Search

We studied the nonequilibrium dynamics of a cycling three-state Potts model using simulations and theory. This model can be tuned from thermal-equilibrium to far-from-equilibrium conditions. At low cycling energy, the homogeneous dominant state cycles via nucleation and growth, while spiral waves are formed at high energy. For large systems, a discontinuous transition occurs from these cyclic homogeneous phases to spiral waves, while the opposite transition is absent. Conversely, these two modes can coexist for small systems. The waves can be reproduced by a continuum theory, and the transition can be understood from the competition between nucleation and growth., Comment: 7 pages, 9 figures

We present a measurement of neutrino oscillation parameters with the Super-Kamiokande detector using atmospheric neutrinos from the complete pure-water SK I-V (April 1996-July 2020) data set, including events from an expanded fiducial volume. The data set corresponds to 6511.3 live days and an exposure of 484.2 kiloton-years. Measurements of the neutrino oscillation parameters $\Delta m^2_{32}$, $\sin^2\theta_{23}$, $\sin^2 \theta_{13}$, $\delta_{CP}$, and the preference for the neutrino mass ordering are presented with atmospheric neutrino data alone, and with constraints on $\sin^2 \theta_{13}$ from reactor neutrino experiments. Our analysis including constraints on $\sin^2 \theta_{13}$ favors the normal mass ordering at the 92.3% level., Comment: 24 pages, 18 figures

We report the first measurement of the atmospheric neutrino-oxygen neutral-current quasielastic (NCQE) cross section in the gadolinium-loaded Super-Kamiokande (SK) water Cherenkov detector. In June 2020, SK began a new experimental phase, named SK-Gd, by loading 0.011% by mass of gadolinium into the ultrapure water of the SK detector. The introduction of gadolinium to ultrapure water has the effect of improving the neutron-tagging efficiency. Using a 552.2 day data set from August 2020 to June 2022, we measure the NCQE cross section to be 0.74 $\pm$ 0.22(stat.) $^{+0.85}_{-0.15}$ (syst.) $\times$ 10$^{-38}$ cm$^{2}$/oxygen in the energy range from 160 MeV to 10 GeV, which is consistent with the atmospheric neutrino-flux-averaged theoretical NCQE cross section and the measurement in the SK pure-water phase within the uncertainties. Furthermore, we compare the models of the nucleon-nucleus interactions in water and find that the Binary Cascade model and the Liege Intranuclear Cascade model provide a somewhat better fit to the observed data than the Bertini Cascade model. Since the atmospheric neutrino-oxygen NCQE reactions are one of the main backgrounds in the search for diffuse supernova neutrino background (DSNB), these new results will contribute to future studies - and the potential discovery - of the DSNB in SK., Comment: 8 pages, 3 figures

We report a search for time variations of the solar $^8$B neutrino flux using 5804 live days of Super-Kamiokande data collected between May 31, 1996, and May 30, 2018. Super-Kamiokande measured the precise time of each solar neutrino interaction over 22 calendar years to search for solar neutrino flux modulations with unprecedented precision. Periodic modulations are searched for in a dataset comprising five-day interval solar neutrino flux measurements with a maximum likelihood method. We also applied the Lomb-Scargle method to this dataset to compare it with previous reports. The only significant modulation found is due to the elliptic orbit of the Earth around the Sun. The observed modulation is consistent with astronomical data: we measured an eccentricity of (1.53$\pm$0.35)\%, and a perihelion shift of ($-$1.5$\pm$13.5) days., Comment: 8 pages, 5 figures, 2 tables, and data file: "sksolartimevariation5804d.txt" (the data file updated with additional 3 columns -- R^2 correction, upper-error, lower-error)

For each $c\ge 1$ we prove tight lower bounds on face sizes that must be present to allow $1$- or $2$-cuts in simple duals of $c$-connected maps. Using these bounds, we determine the smallest genus on which a $c$-connected map can have a simple dual with a $2$-cut and give lower and some upper bounds for the smallest genus on which a $c$-connected map can have a simple dual with a $1$-cut., Comment: 19 pages, 11 figures

Many types of peripheral and transmembrane proteins can sense and generate membrane curvature. Laterally isotropic proteins and crescent proteins with twofold rotational symmetry, such as Bin/Amphiphysin/Rvs superfamily proteins, have been studied theoretically. However, proteins often have an asymmetric structure or a higher rotational symmetry. We theoretically studied the curvature sensing of proteins with asymmetric structures and structural deformations. First, we examined proteins consisting of two rod-like segments. When proteins have mirror symmetry, their sensing ability is similar to that of single-rod proteins; hence, with increasing protein density on a cylindrical membrane tube, a second- or first-order transition occurs at a middle or small tube radius, respectively. As asymmetry is introduced, this transition becomes a continuous change, and metastable states appear at high protein densities. Protein with threefold, fivefold, or higher rotational symmetry has laterally isotropic bending energy. However, when a structural deformation is allowed, the protein can have a preferred orientation and stronger curvature sensing., Comment: 10 pages, 11 figures

