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Tunnels and long corridors are challenging environments for mobile robots because a LiDAR point cloud should degenerate in these environments. To tackle point cloud degeneration, this study presents a tightly-coupled LiDAR-IMU-wheel odometry algorithm with an online calibration for skid-steering robots. We propose a full linear wheel odometry factor, which not only serves as a motion constraint but also performs the online calibration of kinematic models for skid-steering robots. Despite the dynamically changing kinematic model (e.g., wheel radii changes caused by tire pressures) and terrain conditions, our method can address the model error via online calibration. Moreover, our method enables an accurate localization in cases of degenerated environments, such as long and straight corridors, by calibration while the LiDAR-IMU fusion sufficiently operates. Furthermore, we estimate the uncertainty (i.e., covariance matrix) of the wheel odometry online for creating a reasonable constraint. The proposed method is validated through three experiments. The first indoor experiment shows that the proposed method is robust in severe degeneracy cases (long corridors) and changes in the wheel radii. The second outdoor experiment demonstrates that our method accurately estimates the sensor trajectory despite being in rough outdoor terrain owing to online uncertainty estimation of wheel odometry. The third experiment shows the proposed online calibration enables robust odometry estimation in changing terrains., Comment: Accepted by IEEE Access journal (12 September) open-source: https://github.com/TakuOkawara/full_linear_wheel_odometry_factor

Developing methods to solve nuclear many-body problems with quantum computers is an imperative pursuit within the nuclear physics community. Here, we introduce a quantum algorithm to accurately and precisely compute the ground state of valence two-neutron systems leveraging presently available Noisy Intermediate-Scale Quantum devices. Our focus lies on the nuclei having a doubly-magic core plus two valence neutrons in the $ p $, $ sd $, and $ pf $ shells, i.e. ${}^6$He, ${}^{18}$O, and ${}^{42}$Ca, respectively. Our ansatz, quantum circuit, is constructed in the pair-wise form, taking into account the symmetries of the system in an explicit manner, and enables us to reduce the number of qubits and the number of CNOT gates required. The results on a real quantum hardware by IBM Quantum Platform show that the proposed method gives very accurate results of the ground-state energies, which are typically within $ 0.1 \, \% $ error in the energy for ${}^6$He and ${}^{18}$O and at most $ 1 \, \% $ error for ${}^{42}$Ca. Furthermore, our experiments using real quantum devices also show the pivotal role of the circuit layout design, attuned to the connectivity of the qubits, in mitigating errors., Comment: 12 pages, 12 figures; discussions and references added

We propose introducing an extended Hubbard Hamiltonian derived via the ab initio downfolding method, which was originally formulated for periodic materials, towards efficient quantum computing of molecular electronic structure calculations. By utilizing this method, the first-principles Hamiltonian of chemical systems can be coarse-grained by eliminating the electronic degrees of freedom in higher energy space and reducing the number of terms of electron repulsion integral from $\mathcal{O}(N^4)$ to $\mathcal{O}(N^2)$. Our approach is validated numerically on the vertical excitation energies and excitation characters of ethylene, butadiene, and hexatriene. The dynamical electron correlation is incorporated within the framework of the constrained random phase approximation in advance of quantum computations, and the constructed models capture the trend of experimental and high-level quantum chemical calculation results. As expected, the $L^1$-norm of the fermion-to-qubit mapped model Hamiltonians is significantly lower than that of conventional ab initio Hamiltonians, suggesting improved scalability of quantum computing. Those numerical outcomes and the results of the simulation of excited-state sampling demonstrate that the ab initio extended Hubbard Hamiltonian may hold significant potential for quantum chemical calculations using quantum computers., Comment: 15 pages, 3 figures

Grain alignment is a key factor that determines the performance of a superconducting bulk. In this study, the spark plasma texturing (SPT) technique was used to fabricate a CaKFe$_4$As$_4$ superconducting bulk. X-ray diffraction and electron backscatter diffraction revealed that the $c$-axes of the CaKFe$_4$As$_4$ grains in the SPT bulk are aligned, demonstrating that the SPT technique is effective in achieving $c$-axis texture. In addition, chemical composition analysis showed that oxide impurities, which affect the grain boundary characteristics that determine the inter-grain critical current density ($J_c$), are randomly distributed in the SPT bulk. Magnetization measurements showed high $J_c$ values of the SPT bulk, reaching 127 kA cm$^{-2}$ and 26 kA cm$^{-2}$ at 4.2 K under a self-field and magnetic field of 5 T, respectively. These results suggest that the SPT technique is a promising approach for obtaining a high-performance superconducting bulk material for high-field applications.

