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

This study explores the stabilization mechanisms of concentrated emulsions with tunable morphology using amphiphilic polymer-grafted nanoparticles (PGNPs). We employ coarse-grained molecular simulations to investigate concentrated oil-in-water emulsions stabilized by partially hydrolyzed poly(vinyl alcohol)-grafted polymethylmethacrylate (PMMA) particles. Two grafting architectures were examined: hydrophilic-hydrophobic (AB-type) diblock PGNPs and reverse BA-type diblock PGNPs. Our findings reveal that AB-type diblock PGNPs tend to aggregate, leading to droplet-droplet coalescence. In contrast, BA-type diblock PGNPs disperse effectively in the water phase, stabilizing robust emulsion through a space-filling mechanism. The study further demonstrates that the stability and morphology of the emulsions can be tuned by varying the number of PGNPs. Our results suggest that BA-type diblock PGNPs are more effective in stabilizing concentrated emulsions, offering insights for the design of novel emulsifiers in industrial applications., Comment: 10 pages, 5 figures including TOC Graphic

Randomization is a powerful tool that endows algorithms with remarkable properties. For instance, randomized algorithms excel in adversarial settings, often surpassing the worst-case performance of deterministic algorithms with large margins. Furthermore, their success probability can be amplified by simple strategies such as repetition and majority voting. In this paper, we enhance deep neural networks, in particular transformer models, with randomization. We demonstrate for the first time that randomized algorithms can be instilled in transformers through learning, in a purely data- and objective-driven manner. First, we analyze known adversarial objectives for which randomized algorithms offer a distinct advantage over deterministic ones. We then show that common optimization techniques, such as gradient descent or evolutionary strategies, can effectively learn transformer parameters that make use of the randomness provided to the model. To illustrate the broad applicability of randomization in empowering neural networks, we study three conceptual tasks: associative recall, graph coloring, and agents that explore grid worlds. In addition to demonstrating increased robustness against oblivious adversaries through learned randomization, our experiments reveal remarkable performance improvements due to the inherently random nature of the neural networks' computation and predictions.

Reinforcement Learning (RL) offers a fundamental framework for discovering optimal action strategies through interactions within unknown environments. Recent advancement have shown that the performance and applicability of RL can significantly be enhanced by exploiting a population of agents in various ways. Zeroth-Order Optimization (ZOO) leverages an agent population to estimate the gradient of the objective function, enabling robust policy refinement even in non-differentiable scenarios. As another application, Genetic Algorithms (GA) boosts the exploration of policy landscapes by mutational generation of policy diversity in an agent population and its refinement by selection. A natural question is whether we can have the best of two worlds that the agent population can have. In this work, we propose Ancestral Reinforcement Learning (ARL), which synergistically combines the robust gradient estimation of ZOO with the exploratory power of GA. The key idea in ARL is that each agent within a population infers gradient by exploiting the history of its ancestors, i.e., the ancestor population in the past, while maintaining the diversity of policies in the current population as in GA. We also theoretically reveal that the populational search in ARL implicitly induces the KL-regularization of the objective function, resulting in the enhanced exploration. Our results extend the applicability of populational algorithms for RL., Comment: 16pages, 3 figures

We report the discovery of a hyperluminous type 1 quasar (eFEDS J082826.9-013911; eFEDSJ0828-0139) at $z_{\rm spec}$ = 1.622 with a super-Eddington ratio ($\lambda_{\rm Edd}$). We perform the optical spectroscopic observations with KOOLS-IFU on the Seimei Telescope. The black hole mass ($M_{\rm BH}$) based on the single-epoch method with MgII $\lambda$2798 is estimated to be $M_{\rm BH} = (6.2 \pm 1.2) \times 10^8$ $M_{\odot}$. To measure the precise infrared luminosity ($L_{\rm IR}$), we obtain submillimeter data taken by SCUBA-2 on JCMT and conduct the spectral energy distribution analysis with X-ray to submillimeter data. We find that $L_{\rm IR}$ of eFEDSJ0828-0139 is $L_{\rm IR} = (6.8 \pm 1.8) \times 10^{13}$ $L_{\odot}$, confirming the existence of a hypeluminous infrared galaxy (HyLIRG). $\lambda_{\rm Edd}$ is estimated to be $\lambda_{\rm Edd} = 3.6 \pm 0.7$, making it one of the quasars with the highest BH mass accretion rate at cosmic noon., Comment: 9 pages, 3 figures, and 3 tables, accepted for publication in PASJ