Gamma rays from HESS J1849$-$000, a middle-aged TeV pulsar wind nebula (PWN), are observed by the Tibet air shower array and the muon detector array. The detection significance of gamma rays reaches $4.0\, \sigma$ and $4.4\, \sigma$ levels above 25 TeV and 100 TeV, respectively, in units of Gaussian standard deviation $\sigma$. The energy spectrum measured between $40\, {\rm TeV} < E < 320\, {\rm TeV}$ for the first time is described with a simple power-law function of ${\rm d}N/{\rm d}E = (2.86 \pm 1.44) \times 10^{-16}(E/40\, {\rm TeV})^{-2.24 \pm 0.41}\, {\rm TeV}^{-1}\, {\rm cm}^{-2}\, {\rm s}^{-1}$. The gamma-ray energy spectrum from the sub-TeV ($E < 1\, {\rm TeV}$) to sub-PeV ($100\, {\rm TeV} < E < 1\, {\rm PeV}$) ranges including the results of previous studies can be modeled with the leptonic scenario, inverse Compton scattering by high-energy electrons accelerated by the PWN of PSR J1849$-$0001. On the other hand, the gamma-ray energy spectrum can also be modeled with the hadronic scenario in which gamma rays are generated from the decay of neutral pions produced by collisions between accelerated cosmic-ray protons and the ambient molecular cloud found in the gamma-ray emitting region. The cutoff energy of cosmic-ray protons $E_{\rm p\, cut}$, cut is estimated at ${\rm log}_{10}(E_{\rm p,\, cut}/{\rm TeV}) = 3.73^{+2.98}_{-0.66}$, suggesting that protons are accelerated up to the PeV energy range. Our study thus proposes that HESS J1849$-$000 should be further investigated as a new candidate for a Galactic PeV cosmic-ray accelerator, PeVatron., Comment: 10 pages, 2 figures, Accepted for publication from the Astrophysical Journal

We report the first search result for the flux of astrophysical electron antineutrinos for energies O(10) MeV in the gadolinium-loaded Super-Kamiokande (SK) detector. In June 2020, gadolinium was introduced to the ultra-pure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electron antineutrinos via inverse beta decay with efficient background rejection and higher signal efficiency thanks to the high efficiency of the neutron tagging technique. In this paper, we report the result for the initial stage of SK-Gd with a $22.5\times552$ $\rm kton\cdot day$ exposure at 0.01% Gd mass concentration. No significant excess over the expected background in the observed events is found for the neutrino energies below 31.3 MeV. Thus, the flux upper limits are placed at the 90% confidence level. The limits and sensitivities are already comparable with the previous SK result with pure-water ($22.5 \times 2970 \rm kton\cdot day$) owing to the enhanced neutron tagging.

The $2$-Edge-Connected Spanning Subgraph problem (2-ECSS) is one of the most fundamental and well-studied problems in the context of network design. In the problem, we are given an undirected graph $G$, and the objective is to find a $2$-edge-connected spanning subgraph $H$ of $G$ with the minimum number of edges. For this problem, a lot of approximation algorithms have been proposed in the literature. In particular, very recently, Garg, Grandoni, and Ameli gave an approximation algorithm for 2-ECSS with factor $1.326$, which was the best approximation ratio. In this paper, we give a $(1.3+\varepsilon)$-approximation algorithm for 2-ECSS, where $\varepsilon$ is an arbitrary positive fixed constant, which improves the previously known best approximation ratio. In our algorithm, we compute a minimum triangle-free $2$-edge-cover in $G$ with the aid of the algorithm for finding a maximum triangle-free $2$-matching given by Hartvigsen. Then, with the obtained triangle-free $2$-edge-cover, we apply the arguments by Garg, Grandoni, and Ameli.

We investigate how the diverse star formation histories observed across galaxy masses emerged using models that evolve under gas accretion from host halos. They also include ejection of interstellar matter by supernova feedback, recycling of ejected matter and preventive feedback that partially hinders gas accretion. We consider three schemes of gas accretion: the fiducial scheme which includes the accretion of cold gas in low-mass halos and high-redshift massive halos as hinted by cosmological simulations; the flat scheme in which high-mass cold accretion is removed; and finally the shock-heating scheme which assumes radiative cooling of the shock-heated halo gas. The fiducial scheme reproduces dramatic diminishment in star formation rate (SFR) after its peak as observed for the present halo mass $M_{\rm vir}>10^{12.5}{\rm M}_\odot$ while other two schemes show reduced or negligible quenching. This scheme reproduces the high-mass slope in the SFR vs. stellar mass relation decreasing toward recent epochs whereas other two schemes show opposite trend which contradicts observation. Success in the fiducial scheme originates in the existence of high-mass cold-mode accretion which retards transition to the slow hot-mode accretion thereby inducing a larger drop in SFR. Aided by gas recycling, which creates monotonically increasing SFR in low-mass halos, this scheme can reproduce the downsizing galaxy formation. Several issues remain, suggesting non-negligible roles of missing physics. Feedback from active galactic nuclei could mitigate upturn of SFR in low-redshift massive halos whereas galaxy mergers could remedy early inefficient star formation., Comment: 28 pages, 21 figures, MNRAS accepted

In this paper, we propose a level set-based shape optimization method for acoustic wave propagation problems with a deformable structure. First, we propose a mathematical model for acoustic wave propagation with a deformed structure based on coordinate transformation and the Eulerian approach. Next, we formulate the shape optimization problem and perform sensitivity analysis based on the shape derivative concept. We then construct an optimization algorithm based on the framework of a level set-based shape and topology optimization method. Finally, we provide two-dimensional optimization examples that demonstrate the effectiveness of our proposed method in providing optimized designs with desired functionality, while considering the structural deformation.

