of layered skyrmions with two singularities called Bloch points at their ends. Through extensive numerical simulations, we show that the torons also exhibit a Hall motion, but surprisingly over a wide range spanning from the zero Hall effect, a purely longitudinal motion, to the perfect Hall effect, a purely transverse motion accompanied by no longitudinal motion. Such flexible and controllable behaviors stem from anisotropic potential barriers on the discrete lattice, which can be particularly relevant for nanoscale torons recently discovered. Our results not only provide an experimental method to probe topology of three-dimensional magnetic textures but also pave the way for future developments in topological spintronics beyond the realm of skyrmions.

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

Multipole expansions have been often used for extracting cosmological information from anisotropic quantities in observation. However, which basis of the expansion is best suited to quantify the anisotropies is not a trivial question in any summary statistics. In this paper, using the Fisher matrix formalism, we investigate the information content in multipole moments of the power spectra of galaxy density and intrinsic ellipticity fields in linear theory from the Alcock-Paczynski effect and redshift-space distortions (RSD). We consider two expansion schemes, the associated Legendre basis as well as the standard Legendre basis conventionally used in literature. We find that the information in the multipoles of the intrinsic alignment (IA) power spectra in the associated Legendre basis converges more slowly to that in the full 2D power spectra than in the Legendre basis. This trend is particularly significant when we consider a high number density sample. In this high number density case, we show that the errors on the Hubble parameter obtained from the multipoles of the IA cross- and auto-power spectra in the associated Legendre basis are respectively about $6 \%$ and $10 \%$ larger than the full 2D case even when we use multipoles up to $\ell = 6$. Our results demonstrate that the choice of basis is arbitrary but changes the information content encoded in multipoles depending on the sample and statistics under consideration., Comment: 19 pages, 7 figures

Continual learning (CL) with Vision-Language Models (VLMs) has overcome the constraints of traditional CL, which only focuses on previously encountered classes. During the CL of VLMs, we need not only to prevent the catastrophic forgetting on incrementally learned knowledge but also to preserve the zero-shot ability of VLMs. However, existing methods require additional reference datasets to maintain such zero-shot ability and rely on domain-identity hints to classify images across different domains. In this study, we propose Regression-based Analytic Incremental Learning (RAIL), which utilizes a recursive ridge regression-based adapter to learn from a sequence of domains in a non-forgetting manner and decouple the cross-domain correlations by projecting features to a higher-dimensional space. Cooperating with a training-free fusion module, RAIL absolutely preserves the VLM's zero-shot ability on unseen domains without any reference data. Additionally, we introduce Cross-domain Task-Agnostic Incremental Learning (X-TAIL) setting. In this setting, a CL learner is required to incrementally learn from multiple domains and classify test images from both seen and unseen domains without any domain-identity hint. We theoretically prove RAIL's absolute memorization on incrementally learned domains. Experiment results affirm RAIL's state-of-the-art performance in both X-TAIL and existing Multi-domain Task-Incremental Learning settings. The code is released at https://github.com/linghan1997/Regression-based-Analytic-Incremental-Learning., Comment: Accepted by NeurIPS 2024

Maximum a posteriori decoding, a commonly used method for neural machine translation (NMT), aims to maximize the estimated posterior probability. However, high estimated probability does not always lead to high translation quality. Minimum Bayes Risk (MBR) decoding (\citealp{kumar2004minimum}) offers an alternative by seeking hypotheses with the highest expected utility. In this paper, we show that Quality Estimation (QE) reranking (\citealp{fernandes-etal-2022-quality}), which uses a QE model as a reranker, can be viewed as a variant of MBR. Inspired by this, we propose source-based MBR (sMBR) decoding, a novel approach that utilizes synthetic sources (generated via back-translation or paraphrasing) as ``support hypotheses'' and a reference-free quality estimation metric as the utility function, marking the first work to solely use sources in MBR decoding. Experiments show that sMBR outperforms QE reranking and the standard MBR decoding. Our findings suggest that sMBR is a promising approach for NMT decoding.