We apply the HanleRT Tenerife Inversion Code to the spectro-polarimetric observations obtained by the Chromospheric LAyer SpectroPolarimeter. This suborbital space experiment measured the variation with wavelength of the four Stokes parameters in the near-ultraviolet spectral region of the Mg II h & k lines over a solar disk area containing part of an active region plage and the edge of a sunspot penumbra. We infer the stratification of the temperature, the electron density, the line of-sight velocity, the micro-turbulent velocity, and the longitudinal component of the magnetic field from the observed intensity and circular polarization profiles. The inferred model atmosphere shows larger temperature and electron density in the plage and the superpenumbra regions than in the quiet regions. The shape of the plage region in terms of its brightness is similar to the pattern of the inferred longitudinal component of the magnetic field in the chromosphere, as well as to that of the overlying moss observed by AIA in the 171 A band, which suggests a similar magnetic origin for the heating in both the plage and the moss region. Moreover, this heating is particularly significant in the regions with larger inferred magnetic flux. In contrast, in the superpenumbra, the regions with larger electron density and temperature are usually found in between these regions with larger magnetic flux, suggesting that the details of the heating mechanism in the chromosphere of the superpenumbra may be different to those in the plage, but with the magnetic field still playing a key role., Comment: Accepted for publication in the Astrophysical Journal

We develop an energy calculation algorithm leveraging quantum phase difference estimation (QPDE) scheme and a tensor-network-based unitary compression method in the preparation of superposition states and time-evolution gates. Alongside its efficient implementation, this algorithm reduces depolarization noise affections exponentially. We demonstrated energy gap calculations for one-dimensional Hubbard models on IBM superconducting devices using circuits up to 32-system (plus one-ancilla) qubits, a five-fold increase over previous QPE demonstrations, at the 7242 controlled-Z gate level of standard transpilation, keying a Q-CTRL error suppression module. Additionally, we propose a technique towards molecular executions using spatial orbital localization and index sorting, verified by an eight-qubit butadiene simulation. Since QPDE can handle the same objectives as QPE, our algorithm represents a leap forward in quantum computing on real devices., Comment: 24 pages

We present the first measurement of nuclear recoils from solar $^8$B neutrinos via coherent elastic neutrino-nucleus scattering with the XENONnT dark matter experiment. The central detector of XENONnT is a low-background, two-phase time projection chamber with a 5.9\,t sensitive liquid xenon target. A blind analysis with an exposure of 3.51\,t$\times$y resulted in 37 observed events above 0.5\,keV, with ($26.4^{+1.4}_{-1.3}$) events expected from backgrounds. The background-only hypothesis is rejected with a statistical significance of 2.73\,$\sigma$. The measured $^8$B solar neutrino flux of $(4.7_{-2.3}^{+3.6})\times 10^6\,\mathrm{cm}^{-2}\mathrm{s}^{-1}$ is consistent with results from dedicated solar neutrino experiments. The measured neutrino flux-weighted CE$\nu$NS cross-section on Xe of $(1.1^{+0.8}_{-0.5})\times10^{-39}\,\mathrm{cm}^2$ is consistent with the Standard Model prediction. This is the first direct measurement of nuclear recoils from solar neutrinos with a dark matter detector.

We study the extension of the chromo-natural inflation model by incorporating nonminimal coupling between the axion field and gravity. Nonminimal coupling is introduced so that it enhances friction in the axion's equation of motion and thus supports slow-roll inflation. This enhanced friction effectively delays the activation of the gauge field, thereby preventing the overproduction of gravitational waves in the CMB scale. We extend previous results by describing the nonminimal coupling in a general and unifying way utilizing Horndeski gravity. This allows us to explore systematically and comprehensively possible enhanced friction models of chromo-natural inflation consistent with observations. We find a novel enhanced friction model that shows better agreement (within 1$\sigma$) with CMB measurements than the previous nonminimally coupled chromo-natural inflation model. The gravitational-wave spectrum starts to rise at some wavenumber due to retarded activation of the gauge field in the late stage of inflation. We show how one can identify the wavenumber at which this occurs based on the background evolution and present a universal analytic formula for the gravitational-wave spectrum that can be used for any enhanced friction model of chromo-natural inflation., Comment: 22 pages, 7 figures

In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on fund management, fund managers prepare management reports that summarize these monthly reports every six months or once a year. The preparation of fund reports is a labor-intensive and time-consuming task. Therefore, in this paper, we tackle investment summarization from monthly reports using transformer-based models. There are two main types of summarization methods: extractive summarization and abstractive summarization, and this study constructs both methods and examines which is more useful in summarizing investment reports.