In real-world applications, a machine learning model is required to handle an open-set recognition (OSR), where unknown classes appear during the inference, in addition to a domain shift, where the distribution of data differs between the training and inference phases. Domain generalization (DG) aims to handle the domain shift situation where the target domain of the inference phase is inaccessible during model training. Open domain generalization (ODG) takes into account both DG and OSR. Domain-Augmented Meta-Learning (DAML) is a method targeting ODG but has a complicated learning process. On the other hand, although various DG methods have been proposed, they have not been evaluated in ODG situations. This work comprehensively evaluates existing DG methods in ODG and shows that two simple DG methods, CORrelation ALignment (CORAL) and Maximum Mean Discrepancy (MMD), are competitive with DAML in several cases. In addition, we propose simple extensions of CORAL and MMD by introducing the techniques used in DAML, such as ensemble learning and Dirichlet mixup data augmentation. The experimental evaluation demonstrates that the extended CORAL and MMD can perform comparably to DAML with lower computational costs. This suggests that the simple DG methods and their simple extensions are strong baselines for ODG. The code used in the experiments is available at https://github.com/shiralab/OpenDG-Eval., Comment: 18 pages, 5 figures

We describe a setup of time-, spin-, and angle-resolved photoemission spectroscopy (tr-SARPES) employing a 10.7-eV ($\lambda$=115.6 nm) pulse laser at 1-MHz repetition rate as a probe photon source. This equipment effectively combines technologies of a high-power Yb:fiber laser, ultraviolet-driven harmonic generation in Xe gas, and a SARPES apparatus equipped with very-low-energy-electron-diffraction (VLEED) spin detectors. A high repetition rate (1 MHz) of the probe laser allows experiments with the photoemission space-charge effects significantly reduced, despite a high flux of 10$^{13}$ photons/s on the sample. The relatively high photon energy (10.7 eV) also brings the capability of observing a wide momentum range that covers the entire Brillouin zone of many materials while ensuring high momentum resolution. The experimental setup overcomes a low efficiency of spin-resolved measurements, which gets even more severe for the pump-probed unoccupied states, and affords for investigating ultrafast electron and spin dynamics of modern quantum materials with energy and time resolutions of 25 meV and 360 fs, respectively., Comment: 11 pages, 7 figures

The Bin/amphiphysin/Rvs (BAR) superfamily proteins have a crescent binding domain and bend biomembranes along the domain axis. However, their anisotropic bending rigidities and spontaneous curvatures have not been experimentally determined. Here, we estimated these values from the bound protein densities on tethered vesicles using a mean-field theory of anisotropic bending energy and orientation-dependent excluded volume. The dependence curves of the protein density on the membrane curvature are fitted to the experimental data for the I-BAR and N-BAR domains reported by C. Prevost et al. Nat. Commun. 6, 8529 (2015) and F.-C. Tsai et al. Soft Matter 17, 4254 (2021), respectively. For the I-BAR domain, all three density curves of different chemical potentials exhibit excellent fits with a single parameter set of anisotropic bending energy. When the classical isotropic bending energy is used instead, one of the curves can be fitted well, but the others exhibit large deviations. In contrast, for the N-BAR domain, two curves are not well-fitted simultaneously using the anisotropic model, although it is significantly improved compared to the isotropic model. This deviation likely suggests a cluster formation of the N-BAR domains., Comment: 12 pages, 15 figures

In recent years, many automobiles have been equipped with cameras, which have accumulated an enormous amount of video footage of driving scenes. Autonomous driving demands the highest level of safety, for which even unimaginably rare driving scenes have to be collected in training data to improve the recognition accuracy for specific scenes. However, it is prohibitively costly to find very few specific scenes from an enormous amount of videos. In this article, we show that proper video-to-video distances can be defined by focusing on ego-vehicle actions. It is well known that existing methods based on supervised learning cannot handle videos that do not fall into predefined classes, though they work well in defining video-to-video distances in the embedding space between labeled videos. To tackle this problem, we propose a method based on semi-supervised contrastive learning. We consider two related but distinct contrastive learning: standard graph contrastive learning and our proposed SOIA-based contrastive learning. We observe that the latter approach can provide more sensible video-to-video distances between unlabeled videos. Next, the effectiveness of our method is quantified by evaluating the classification performance of the ego-vehicle action recognition using HDD dataset, which shows that our method including unlabeled data in training significantly outperforms the existing methods using only labeled data in training., Comment: 19 pages, 17 figures