Extractive summarization can produce faithful summaries but often requires additional constraints such as a desired summary length. Traditional sentence compression models do not typically consider the constraints because of their restricted model abilities, which require model modifications for coping with them. To bridge this gap, we propose Instruction-based Compression (InstructCMP), an approach to the sentence compression task that can consider the length constraint through instructions by leveraging the zero-shot task-solving abilities of Large Language Models (LLMs). For this purpose, we created new evaluation datasets by transforming traditional sentence compression datasets into an instruction format. By using the datasets, we first reveal that the current LLMs still face challenges in accurately controlling the length for a compressed text. To address this issue, we propose an approach named "length priming," that incorporates additional length information into the instructions without external resources. While the length priming effectively works in a zero-shot setting, a training dataset with the instructions would further improve the ability of length control. Thus, we additionally created a training dataset in an instruction format to fine-tune the model on it. Experimental results and analysis show that applying the length priming significantly improves performances of InstructCMP in both zero-shot and fine-tuning settings without the need of any model modifications., Comment: 8 pages, 3 figures, accepted to ACL 2024 Findings (Long Paper)

We report the discovery and validation of HD 21520 b, a transiting planet found with TESS and orbiting a bright G dwarf (V=9.2, $T_{eff} = 5871 \pm 62$ K, $R_{\star} = 1.04\pm 0.02\, R_{\odot}$). HD 21520 b was originally alerted as a system (TOI-4320) consisting of two planet candidates with periods of 703.6 and 46.4 days. However, our analysis supports instead a single-planet system with an orbital period of $25.1292\pm0.0001$ days and radius of $2.70 \pm 0.09\, R_{\oplus}$. Three full transits in sectors 4, 30 and 31 match this period and have transit depths and durations in agreement with each other, as does a partial transit in sector 3. We also observe transits using CHEOPS and LCOGT. SOAR and Gemini high-resolution imaging do not indicate the presence of any nearby companions, and MINERVA-Australis and CORALIE radial velocities rule out an on-target spectroscopic binary. Additionally, we use ESPRESSO radial velocities to obtain a tentative mass measurement of $7.9^{+3.2}_{-3.0}\, M_{\oplus}$, with a 3-$\sigma$ upper limit of 17.7 $M_{\oplus}$. Due to the bright nature of its host and likely significant gas envelope of the planet, HD 21520 b is a promising candidate for further mass measurements and for atmospheric characterization., Comment: Submitted to MNRAS

The Lorentz Invariance Violation (LIV), a proposed consequence of certain quantum gravity (QG) scenarios, could instigate an energy-dependent group velocity for ultra-relativistic particles. This energy dependence, although suppressed by the massive QG energy scale $E_\mathrm{QG}$, expected to be on the level of the Planck energy $1.22 \times 10^{19}$ GeV, is potentially detectable in astrophysical observations. In this scenario, the cosmological distances traversed by photons act as an amplifier for this effect. By leveraging the observation of a remarkable flare from the blazar Mrk\,421, recorded at energies above 100 GeV by the MAGIC telescopes on the night of April 25 to 26, 2014, we look for time delays scaling linearly and quadratically with the photon energies. Using for the first time in LIV studies a binned-likelihood approach we set constraints on the QG energy scale. For the linear scenario, we set $95\%$ lower limits $E_\mathrm{QG}>2.7\times10^{17}$ GeV for the subluminal case and $E_\mathrm{QG}> 3.6 \times10^{17}$ GeV for the superluminal case. For the quadratic scenario, the $95\%$ lower limits for the subluminal and superluminal cases are $E_\mathrm{QG}>2.6 \times10^{10}$ GeV and $E_\mathrm{QG}>2.5\times10^{10}$ GeV, respectively.

Recently, simple scaling laws concerning the mechanical response and mechanical transition of Kirigami have been revealed through agreement between theory and experiment for kirigami made of paper [M. Isobe and K. Okumura, Sci. Rep. 2016]. Here, we provide experimental data obtained from kirigami made of soft elastic sheets to demonstrate good agreement with previous theories, although a number of assumptions in the theory are violated and the elastic modulus is three orders of magnitude smaller in the present case. This remarkable universality in the mechanics of Kirigami, which could be useful for applications, is reported with physical insights based on previous theories.