Let $p,q$ be two integers with $p\geq q$. Given a finite graph $F$ with no isolated vertices, the generalized Ramsey achievement game of $F$ on the complete graph $K_n$, denoted by $(p,q;K_n,F,+)$, is played by two players called Alice and Bob. In each round, Alice firstly chooses $p$ uncolored edges $e_1,e_2,...,e_p$ and colors it blue, then Bob chooses $q$ uncolored edge $f_1,f_2,...,f_q$ and colors it red; the player who can first complete the formation of $F$ in his (or her) color is the winner. The generalized achievement number of $F$, denoted by ${a}(p,q;F)$ is defined to be the smallest $n$ for which Alice has a winning strategy. If $p=q=1$, then it is denoted by ${a}(F)$, which is the classical achievement number of $F$ introduced by Harary in 1982. If Alice aims to form a blue $F$, and the goal of Bob is to try to stop him, this kind of game is called the first player game by Bollob\'{a}s. Let ${a}^*(F)$ be the smallest positive integer $n$ for which Alice has a winning strategy in the first player game. A conjecture due to Harary states that the minimum value of ${a}(T)$ is realized when $T$ is a path and the maximum value of ${a}(T)$ is realized when $T$ is a star among all trees $T$ of order $n$. He also asked which graphs $F$ satisfy $a^*(F)=a(F)$? In this paper, we proved that $n\leq {a}(p,q;T)\leq n+q\left\lfloor (n-2)/p \right\rfloor$ for all trees $T$ of order $n$, and obtained a lower bound of ${a}(p,q;K_{1,n-1})$, where $K_{1,n-1}$ is a star. We proved that the minimum value of ${a}(T)$ is realized when $T$ is a path which gives a positive solution to the first part of Harary's conjecture, and ${a}(T)\leq 2n-2$ for all trees of order $n$. We also proved that for $n\geq 3$, we have $2n-2-\sqrt{(4n-8)\ln (4n-4)}\leq a(K_{1,n-1})\leq 2n-2$ with the help of a theorem of Alon, Krivelevich, Spencer and Szab\'o. We proved that $a^*(P_n)=a(P_n)$ for a path $P_n$., Comment: 13 pages

This study proposes a method for radar-based identification of individuals using a combination of their respiratory and heartbeat features. In the proposed method, the target individual's respiratory features are extracted using the modified raised-cosine-waveform model and their heartbeat features are extracted using the mel-frequency cepstral analysis technique. To identify a suitable combination of features and a classifier, we compare the performances of nine methods based on various combinations of three feature vectors with three classifiers. The accuracy of the proposed method in performing individual identification is evaluated using a 79-GHz millimeter-wave radar system with an antenna array in two experimental scenarios and we demonstrate the importance of use of the combination of the respiratory and heartbeat features in achieving accurate identification of individuals. The proposed method achieves accuracy of 96.33% when applied to a five-day dataset of six participants and 99.39% when applied to a public one-day dataset of thirty participants., Comment: 11 pages, 11 figures, 5 tables. This work is going to be submitted to the IEEE for possible publication

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 an 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

The neutron-rich unbound fluorine isotope $^{30}$F$_{21}$ has been observed for the first time by measuring its neutron decay at the SAMURAI spectrometer (RIBF, RIKEN) in the quasi-free proton knockout reaction of $^{31}$Ne nuclei at 235 MeV/nucleon. The mass and thus one-neutron-separation energy of $^{30}$F has been determined to be $S_n = -472\pm 58 \mathrm{(stat.)} \pm 33 \mathrm{(sys.)}$ keV from the measurement of its invariant-mass spectrum. The absence of a sharp drop in $S_n$($^{30}$F) shows that the ``magic'' $N=20$ shell gap is not restored close to $^{28}$O, which is in agreement with our shell-model calculations that predict a near degeneracy between the neutron $d$ and $fp$ orbitals, with the $1p_{3/2}$ and $1p_{1/2}$ orbitals becoming more bound than the $0f_{7/2}$ one. This degeneracy and reordering of orbitals has two potential consequences: $^{28}$O behaves like a strongly superfluid nucleus with neutron pairs scattering across shells, and both $^{29,31}$F appear to be good two-neutron halo-nucleus candidates., Comment: 9 pages, 2 figures, accepted for publication in Physical Review Letters

Benchmarking estimation and its risk evaluation is a practically important issue in small area estimation. While hierarchical Bayesian methods have been widely adopted in small area estimation, a unified Bayesian approach to benchmarking estimation has not been fully discussed. This work employs an entropic tilting method to modify the posterior distribution of the small area parameters to meet the benchmarking constraint, which enables us to obtain benchmarked point estimation as well as reasonable uncertainty quantification. Using conditionally independent structures of the posterior, we first introduce general Monte Carlo methods for obtaining a benchmarked posterior and then show that the benchmarked posterior can be obtained in an analytical form for some representative small area models. We demonstrate the usefulness of the proposed method through simulation and empirical studies., Comment: 26 pages

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

Collective migration is a phenomenon observed in various biological systems, where the cooperation of multiple cells leads to complex functions beyond individual capabilities, such as in immunity and development. A distinctive example is cell populations that not only ascend attractant gradient originating from targets, such as damaged tissue, but also actively modify the gradient, through their own production and degradation. While the optimality of single-cell information processing has been extensively studied, the optimality of the collective information processing that includes gradient sensing and gradient generation, remains underexplored. In this study, we formulated a cell population that produces and degrades an attractant while exploring the environment as an agent population performing distributed reinforcement learning. We demonstrated the existence of optimal couplings between gradient sensing and gradient generation, showing that the optimal gradient generation qualitatively differs depending on whether the gradient sensing is logarithmic or linear. The derived dynamics have a structure homogeneous to the Keller-Segel model, suggesting that cell populations might be learning. Additionally, we showed that the distributed information processing structure of the agent population enables a proportion of the population to robustly accumulate at the target. Our results provide a quantitative foundation for understanding the collective information processing mediated by attractants in extracellular environments.