A high density CaKFe$_4$As$_4$ bulk sample was successfully synthesized using a spark plasma sintering (SPS) technique. The density of the synthesized sample was 5.02 g cm$^{-3}$, corresponding to 96.2% of the theoretical density of CaKFe$_4$As$_4$. Moreover, a reasonably high Vickers hardness of 1 GPa was measured. The electrical resistivity of the SPS bulk sample was as low as approximately 600 $\mu\Omega$ cm at 300 K, which is smaller than that of the ordinary sintered polycrystalline sample by nearly one order of magnitude, and exhibited a sharp superconducting transition, with the transition width $\Delta\textit{T}_c$ less than 2 K, indicating an improved grain connectivity. The critical current density of the SPS bulk sample, as calculated from the magnetization hysteresis loops (magnetic $\textit{J}_c$), reached 18 kA cm$^{-2}$ at 4.2 K under 5 T, which is the highest among the iron-based superconductor polycrystalline samples reported thus far., Comment: 13 pages, 6 figures, 1 table

Understanding the nanoscale carrier dynamics induced by light excitation is the key to unlocking futuristic devices and innovative functionalities in advanced materials. Optical pump-probe scanning tunneling microscopy (OPP-STM) has opened a window to these phenomena. However, mastering the combination of ultrafast pulsed lasers with STM requires high expertise and effort. We have shattered this barrier and developed a compact OPP-STM system accessible to all. This system precisely controls laser pulse timing electrically and enables stable laser irradiation on sample surfaces. Furthermore, by applying this technique to atomic force microscopy (AFM), we have captured time-resolved force signals with an exceptionally high signal-to-noise ratio. Originating from the dipole-dipole interactions, these signals provide insights into the carrier dynamics on sample surfaces, which are activated by photo-illumination. These technologies are promising as powerful tools for exploring a wide range of photoinduced phenomena in conductive and insulating materials., Comment: 8 pages, 4 figures

Recent advancements in machine learning have showcased its potential to significantly accelerate the discovery of new materials. Central to this progress is the development of rapidly computable property predictors, enabling the identification of novel materials with desired properties from vast material spaces. However, the limited availability of data resources poses a significant challenge in data-driven materials research, particularly hindering the exploration of innovative materials beyond the boundaries of existing data. While machine learning predictors are inherently interpolative, establishing a general methodology to create an extrapolative predictor remains a fundamental challenge, limiting the search for innovative materials beyond existing data boundaries. In this study, we leverage an attention-based architecture of neural networks and meta-learning algorithms to acquire extrapolative generalization capability. The meta-learners, experienced repeatedly with arbitrarily generated extrapolative tasks, can acquire outstanding generalization capability in unexplored material spaces. Through the tasks of predicting the physical properties of polymeric materials and hybrid organic--inorganic perovskites, we highlight the potential of such extrapolatively trained models, particularly with their ability to rapidly adapt to unseen material domains in transfer learning scenarios., Comment: 26 pages, 7 figures