We explore the potential of detecting parity violation in primordial vector fossils using late-time galaxy spins. Utilizing $N$-body simulations, we use halo spins as a reliable proxy for galaxy spins to investigate how effectively such primordial vectorial parity asymmetry remains in galaxy spins at low redshifts. We develop a novel approach to generate initial conditions with substantial parity asymmetry, while maintaining the initial matter power spectrum unchanged. From the parity broken initial condition and halos evolved from it, we construct the initial spin and halo spin fields, respectively. Focusing on the helicity of these vector fields, we detect substantial asymmetry in the initial spin field as a consequence of parity violation in the primordial vector fossil. In addition, we discover that over $50\%$ of the primordial asymmetry in the initial spin field remains in the late-time halo spin field on a range of scales. Given the tight correlation between halo spins and observable galaxy spins, we expect to detect the current amplitude of vectorial parity asymmetry potentially up to $16\sigma$-level in observation, when utilizing galaxy samples from DESI BGS. Our findings demonstrate that the primordial imprints of vectorial parity violation persist through non-linear gravitational evolution, highlighting the reliability of galaxy spin as a sensitive probe for testing the vectorial parity-invariance in the early Universe., Comment: 5 pages, 3 figures. Submitted to PRL

The Super-Kamiokande and T2K collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7(16.3) \times 10^{20}$ protons on target in (anti)neutrino mode, the analysis finds a 1.9$\sigma$ exclusion of CP-conservation (defined as $J_{CP}=0$) and a preference for the normal mass ordering., Comment: 12 pages, 4 figures

We studied the optical variability of 241 BL Lacs and 83 flat-spectrum radio quasars (FSRQ) from the 4LAC catalog using data from the Tomo-e Gozen Northern Sky Transient Survey, with $\sim$ 50 epochs per blazar on average. We excluded blazars whose optical variability may be underestimated due to the influence of their host galaxy, based on their optical luminosity ($L_O$). FSRQs with $\gamma$-ray photon index greater than 2.6 exhibit very low optical variability, and their distribution of standard deviation of repeated photometry is significantly different from that of the other FSRQs (KS test P value equal to $5 \times 10^{-6}$ ). Among a sample of blazars at any particular cosmological epoch, those with lower $\gamma$-ray luminosity ($L_\gamma$) tend to have lower optical variability, and those FSRQs with $\gamma$-ray photon index greater than 2.6 tend to have low $L_\gamma$. We also measured the structure function of optical variability and found that the amplitude of the structure function for FSRQs is higher than previously measured and higher than that of BL Lacs at multiple time lags. Additionally, the amplitude of the structure function of FSRQs with high $\gamma$-ray photon index is significantly lower than that of FSRQs with low $\gamma$-ray photon index. The structure function of FSRQs of high $\gamma$-ray photon index shows a characteristic timescale of more than 10 days, which may be the variability timescale of the accretion disk. In summary, we infer that the optical component of FSRQs with high $\gamma$-ray photon index may be dominated by the accretion disk., Comment: 22 pages, 13 figures

Despite proposing a quantum generative model for time series that successfully learns correlated series with multiple Brownian motions, the model has not been adapted and evaluated for financial problems. In this study, a time-series generative model was applied as a quantum generative model to actual financial data. Future data for two correlated time series were generated and compared with classical methods such as long short-term memory and vector autoregression. Furthermore, numerical experiments were performed to complete missing values. Based on the results, we evaluated the practical applications of the time-series quantum generation model. It was observed that fewer parameter values were required compared with the classical method. In addition, the quantum time-series generation model was feasible for both stationary and nonstationary data. These results suggest that several parameters can be applied to various types of time-series data., Comment: 12 pages

We present a criteria affirming the existence of discrete ground states of the Dirac operators which describe the fermion scattering on topological solitons in the nonlinear $O(3)$ $\sigma$-model. Additionally, we investigate a sufficient condition that elucidates the phenomenon of supersymmetry breaking within the supersymmetric quantum mechanics associated with this Dirac operator., Comment: 12 pages

Topological flat bands have gained extensive interest as a platform for exploring the interplay between nontrivial band topology and correlation effects. In recent studies, strongly correlated phenomena originating from a topological flat band were discussed on a periodically 1/6-depleted honeycomb lattice, but the fundamental topological nature associated with this lattice structure remains unexplored. Here we study the band structure and topological phase diagram for the Haldane model on this lattice, which we call the Bishamon-kikko lattice. We also extend our study to the model connecting the Bishamon-kikko and honeycomb lattices. We show that these models exhibit richer topological characteristics compared to the original Haldane model on the honeycomb lattice, such as topological insulating states with higher Chern numbers, metallic states with nontrivial band topology even at commensurate electron fillings, and metal-insulator transitions between them.7 Our findings offer a playground of correlated topological phenomena and stimulate their realization in a variety of two-dimensional systems, such as van der Waals materials, graphene nanostructures, and photonic crystals., Comment: 7 pages, 5 figures