Wearable assistive robots (WR) for the lower extremity are extensively documented in literature. Various interfaces have been designed to control these devices during gait and balance activities. However, achieving seamless and intuitive control requires accurate modeling of the human neuromusculoskeletal (NMSK) system. Such modeling enables WR to anticipate user intentions and determine the necessary joint assistance. Despite the existence of controllers interfacing with the NMSK system, robust and generalizable techniques across different tasks remain scarce. Designing these novel controllers necessitates the combined expertise of neurophysiologists, who understand the physiology of movement initiation and generation, and biomechatronic engineers, who design and control devices that assist movement. This paper aims to bridge the gaps between these fields by presenting a primer on key concepts and the current state of the science in each area. We present three main sections: the neuromechanics of locomotion, neuromechanical models of movement, and existing neuromechanical controllers used in WR. Through these sections, we provide a comprehensive overview of seminal studies in the field, facilitating collaboration between neurophysiologists and biomechatronic engineers for future advances in wearable robotics for locomotion.

We study the influence of two mutual friction models on quantized vortices and normal fluid using two-way coupled simulations of superfluid $^4$He. The normal fluid is affected by quantized vortices via mutual friction. A previous study [Y. Tang, et al. Nat. Commun. 14, 2941 (2023)] compared the time evolutions of the vortex ring radius and determined that the self-consistent two-way coupled mutual friction (S2W) model yielded better agreement with the experimental results than the two-way coupled mutual friction (2W) model whose model parameters were determined through experiments with rotating superfluid helium. In this study, we compare the two models in more detail in terms of the quantized vortex ring propagation, reconnection, and thermal counterflow. We found that the S2W model exhibits better results than the 2W model on the microscopic scale near a quantized vortex, such as during quantized vortex ring propagation and reconnection, although the S2W model requires a higher spatial resolution. For complex flows such as a thermal counterflow, the 2W model can be applied even to a low-resolution flow while maintaining the anisotropic normal fluid velocity fluctuations. In contrast, the 2W model predicts lower normal fluid velocity fluctuations than the S2W model. The two models show probability density functions with $- 3$ power-law tails for the normal fluid velocity fluctuations.

Automated vehicles need to estimate tire-road friction information, as it plays a key role in safe trajectory planning and vehicle dynamics control. Notably, friction is not solely dependent on road surface conditions, but also varies significantly depending on the tire temperature. However, tire parameters such as the friction coefficient have been conventionally treated as constant values in automated vehicle motion planning. This paper develops a simple thermodynamic model that captures tire friction temperature variation. To verify the model, it is implemented into trajectory planning for automated drifting - a challenging application that requires leveraging an unstable, drifting equilibrium at the friction limits. The proposed method which captures the hidden tire dynamics provides a dynamically feasible trajectory, leading to more precise tracking during experiments with an LQR (Linear Quadratic Regulator) controller., Comment: This manuscript was accepted from IEEE Intelligent Vehicle Symposium (IV 2024) and will be published late August

Many tasks can be composed from a few independent components. This gives rise to a combinatorial explosion of possible tasks, only some of which might be encountered during training. Under what circumstances can transformers compositionally generalize from a subset of tasks to all possible combinations of tasks that share similar components? Here we study a modular multitask setting that allows us to precisely control compositional structure in the data generation process. We present evidence that transformers learning in-context struggle to generalize compositionally on this task despite being in principle expressive enough to do so. Compositional generalization becomes possible only when introducing a bottleneck that enforces an explicit separation between task inference and task execution., Comment: ICML 2024 workshop on Next Generation of Sequence Modeling Architectures

Soft robots have gained significant attention due to their flexibility and safety, particularly in human-centric applications. The co-design of structure and controller in soft robotics has presented a longstanding challenge owing to the complexity of the dynamics involved. Despite some pioneering work dealing with the co-design of soft robot structures and actuation, design freedom has been limited by stochastic design search approaches. This study proposes the simultaneous optimization of structure and controller for soft robots in locomotion tasks, integrating topology optimization-based structural design with neural network-based feedback controller design. Here, the feedback controller receives information about the surrounding terrain and outputs actuation signals that induce the expansion and contraction of the material. We formulate the simultaneous optimization problem under uncertainty in terrains and construct an optimization algorithm that utilizes automatic differentiation within topology optimization and neural networks. We present numerical experiments to demonstrate the validity and effectiveness of our proposed method., Comment: 23 pages, 22 figures