We present JWST NIRCam imaging of B14-65666 ("Big Three Dragons"), a bright Lyman-break galaxy system ($M_\text{UV}=-22.5$ mag) at $z=7.15$. The high angular resolution of NIRCam reveals the complex morphology of two galaxy components: galaxy E has a compact core (E-core), surrounded by diffuse, extended, rest-frame optical emission, which is likely to be tidal tails; and galaxy W has a clumpy and elongated morphology with a blue UV slope ($\beta_\text{UV}=-2.2\pm0.1$). The flux excess, F356W$-$F444W, peaks at the E-core ($1.05^{+0.08}_{-0.09}$ mag), tracing the presence of strong [OIII] 4960,5008 \r{A} emission. ALMA archival data show that the bluer galaxy W is brighter in dust continua than the redder galaxy E, while the tails are bright in [OIII] 88 $\mathrm{\mu m}$. The UV/optical and sub-mm SED fitting confirms that B14-65666 is a major merger in a starburst phase as derived from the stellar mass ratio (3:1 to 2:1) and the star-formation rate, $\simeq1$ dex higher than the star-formation main sequence at the same redshift. The galaxy E is a dusty ($A_\text{V}=1.2\pm0.1$ mag) starburst with a possible high dust temperature ($\ge63$-$68$ K). The galaxy W would have a low dust temperature ($\le27$-$33$ K) or patchy stellar-and-dust geometry, as suggested from the infrared excess (IRX) and $\beta_\text{UV}$ diagram. The high optical-to-FIR [OIII] line ratio of the E-core shows its lower gas-phase metallicity ($\simeq0.2$ Z$_{\odot}$) than the galaxy W. These results agree with a scenario where major mergers disturb morphology and induce nuclear dusty starbursts triggered by less-enriched inflows. B14-65666 shows a picture of complex stellar buildup processes during major mergers in the epoch of reionization., Comment: 18 pages, 6 figures, 4 tables. Submitted to ApJ

For all $\alpha_1,\alpha_2\in(1,2)$ with $1/\alpha_1+1/\alpha_2>5/3$, we show that the number of pairs $(n_1,n_2)$ of positive integers with $N=\lfloor{n_1^{\alpha_1}}\rfloor+\lfloor{n_2^{\alpha_2}}\rfloor$ is equal to $\Gamma(1+1/\alpha_1)\Gamma(1+1/\alpha_2)\Gamma(1/\alpha_1+1/\alpha_2)^{-1}N^{1/\alpha_1+1/\alpha_2-1} + o(N^{1/\alpha_1+1/\alpha_2-1})$ as $N\to\infty$, where $\Gamma$ denotes the gamma function. Moreover, we show a non-asymptotic result for the same counting problem when $\alpha_1,\alpha_2\in(1,2)$ lie in a larger range than the above. Finally, we give some asymptotic formulas for similar counting problems in a heuristic way., Comment: 44 pages, 4 figures

It is of special importance in the clinical trial to compare survival times between the treatment group and the control group. Propensity score methods with a logistic regression model are often used to reduce the effects of confounders. However, the modeling of complex structures between the covariates, the treatment assignment and the survival time is difficult. In this paper, we consider coarsened exact matching (CEM), which does not need any parametric models, and we propose the weighted log-rank statistic based on CEM. We derive asymptotic properties of the weighted log-rank statistic, such as the weak convergence to a Gaussian process in Skorokhod space, in particular the asymptotic normality, under the null hypothesis and the consistency of the log-rank test. Simulation studies show that the log-rank statistic based on CEM is more robust than the log-rank statistic based on the propensity score.

Convolutional neural networks (CNNs) have gained widespread usage across various fields such as weather forecasting, computer vision, autonomous driving, and medical image analysis due to its exceptional ability to extract spatial information, share parameters, and learn local features. However, the practical implementation and commercialization of CNNs in these domains are hindered by challenges related to model sizes, overfitting, and computational time. To address these limitations, our study proposes a groundbreaking approach that involves tensorizing the dense layers in the CNN to reduce model size and computational time. Additionally, we incorporate attention layers into the CNN and train it using Contrastive self-supervised learning to effectively classify cloud information, which is crucial for accurate weather forecasting. We elucidate the key characteristics of tensorized neural network (TNN), including the data compression rate, accuracy, and computational speed. The results indicate how TNN change their properties under the batch size setting., Comment: 11 pages, 7 figures