Many organizations use algorithms that have a disparate impact, i.e., the benefits or harms of the algorithm fall disproportionately on certain social groups. Addressing an algorithm's disparate impact can be challenging, however, because it is often unclear whether it is possible to reduce this impact without sacrificing other objectives of the organization, such as accuracy or profit. Establishing the improvability of algorithms with respect to multiple criteria is of both conceptual and practical interest: in many settings, disparate impact that would otherwise be prohibited under US federal law is permissible if it is necessary to achieve a legitimate business interest. The question is how a policy-maker can formally substantiate, or refute, this "necessity" defense. In this paper, we provide an econometric framework for testing the hypothesis that it is possible to improve on the fairness of an algorithm without compromising on other pre-specified objectives. Our proposed test is simple to implement and can be applied under any exogenous constraint on the algorithm space. We establish the large-sample validity and consistency of our test, and illustrate its practical application by evaluating a healthcare algorithm originally considered by Obermeyer et al. (2019). In this application, we reject the null hypothesis that it is not possible to reduce the algorithm's disparate impact without compromising the accuracy of its predictions.

Gravitational waves (GWs) may be produced by various mechanisms in the early universe. In particular, if parity is violated, it may lead to the production of parity-violating GWs. In this paper, we focus on GWs on the scale of the large-scale structure. Since GWs induce tidal deformations of the shape of galaxies, one can extract such GW signals by observing images of galaxies in galaxy surveys. Conventionally the detection of such signals is discussed by considering the three-dimensional power spectra of the $E/B$-modes. Here, we develop a complementary new technique to estimate the contribution of GWs to the tidal force tensor field projected on the celestial sphere, which is a directly observable quantity. We introduce two two-dimensional vector fields constructed by taking the divergence and curl of the projected tidal field in three dimensions. Their auto-correlation functions naturally contain contributions of the scalar-type tidal field. However, we find that the divergence of the curl of the projected tidal field, which is a pseudo-scalar quantity, is free from the scalar contribution and thus enables us to extract GW signals. We also find that we can detect parity-violating signals in the GWs by observing the nonzero cross-correlation between the divergence of the projected tidal field and the curl of it. It roughly corresponds to measuring the cross-power spectrum of E and B-modes, but these are complementary to each other in the sense that our estimator can be naturally defined locally in position space. Finally we present expressions of the correlation functions in the form of Fourier integrals, and discuss the properties of the kernels specific to the GW case, which we call the overlap reduction function, borrowing the terminology used in the pulsar timing array experiments., Comment: 25 pages, 3 figures, accepted in JCAP

Critical phenomena, in which various physical quantities exhibit power laws, have been widely observed in nature and played a central role in physics. They generated the concept of universality class, which origin is elucidated by the renormalization group (RG) theory and which has guided the recent development of physics. Accordingly, identifying a rich variety of universality class is a major issue in modern physics. Here, we report that a daily phenomenon, similar to a drop falling from a faucet, possesses a strikingly close analogy with critical phenomena, with this version remarkably revealing the existence of an uncountably infinite number of universality classes. The key for our present findings is the confinement of a system into a thin cell, in which we observe the dynamics of air-liquid interface formed by entrained air into viscous liquid by a solid disk. The entrained air eventually detaches from the disk with or without breakup involving change in topology. While the time development of the interface shape is self-similar with characteristic length scales exhibiting power laws as in the case of non-confined previous studies, we here found that the observed self-similar shape corresponds to a solution to the governing equations, which we show a stable fixed point of the RG flow by combining a RG analysis and the dynamical system description (DSD) developed for singular dynamics in applied mathematics. We thus demonstrate a striking analogy with critical phenomena, showing critical exponents that define a universality class depend on "continuous numbers" characterizing the confinement. This is in contrast with the conventional critical phenomena, in which a class is defined by "discrete numbers." Our results open a new avenue for our understanding of critical phenomena, RG, and DSD, which impacts on the study of singular dynamics widely observed in nature.