The extreme outer Galaxy (EOG), which we define as the region of the Milky Way with a galactocentric radius of more than 18 kpc, provides an excellent opportunity to study star formation in an environment significantly different from that in the solar neighborhood because of its lower metallicity and lower gas density. We carried out near- and mid-infrared (NIR and MIR) imaging observations toward two star-forming clusters located in the EOG using JWST NIRCam and MIRI with nine filters: F115W, F150W, F200W, F350W, F405N, F444W, F770W, F1280W, and F2100W. In this paper, we present an overview of the observations, data reduction, and initial results. The NIR sensitivity is approximately 10--80 times better than our previous observation with the Subaru 8.2 m telescope. Accordingly, the mass detection limit reaches to about 0.01--0.05 $M_\odot$, which is about 10 times better than the previous observations. At MIR wavelengths, the high sensitivity and resolution data enable us to resolve individual young stellar objects in such a distant region for the first time. The mass detection limit at MIR F770W filter reaches about 0.1--0.3 $M_\odot$. With these new observations, we have identified components of the clusters that previous surveys did not detect, including class 0 candidates, outflow/jet components, and distinctive nebular structures. These data will enable us to investigate the properties of star formation in the EOG at the same depth of detail as previous observations of star formation in the solar neighborhood., Comment: 39 pages, 21 figures, and 5 tables. Accepted for publication in Astronomical Journal. The figure with the full resolution is shown in the publication in the Astronomical Journal

To understand and control the dynamics of coupled oscillators, it is important to reveal the structure of the interaction network from observed data. While various techniques have been developed for inferring the network of asynchronous systems, it remains challenging to infer the network of synchronized oscillators without external stimulations. In this study, we develop a method for non-invasively inferring the network of synchronized and/or de-synchronized oscillators. An approach to network inference would be to fit the data to a set of differential equations describing the dynamics of phase oscillators. However, we show that this method fails to infer the true network due to the problems that arise when we use short-time phase differences. Therefore, we propose a method based on the circle map, which describes the phase change in one oscillatory cycle. We demonstrate the efficacy of the proposed method through the successful inference of the network structure from simulated data of limit cycle oscillator models. Our method provides a unified and concise framework for network estimation for a wide class of oscillator systems., Comment: 20 pages, 5 figures

Saturated fatty acids are abundant organic compounds in oceans and sea sprays. Their photochemical reactions induced by solar radiation have recently been discovered as an abiotic source of volatile organic compounds, which serve as precursors of secondary organic aerosols. However, photoabsorption of wavelengths longer than 250 nm in liquid saturated fatty acids remains unexplained, despite being first reported in 1931. Here we demonstrate that the previously reported absorption of wavelengths longer than 250 nm by liquid nonanoic acid [CH3(CH2)7COOH)] originates from traces of impurities (0.1% at most) intrinsically contained in nonanoic acid reagents. Absorption cross sections of nonanoic acid newly obtained here indicate that the upper limit of its photolysis rate is three-to-five orders of magnitude smaller than those for atmospherically relevant carbonyl compounds.

The strength distributions of the Isoscalar Giant Monopole Resonance (ISGMR) and Isoscalar Giant Quadrupole Resonance (ISGQR) in 142,146-150Nd have been determined via inelastic alpha-particle scattering with the Grand Raiden (GR) Spectrometer at the Research Center for Nuclear Physics (RCNP), Japan. In the deformed nuclei 146-150Nd, the ISGMR strength distributions exhibit a splitting into two components, while the nearly spherical nucleus 142Nd displays a single peak in the ISGMR strength distribution. A noteworthy achievement in this study is the first-time detection of overtones in the Isoscalar Giant Quadrupole Resonance (ISGQR) strength distributions within Nd isotopes at an excitation energy around 25 MeV obtained through Multipole Decomposition Analysis (MDA)., Comment: Accepted for publication in Physics Letters B

Coupon allocation drives customer purchases and boosts revenue. However, it presents a fundamental trade-off between exploiting the current optimal policy to maximize immediate revenue and exploring alternative policies to collect data for future policy improvement via off-policy evaluation (OPE). While online A/B testing can validate new policies, it risks compromising short-term revenue. Conversely, relying solely on an exploitative policy hinders the ability to reliably estimate and enhance future policies. To balance this trade-off, we propose a novel approach that combines a model-based revenue maximization policy and a randomized exploration policy for data collection. Our framework enables flexibly adjusting the mixture ratio between these two policies to optimize the balance between short-term revenue and future policy improvement. We formulate the problem of determining the optimal mixture ratio between a model-based revenue maximization policy and a randomized exploration policy for data collection. We empirically verified the effectiveness of the proposed mixed policy using both synthetic and real-world data. Our main contributions are: (1) Demonstrating a mixed policy combining deterministic and probabilistic policies, flexibly adjusting the data collection vs. revenue trade-off. (2) Formulating the optimal mixture ratio problem as multi-objective optimization, enabling quantitative evaluation of this trade-off. By optimizing the mixture ratio, businesses can maximize revenue while ensuring reliable future OPE and policy improvement. This framework is applicable in any context where the exploration-exploitation trade-off is relevant.