Unsupervised intrinsic image decomposition (IID) is the process of separating a natural image into albedo and shade without these ground truths. A recent model employing light detection and ranging (LiDAR) intensity demonstrated impressive performance, though the necessity of LiDAR intensity during inference restricts its practicality. Thus, IID models employing only a single image during inference while keeping as high IID quality as the one with an image plus LiDAR intensity are highly desired. To address this challenge, we propose a novel approach that utilizes only an image during inference while utilizing an image and LiDAR intensity during training. Specifically, we introduce a partially-shared model that accepts an image and LiDAR intensity individually using a different specific encoder but processes them together in specific components to learn shared representations. In addition, to enhance IID quality, we propose albedo-alignment loss and image-LiDAR conversion (ILC) paths. Albedo-alignment loss aligns the gray-scale albedo from an image to that inferred from LiDAR intensity, thereby reducing cast shadows in albedo from an image due to the absence of cast shadows in LiDAR intensity. Furthermore, to translate the input image into albedo and shade style while keeping the image contents, the input image is separated into style code and content code by encoders. The ILC path mutually translates the image and LiDAR intensity, which share content but differ in style, contributing to the distinct differentiation of style from content. Consequently, LIET achieves comparable IID quality to the existing model with LiDAR intensity, while utilizing only an image without LiDAR intensity during inference.

We investigate a gedanken experiment to destroy an extremally charged black hole by dropping a test particle, provided that there are multiple $U(1)$ gauge fields coupled with each other through higher derivative interactions. In the absence of higher derivative corrections, it is known that the Coulomb repulsion prevents a test particle that would break the extremal condition from falling into an extremal black hole and therefore the black hole cannot be destroyed. We extend this observation to include higher derivative corrections. Although the extremal condition is modified by the higher derivative interactions, we find that the repulsive force induced by the higher derivative couplings is responsible for preventing a test particle that would break the modified extremal condition to reach the event horizon. Thus, we confirm that the weak cosmic censorship conjecture holds for extremally charged black holes even in the presence of higher derivative corrections, as long as the test particle approximation is justified., Comment: 13 pages

Quantum computing has been pursued with various hardware platforms, and an optical system is one of the most reasonable choices for large-scale computation. In the optical continuous-variable computation scheme, the incorporation of Gaussian gates and a highly non-classical non-Gaussian state enables universal quantum computation. Although basic technologies for Gaussian gates and non-Gaussian state generations have long been developed, these building blocks have not yet been integrated in a scalable fashion. Here, we integrate them to develop a scalable and programmable optical quantum computing platform that can sequentially perform an essential Gaussian gate, the squeezing gate, on a non-Gaussian input state. The key enablers are a loop-based optical circuit with dynamical and programmable controllability and its time-synchronization with the probabilistic non-Gaussian state generation. We verify the deterministic, programmable, and repeatable quantum gates on a typical non-Gaussian state by implementing up to three-step gates. The gates implemented are so high-quality that strong evidence of the states' non-classicalities, negativities of the Wigner functions, are preserved even after multistep gates. This platform is compatible with other non-Gaussian states and realizes large-scale universal quantum computing by incorporating other existing processing technologies., Comment: 9 pages, 3 figures for the main text, and 3 pages and 2 figures for the supplementary information

We consider an operator $P_V=(1+V)P$ on $\ell^2(Z^d)$, where $P$ is the transition operator of a symmetric irreducible random walk, and $V$ is a ``sparse'' potential. We first characterize the essential spectra of this operator. Secondly, we prove that all the eigenfunctions which correspond to discrete spectra decay exponentially fast. Thirdly, we give a sufficient condition for this operator to have an absolute spectral gap at the right edge of the spectra. Finally, as an application of the absolute spectral gap and the exponential decay of the eigenfunctions, we prove a limit theorem for the random walk under the Gibbs measure associated to the potential $V$.