High harmonic generation (HHG) is a striking phenomenon, which reflects the ultrafast dynamics of electrons. Recently, it has been demonstrated that HHG can be used to reconstruct not only the energy band structure but also the geometric structure characterized by the Berry curvature. Here, we numerically investigate HHG arising from electrons coupled with a topological spin texture in a spin scalar chiral state where time reversal symmetry is broken. In this system, a sign change in scalar chirality alters the sign of the Berry curvature while keeping the energy band structure unchanged, allowing us to discuss purely geometrical effects on HHG. Notably, we found that, when the optical frequency is significantly lower than the energy gap, the sign of scalar chirality largely affects the longitudinal response parallel to the optical field rather than the transverse response. Our analysis suggests that this can be attributed to interband currents induced by the recombination of electron-hole pairs whose real-space trajectories are modulated by the anomalous velocity term., Comment: 17 pages, 16 figures

Graph augmentation has received great attention in recent years for graph contrastive learning (GCL) to learn well-generalized node/graph representations. However, mainstream GCL methods often favor randomly disrupting graphs for augmentation, which shows limited generalization and inevitably leads to the corruption of high-level graph information, i.e., the graph community. Moreover, current knowledge-based graph augmentation methods can only focus on either topology or node features, causing the model to lack robustness against various types of noise. To address these limitations, this research investigated the role of the graph community in graph augmentation and figured out its crucial advantage for learnable graph augmentation. Based on our observations, we propose a community-invariant GCL framework to maintain graph community structure during learnable graph augmentation. By maximizing the spectral changes, this framework unifies the constraints of both topology and feature augmentation, enhancing the model's robustness. Empirical evidence on 21 benchmark datasets demonstrates the exclusive merits of our framework. Code is released on Github (https://github.com/ShiyinTan/CI-GCL.git)., Comment: This paper is accepted by ICML-2024

Active learning seeks to achieve strong performance with fewer training samples. It does this by iteratively asking an oracle to label new selected samples in a human-in-the-loop manner. This technique has gained increasing popularity due to its broad applicability, yet its survey papers, especially for deep learning-based active learning (DAL), remain scarce. Therefore, we conduct an advanced and comprehensive survey on DAL. We first introduce reviewed paper collection and filtering. Second, we formally define the DAL task and summarize the most influential baselines and widely used datasets. Third, we systematically provide a taxonomy of DAL methods from five perspectives, including annotation types, query strategies, deep model architectures, learning paradigms, and training processes, and objectively analyze their strengths and weaknesses. Then, we comprehensively summarize main applications of DAL in Natural Language Processing (NLP), Computer Vision (CV), and Data Mining (DM), etc. Finally, we discuss challenges and perspectives after a detailed analysis of current studies. This work aims to serve as a useful and quick guide for researchers in overcoming difficulties in DAL. We hope that this survey will spur further progress in this burgeoning field., Comment: This paper is accepted by IEEE Transactions on Neural Networks and Learning Systems

Speech emotion recognition (SER) has garnered increasing attention due to its wide range of applications in various fields, including human-machine interaction, virtual assistants, and mental health assistance. However, existing SER methods often overlook the information gap between the pre-training speech recognition task and the downstream SER task, resulting in sub-optimal performance. Moreover, current methods require much time for fine-tuning on each specific speech dataset, such as IEMOCAP, which limits their effectiveness in real-world scenarios with large-scale noisy data. To address these issues, we propose an active learning (AL)-based fine-tuning framework for SER, called \textsc{After}, that leverages task adaptation pre-training (TAPT) and AL methods to enhance performance and efficiency. Specifically, we first use TAPT to minimize the information gap between the pre-training speech recognition task and the downstream speech emotion recognition task. Then, AL methods are employed to iteratively select a subset of the most informative and diverse samples for fine-tuning, thereby reducing time consumption. Experiments demonstrate that our proposed method \textsc{After}, using only 20\% of samples, improves accuracy by 8.45\% and reduces time consumption by 79\%. The additional extension of \textsc{After} and ablation studies further confirm its effectiveness and applicability to various real-world scenarios. Our source code is available on Github for reproducibility. (https://github.com/Clearloveyuan/AFTER)., Comment: Accepted by Journal of Natural Language Processing. arXiv admin note: text overlap with arXiv:2310.00283

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/