The calcium isotopes are an ideal system to investigate the evolution of shell structure and magic numbers. Although the properties of surface nucleons in calcium have been well studied, probing the structure of deeply bound nucleons remains a challenge. Here, we report on the first measurement of unbound states in $^{53}$Ca and $^{55}$Ca, populated from \ts{54,56}Ca($p,pn$) reactions at a beam energy of around 216 MeV/nucleon at the RIKEN Radioactive Isotopes Beam Factory. The resonance properties, partial cross sections, and momentum distributions of these unbound states were analyzed. Orbital angular momentum $l$ assignments were extracted from momentum distributions based on calculations using the distorted wave impulse approximation (DWIA) reaction model. The resonances at excitation energies of 5516(41)\,keV in $^{53}$Ca and 6000(250)\,keV in $^{55}$Ca indicate a significant $l$\, =\,3 component, providing the first experimental evidence for the $\nu 0f_{7/2}$ single-particle strength of unbound hole states in the neutron-rich Ca isotopes. The observed excitation energies and cross-sections point towards extremely localized and well separated strength distributions, with some fragmentation for the $\nu 0f_{7/2}$ orbital in $^{55}$Ca. These results are in good agreement with predictions from shell-model calculations using the effective GXPF1Bs interaction and \textit{ab initio} calculations and diverge markedly from the experimental distributions in the nickel isotones at $Z=28$., Comment: 13 pages, 7 figures

We investigate the tractability of a simple fusion of two fundamental structures on graphs, a spanning tree and a perfect matching. Specifically, we consider the following problem: given an edge-weighted graph, find a minimum-weight spanning tree among those containing a perfect matching. On the positive side, we design a simple greedy algorithm for the case when the graph is complete (or complete bipartite) and the edge weights take at most two values. On the negative side, the problem is NP-hard even when the graph is complete (or complete bipartite) and the edge weights take at most three values, or when the graph is cubic, planar, and bipartite and the edge weights take at most two values. We also consider an interesting variant. We call a tree strongly balanced if on one side of the bipartition of the vertex set with respect to the tree, all but one of the vertices have degree $2$ and the remaining one is a leaf. This property is a sufficient condition for a tree to have a perfect matching, which enjoys an additional property. When the underlying graph is bipartite, strongly balanced spanning trees can be written as matroid intersection, and this fact was recently utilized to design an approximation algorithm for some kind of connectivity augmentation problem. The natural question is its tractability in nonbipartite graphs. As a negative answer, it turns out NP-hard to test whether a given graph has a strongly balanced spanning tree or not even when the graph is subcubic and planar., Comment: 14 pages, 5 figures

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

We analyse ultra-deep JWST observations of the galaxy JADES-GS-z9-0 at z = 9.4327, and derive detailed stellar and interstellar medium (ISM) properties of this luminous (MUV=-20.43) high-redshift system. Complementary information from NIRCam imaging and NIRSpec (both low- and medium-resolution) spectroscopy reveal a compact system (Re ~110 pc) characterised by a steeply rising star formation history, which is reflected in the inferred young stellar age (t ~ 3 Myr, light-weighted), high star-formation rate surface density ({\Sigma}SFR ~ 72 M yr-1 kpc-2), high ionisation parameter (log(U) ~ -1.5), low metallicity (12+log(O/H) ~ 7.5), and low carbon-over-oxygen abundance ([C/O] = -0.64). Leveraging the detection of N iii]1750 we derive nitrogen-over-oxygen abundance ([N/O] ~ 0) higher than the plateau followed by low-redshift galaxies of similar metallicity, possibly revealing the imprint from (very) massive stars on the ISM enrichment and favouring a top-heavy Initial Mass Function (IMF) scenario. Massive stars powering a hard radiation field are also required to explain the rest-frame UV line ratios, though the presence of the high-excitation [Ne v]{\lambda}3426 emission line possibly hints at additional ionization from an AGN. We also report the tentative detection of Ly{\alpha} emission in the G140M spectrum, shifted by ~450 km/s redward of the systemic redshift. Combined with a modelling of the Ly{\alpha} spectral break, we rule out the presence of very high column densities of neutral gas pertaining to local absorbers, as well as any extended surrounding ionised bubble, suggesting that JADES-GS-z9-0 has not yet significantly contributed to cosmic Reionization., Comment: Submitted to A&A. Comments are welcome