Super-puffs are planets with exceptionally low densities ($\rho \lesssim 0.1$~g~cm$^{-3}$) and core masses ($M_c \lesssim 5 M_\oplus$). Many lower-mass ($M_p\lesssim10M_\oplus$) super-puffs are expected to be unstable to catastrophic mass loss via photoevaporation and/or boil-off, whereas the larger gravitational potentials of higher-mass ($M_p\gtrsim10M_\oplus$) super-puffs should make them more stable to these processes. We test this expectation by studying atmospheric loss in the warm, higher-mass super-puff TOI-1420b ($M = 25.1M_\oplus$, $R = 11.9R_\oplus$, $\rho = 0.08$~g~cm$^{-3}$, $T_\mathrm{eq} = 960$~K). We observed one full transit and one partial transit of this planet using the metastable helium filter on Palomar/WIRC and found that the helium transits were $0.671\pm0.079\%$ (8.5$\sigma$) deeper than the TESS transits, indicating an outflowing atmosphere. We modeled the excess helium absorption using a self-consistent 1D hydrodynamics code to constrain the thermal structure of the outflow given different assumptions for the stellar XUV spectrum. These calculations then informed a 3D simulation which provided a good match to the observations with a modest planetary mass-loss rate of $10^{10.82}$~g~s$^{-1}$ ($M_p/\dot{M}\approx70$~Gyr). Super-puffs with $M_p\gtrsim10M_\oplus$, like TOI-1420b and WASP-107b, appear perfectly capable of retaining atmospheres over long timescales; therefore, these planets may have formed with the unusually large envelope mass fractions they appear to possess today. Alternatively, tidal circularization could have plausibly heated and inflated these planets, which would bring their envelope mass fractions into better agreement with expectations from core-nucleated accretion., Comment: 18 pages, 8 figures, accepted to AJ

Following the Pluto fly-by of the New Horizons spacecraft, the mission provided a unique opportunity to explore the Kuiper Belt in-situ. The possibility existed to fly-by a Kuiper Belt object (KBO) as well as to observe additional objects at distances closer than are feasible from earth-orbit facilities. However, at the time of launch no KBOs were known about that were accessible by the spacecraft. In this paper we present the results of 10 years of observations and three uniquely dedicated efforts -- two ground-based using the Subaru Suprime Camera, the Magellan MegaCam and IMACS Cameras, and one with the Hubble Space Telescope -- to find such KBOs for study. In this paper we overview the search criteria and strategies employed in our work and detail the analysis efforts to locate and track faint objects in the galactic plane. We also present a summary of all of the KBOs that were discovered as part of our efforts and how spacecraft targetability was assessed, including a detailed description of our astrometric analysis which included development of an extensive secondary calibration network. Overall, these efforts resulted in the discovery of 89 KBOs including 11 which became objects for distant observation by New Horizons and (486958) Arrokoth which became the first post-Pluto fly-by destination., Comment: Accepted to PSJ. 40 pages, 10 figures, 10 tables

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

The execution of smart contracts on Ethereum, a public blockchain system, incurs a fee called gas fee for its computation and data-store consumption. When programmers develop smart contracts (e.g., in the Solidity programming language), they could unknowingly write code snippets that unnecessarily cause more gas fees. These issues, or what we call gas wastes, could lead to significant monetary waste for users. Yet, there have been no systematic examination of them or effective tools for detecting them. This paper takes the initiative in helping Ethereum users reduce their gas fees in two important steps: we conduct the first empirical study on gas wastes in popular smart contracts written in Solidity by understanding their root causes and fixing strategies; we then develop a static tool, PeCatch, to effectively detect gas wastes with simple fixes in Solidity programs based on our study findings. Overall, we make seven insights and four suggestions from our gas-waste study, which could foster future tool development, language improvement, and programmer awareness, and develop eight gas-waste checkers, which pinpoint 383 previously unknown gas wastes from famous Solidity libraries.