Majorana fermions (MFs) in a topological superconductor exhibit anisotropic electromagnetic responses, called Majorana multipole responses, when MFs are degenerate under time-reversal and crystalline symmetries. In time-reversal symmetric systems, the Majorana multipole response relates to Cooper pair symmetry in the underlying superconducting material, which provides a way to identify pairing symmetries through surface-spin-sensitive measurements. Here, we extend the concept of Majorana multipole response to systems with magnetic point group symmetry that break time-reversal symmetry and clarify how the response of MFs includes information about underlying superconductors. From a topological classification of symmetry-protected MFs and an effective surface theory, we classify possible magnetic and electric responses for MFs, which manifests a direct connection to Cooper pair symmetry for a symmetry-enforced pair of MFs. Additionally, we find several time-reversal-even higher-order multipole responses, such as the quadrupole response, which are forbidden in time-reversal symmetric systems, whereby indicating breaking of time-reversal symmetry. The theory is applied to the odd-parity chiral superconductor UTe$_2$ and the ferromagnetic superconductor UCoGe, demonstrating the appearance of a magnetic quadrupole response on a surface., Comment: 21 pages, 5 figures

To investigate impact vaporization for planetary atmosphere formation, we have studied the thermodynamic state generated by the shock wave due to a high-velocity impact, called the shock field. We have carried out iSALE simulations for high-velocity vertical impacts using ANEOS for an equation-of-state (EoS) model. To understand the shock fields obtained from simulations, we have investigated the contribution of the thermal and cold terms in the EoS model on the Hugoniot curves. Although the thermal and cold terms are important for the pressure, the internal energy is mainly determined by the thermal term. We thus assume a simple EoS determined by the thermal term and then analytically derive the shock internal-energy field, which reproduces the results of simulations well. Using the analytical solution of internal energy and the Hugoniot curve, we have derived the shock pressure field analytically as well. The analytical solutions for internal energy and pressure are valid even for impact velocities as low as the sound speed. The solution is good for the vertical direction or within the angles of about 60 degrees. We have applied the solution to impact vaporization for the formation of planetary atmospheres. This gives good estimation of reformation of the planetary atmospheres of Earth sized planet., Comment: Accepted for publication in A&A

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

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

Quantum reservoir computing (QRC) is a highly promising computational paradigm that leverages quantum systems as a computational resource for nonlinear information processing. While its application to time-series analysis is eagerly anticipated, prevailing approaches suffer from the collapse of the quantum state upon measurement, resulting in the erasure of temporal input memories. Neither repeated initializations nor weak measurements offer a fundamental solution, as the former escalates time complexity while the latter restricts the information extraction from the Hilbert space. To address this issue, we propose a feedback-driven QRC framework. This methodology employs projective measurements on all qubits for unrestricted access to the quantum state, with the measurement outcomes subsequently fed back into the reservoir to restore the memory of prior inputs. We demonstrate that our QRC successfully acquires the fading-memory property through the feedback, a critical element in time-series processing. Notably, analysis of measurement trajectories reveal three distinct phases depending on the feedback strength, with the memory performance maximized at the edge of chaos. We also evaluate the predictive capabilities of our QRC, demonstrating its suitability for forecasting signals originating from quantum spin systems., Comment: 11 pages, 6 figures

The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/$c^2$ up to the TeV/$c^2$ scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals., Comment: 20 pages, 10 figures

Point clouds are a general format for representing realistic 3D objects in diverse 3D applications. Since point clouds have large data sizes, developing efficient point cloud compression methods is crucial. However, excessive compression leads to various distortions, which deteriorates the point cloud quality perceived by end users. Thus, establishing reliable point cloud quality assessment (PCQA) methods is essential as a benchmark to develop efficient compression methods. This paper presents an accurate full-reference point cloud quality assessment (FR-PCQA) method called full-reference quality assessment using support vector regression (FRSVR) for various types of degradations such as compression distortion, Gaussian noise, and down-sampling. The proposed method demonstrates accurate PCQA by integrating five FR-based metrics covering various types of errors (e.g., considering geometric distortion, color distortion, and point count) using support vector regression (SVR). Moreover, the proposed method achieves a superior trade-off between accuracy and calculation speed because it includes only the calculation of these five simple metrics and SVR, which can perform fast prediction. Experimental results with three types of open datasets show that the proposed method is more accurate than conventional FR-PCQA methods. In addition, the proposed method is faster than state-of-the-art methods that utilize complicated features such as curvature and multi-scale features. Thus, the proposed method provides excellent performance in terms of the accuracy of PCQA and processing speed. Our method is available from https://github.com/STAC-USC/FRSVR-PCQA., Comment: Source code: https://github.com/STAC-USC/FRSVR-PCQA

Point clouds in 3D applications frequently experience quality degradation during processing, e.g., scanning and compression. Reliable point cloud quality assessment (PCQA) is important for developing compression algorithms with good bitrate-quality trade-offs and techniques for quality improvement (e.g., denoising). This paper introduces a full-reference (FR) PCQA method utilizing spectral graph wavelets (SGWs). First, we propose novel SGW-based PCQA metrics that compare SGW coefficients of coordinate and color signals between reference and distorted point clouds. Second, we achieve accurate PCQA by integrating several conventional FR metrics and our SGW-based metrics using support vector regression. To our knowledge, this is the first study to introduce SGWs for PCQA. Experimental results demonstrate the proposed PCQA metric is more accurately correlated with subjective quality scores compared to conventional PCQA metrics.