We report on a measurement of astrophysical tau neutrinos with 9.7 years of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate $\nu_\tau$ events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent $\nu_\tau$ energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from $\pi^\pm/K^\pm$ decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-$\nu_\tau$ astrophysical neutrinos. Thus, we rule out the absence of astrophysical $\nu_\tau$ at the $5\sigma$ level. The measured astrophysical $\nu_\tau$ flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations., Comment: Accepted for publication in Physical Review Letters. This version includes full author list metadata

The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed., Comment: 28 pages, 18 figures, 1 table, submitted to JINST, updated to account for comments received

Recent measurements of carbon isotope ratios in both protoplanetary disks and exoplanet atmospheres have suggested a possible transfer of significant carbon isotope fractionation from disks to planets. For a clearer understanding of the isotopic link between disks and planets, it is important to measure the carbon isotope ratios in various species. In this paper, we present a detection of the $^{13}$CN $N=2-1$ hyperfine lines in the TW Hya disk with the Atacama Large Millimeter/submillimeter Array. This is the first spatially-resolved detection of $^{13}$CN in disks, which enables us to measure the spatially resolved $^{12}$CN/$^{13}$CN ratio for the first time. We conducted non-local thermal equilibrium modeling of the $^{13}$CN lines in conjunction with previously observed $^{12}$CN lines to derive the kinetic temperature, ${\rm H_2}$ volume density, and column densities of $^{12}$CN and $^{13}$CN. The ${\rm H_2}$ volume density is found to range between $ (4 - 10)\times10^7 \ {\rm cm^{-3}}$, suggesting that CN molecules mainly reside in the disk upper layer. The $^{12}$CN/$^{13}$CN ratio is measured to be $ 70^{+9}_{-6}$ at $30 < r < 80$ au from the central star, which is similar to the $\rm ^{12}C/^{13}C$ ratio in the interstellar medium. However, this value differs from the previously reported values found for other carbon-bearing molecules (CO and HCN) in the TW Hya disk. This could be self-consistently explained by different emission layer heights for different molecules combined with preferential sequestration of $\rm ^{12}C$ into the solid phase towards the disk midplane. This study reveals the complexity of the carbon isotope fractionation operating in disks., Comment: 16 pages, 7 figures, accepted for publication in ApJ

Solvent plays an essential role in a variety of chemical, physical, and biological processes that occur in the solution phase. The reference interaction site model (RISM) and its three-dimensional extension (3D-RISM) serve as powerful computational tools for modeling solvation effects in chemical reactions, biological functions, and structure formations. We present the RISM integrated calculator (RISMiCal) program package, which is based on RISM and 3D-RISM theories with fast GPU code. RISMiCal has been developed as an integrated RISM/3D-RISM program that has interfaces with external programs such as Gaussian16, GAMESS, and Tinker. Fast 3D-RISM programs for single- and multi-GPU codes written in CUDA would enhance the availability of these hybrid methods because they require the performance of many computationally expensive 3D-RISM calculations. We expect that our package can be widely applied for chemical and biological processes in solvent. The RISMiCal package is available at https://rismical-dev.github.io.

We present an asymptotic expansion formula of an estimator for the drift coefficient of the fractional Ornstein-Uhlenbeck process. As the machinery, we apply the general expansion scheme for Wiener functionals recently developed by the authors [26]. The central limit theorem in the principal part of the expansion has the classical scaling T^{1/2}. However, the asymptotic expansion formula is a complex in that the order of the correction term becomes the classical T^{-1/2} for H in (1/2,5/8), but T^{4H-3} for H in [5/8, 3/4).

A measurement of the diffuse astrophysical neutrino spectrum is presented using IceCube data collected from 2011-2022 (10.3 years). We developed novel detection techniques to search for events with a contained vertex and exiting track induced by muon neutrinos undergoing a charged-current interaction. Searching for these starting track events allows us to not only more effectively reject atmospheric muons but also atmospheric neutrino backgrounds in the southern sky, opening a new window to the sub-100 TeV astrophysical neutrino sky. The event selection is constructed using a dynamic starting track veto and machine learning algorithms. We use this data to measure the astrophysical diffuse flux as a single power law flux (SPL) with a best-fit spectral index of $\gamma = 2.58 ^{+0.10}_{-0.09}$ and per-flavor normalization of $\phi^{\mathrm{Astro}}_{\mathrm{per-flavor}} = 1.68 ^{+0.19}_{-0.22} \times 10^{-18} \times \mathrm{GeV}^{-1} \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$ (at 100 TeV). The sensitive energy range for this dataset is 3 - 550 TeV under the SPL assumption. This data was also used to measure the flux under a broken power law, however we did not find any evidence of a low energy cutoff., Comment: 27 pages, 28 figures

Multiparty session types (MPST) provide a type discipline where a programmer or architect specifies a whole view of communications as a global protocol, and each distributed program is locally type-checked against its end-point projection. After 10 years from the birth of MPST, Scalas and Yoshida discovered that the proofs of type safety in the literature which use the end-point projection with mergeability are flawed. After this paper, researchers wrongly believed that the end-point projection (with mergeability) was unsound. We correct this misunderstanding, proposing a new general proof technique for type soundness of multiparty session $\pi$-calculus, which uses an association relation between a global type and its end-point projection.

Atmospheric escape is crucial to understand the evolution of planets in and out of the Solar system and to interpret atmospheric observations. While hydrodynamic escape simulations have been actively developed incorporating detailed processes such as UV heating, chemical reactions, and radiative cooling, the radiative cooling by molecules has been treated as emission from selected lines or rotational/vibrational bands to reduce its numerical cost. However, ad hoc selections of radiative lines would risk estimating inaccurate cooling rates because important lines or wavelengths for atmospheric cooling depend on emitting conditions such as temperature and optical thickness. In this study, we apply the correlated-k distribution (CKD) method to cooling rate calculations for H$_2$-dominant transonic atmospheres containing H$_2$O or CO as radiative species, to investigate its numerical performance and the importance of considering all lines of the molecules. Our simulations demonstrate that the sum of weak lines, which provides only 1 % of the line emission energy in total at optically thin conditions, can become the primary source of radiative cooling in optically thick regions, especially for H$_2$O-containing atmospheres. Also, in our hydrodynamic simulations, the CKD method with a wavelength resolution of 1000 is found to be effective, allowing the calculation of escape rate and temperature profiles with acceptable numerical cost. Our results show the importance of treating all radiative lines and the usefulness of the CKD method in hydrodynamic escape simulations. It is particularly practical for heavy-element-enriched atmospheres considered in small exoplanets, including super-Earths, without any prior selections for effective lines., Comment: 17 pages, 10 figures, accepted in ApJ

The human brain's plasticity allows for the integration of artificial body parts into the human body. Leveraging this, embodied systems realize intuitive interactions with the environment. We introduce a novel concept: embodied swarm robots. Swarm robots constitute a collective of robots working in harmony to achieve a common objective, in our case, serving as functional body parts. Embodied swarm robots can dynamically alter their shape, density, and the correspondences between body parts and individual robots. We contribute an investigation of the influence on embodiment of swarm robot-specific factors derived from these characteristics, focusing on a hand. Our paper is the first to examine these factors through virtual reality (VR) and real-world robot studies to provide essential design considerations and applications of embodied swarm robots. Through quantitative and qualitative analysis, we identified a system configuration to achieve the embodiment of swarm robots.

The adaptive quasi-likelihood analysis is developed for a degenerate diffusion process. Asymptotic normality and moment convergence are proved for the quasi-maximum likelihood estimators and quasi-Bayesian estimators, in the adaptive scheme.

We present a loop-based optical processor enabling time-domain programmable beam-splitter (BS) operations for a phase-sensitive non-Gaussian state. The loop itself is of high quality, allowing for storage of a non-Gaussian state for up to seven round trips while preserving its Wigner negativity and phase coherence. We perform various BS operations on a non-Gaussian state and evaluate them as transformations of the state's waveforms. Our work integrates non-Gaussian states with time multiplexing, laying the foundation for large-scale universal quantum information processing., Comment: 5 pages, 4 figures

We study the geometry of tropical Fermat-Weber points in terms of the symmetric tropical metric over the tropical projective torus. It is well known that a tropical Fermat-Weber point of a given sample is not unique and in this paper we show that the set of all possible Fermat-Weber points forms a polytrope. Then, we introduce the tropical Fermat-Weber gradient and using them, we show that the tropical Fermat-Weber polytrope is a bounded cell of a tropical hyperplane arrangement given by both min- and max-tropical hyperplanes with apices which are observations in the input data.