We show that spin-singlet $s$-wave multi-band superconductors have a topological phase protected by rotation symmetry and time-reversal symmetry without spin-orbit coupling in two and three dimensions. This topological phase, an example of a representation-protected topological phase, has a $\mathbb{Z}_2$ topological index and is stable as long as the bands at the Fermi energy are formed by a doublet of orbital states with finite angular momenta. In the limit of weak superconducting pair potential, the $\mathbb{Z}_2$ index gives a Fermi-surface formula and is related to the winding number of three-dimensional strong topological superconductors of class CI. We present a model of a topological $s_{\pm}$-wave superconductor that has gapless surface states with a quadratic dispersion and suggest a connection with iron-based superconductors., Comment: 7+10 pages, 2+1 figures

A tensegrity-based system is a promising approach for dynamic exploration of uneven and unpredictable environments, particularly, space exploration. However, implementing such systems presents challenges in terms of intelligent aspects: state recognition, wireless monitoring, human interaction, and smart analyzing and advising function. Here, we introduce a 6-strut tensegrity integrate with 24 multimodal strain sensors by leveraging both deep learning model and large language models to realize smart tensegrity. Using conductive flexible tendons assisted by long short-term memory model, the tensegrity achieves the self-shape reconstruction without extern sensors. Through integrating the flask server and gpt-3.5-turbo model, the tensegrity autonomously enables to send data to iPhone for wireless monitoring and provides data analysis, explanation, prediction, and suggestions to human for decision making. Finally, human interaction system of the tensegrity helps human obtain necessary information of tensegrity from the aspect of human language. Overall, this intelligent tensegrity-based system with self-sensing tendons showcases potential for future exploration, making it a versatile tool for real-world applications.

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.

Transformers can under some circumstances generalize to novel problem instances whose constituent parts might have been encountered during training but whose compositions have not. What mechanisms underlie this ability for compositional generalization? By reformulating multi-head attention as a hypernetwork, we reveal that a low-dimensional latent code specifies key-query specific operations. We find empirically that this latent code is highly structured, capturing information about the subtasks performed by the network. Using the framework of attention as a hypernetwork we further propose a simple modification of multi-head linear attention that strengthens the ability for compositional generalization on a range of abstract reasoning tasks. In particular, we introduce a symbolic version of the Raven Progressive Matrices human intelligence test on which we demonstrate how scaling model size and data enables compositional generalization and gives rise to a functionally structured latent code in the transformer., Comment: Code available at https://github.com/smonsays/hypernetwork-attention

The newly updated \texttt{GIZMO} and \texttt{Simba} based simulation, \texttt{Simba-C}, with its new stellar feedback, chemical enrichment, and recalibrated AGN feedback, allows for a detailed study of the intragroup medium X-ray properties. We discuss the impact of various physical mechanisms, e.g. stellar and AGN feedback, and chemical enrichment, on the composition and the global scaling relations of nearby galaxy groups. We also study the evolution ($z=2$ to $0$) of the global properties for the $1\,\mathrm{keV}$ temperature groups. \texttt{Simba-C} shows improved consistent matching with the observations of all X-ray scaling relations compared to \texttt{Simba}. It is well known that AGN feedback has a significant influence on $L_{X,0.5-2.0}-T_{spec,corr}$, $S_{500/2500}-T_{spec,corr}$, and gas mass fractions, with our \texttt{Simba-C} results consistent with it. Our recalibrated AGN feedback strength also showed an additional improvement in gas entropy, which now aligns with CLoGS observations. The updated stellar feedback and chemical enrichment model is shown to play an important role in our understanding of the chemical abundance ratios and their evolution within galaxy groups. In particular, we find that \texttt{Simba-C} produces an increase in the amount of heavier elements (specifically Si and Fe) relative to O, compared to \texttt{Simba}., Comment: 20 pages, 13 figures, 2 tables, accepted by MNRAS on 6 June 2024

This paper proposes a new algorithm for learning accurate tree-based models while ensuring the existence of recourse actions. Algorithmic Recourse (AR) aims to provide a recourse action for altering the undesired prediction result given by a model. Typical AR methods provide a reasonable action by solving an optimization task of minimizing the required effort among executable actions. In practice, however, such actions do not always exist for models optimized only for predictive performance. To alleviate this issue, we formulate the task of learning an accurate classification tree under the constraint of ensuring the existence of reasonable actions for as many instances as possible. Then, we propose an efficient top-down greedy algorithm by leveraging the adversarial training techniques. We also show that our proposed algorithm can be applied to the random forest, which is known as a popular framework for learning tree ensembles. Experimental results demonstrated that our method successfully provided reasonable actions to more instances than the baselines without significantly degrading accuracy and computational efficiency., Comment: 27 pages, 10 figures, to appear in the 41st International Conference on Machine Learning (ICML 2024)

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: 10 pages, 3 figures

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/