The emissions of Taylor cones from a wide range of ionic liquids (ILs) have been tested in vacuo in an attempt to identify what physical properties favor the purely ionic regime (PIR). This regime is well known in the case of Taylor cones of liquid metals. For nonmetallic liquids, it has been previously observed in conventional (capillary tube) electrospray sources at room temperature only for the room temperature molten salt (ionic liquid) EMI-BF4 (EMI=1-ethyl-3-methylimidazolium). A large number of other ILs and their mixtures have been studied here, most of which (but not all) are unable to reach the PIR at room temperature. Based on these results and additional theoretical considerations, strong support is assembled for the notion that the PIR is favored by ILs not only of high electrical conductivity but also of high surface tension. This hypothesis is confirmed by tests with three recently synthesized ILs, EMI-GaCl4, EMI-C(CN)3, and EMI-N(CN)2, all of which combine exceptional surface tension and electrical conductivity, and all of which reach the PIR at room temperature far more readily than EMI-BF4.

Our aim of this paper is to develop new map matching algorithms and to improve upon previous work. We address two key approaches: Analytic Hierarchy Process (AHP) map matching and fuzzy logic map matching. AHP is a decision-making method that combines mathematical analysis with human judgment, and fuzzy logic is an approach to computing based on the degree of truth and aims at modeling the imprecise modes of reasoning from 0 to 1 rather than the usual boolean logic. Of these algorithms, the way of our applying AHP to map matching is newly developed in this paper, meanwhile, our application of fuzzy logic to map matching is mostly the same as existing research except for some small changes. Because of the common characteristic that both methods are designed to handle imprecise information and simplicity for implementation, we decided to use these methods., Comment: 25 pages, 27 figures

Syntactic Language Models (SLMs) can be trained efficiently to reach relatively high performance; however, they have trouble with inference efficiency due to the explicit generation of syntactic structures. In this paper, we propose a new method dubbed tree-planting: instead of explicitly generating syntactic structures, we "plant" trees into attention weights of unidirectional Transformer LMs to implicitly reflect syntactic structures of natural language. Specifically, unidirectional Transformer LMs trained with tree-planting will be called Tree-Planted Transformers (TPT), which inherit the training efficiency from SLMs without changing the inference efficiency of their underlying Transformer LMs. Targeted syntactic evaluations on the SyntaxGym benchmark demonstrated that TPTs, despite the lack of explicit generation of syntactic structures, significantly outperformed not only vanilla Transformer LMs but also various SLMs that generate hundreds of syntactic structures in parallel. This result suggests that TPTs can learn human-like syntactic knowledge as data-efficiently as SLMs while maintaining the modeling space of Transformer LMs unchanged., Comment: Accepted by ACL 2024 (Findings)

The world's languages exhibit certain so-called typological or implicational universals; for example, Subject-Object-Verb (SOV) languages typically use postpositions. Explaining the source of such biases is a key goal of linguistics. We study word-order universals through a computational simulation with language models (LMs). Our experiments show that typologically-typical word orders tend to have lower perplexity estimated by LMs with cognitively plausible biases: syntactic biases, specific parsing strategies, and memory limitations. This suggests that the interplay of cognitive biases and predictability (perplexity) can explain many aspects of word-order universals. It also showcases the advantage of cognitively-motivated LMs, typically employed in cognitive modeling, in the simulation of language universals., Comment: Accepted by ACL 2024 main conference, 22 pages

The essential requirement for fault-tolerant quantum computation (FTQC) is the total protocol design to achieve a fair balance of all the critical factors relevant to its practical realization, such as the space overhead, the threshold, and the modularity. A major obstacle in realizing FTQC with conventional protocols, such as those based on the surface code and the concatenated Steane code, has been the space overhead, i.e., the required number of physical qubits per logical qubit. Protocols based on high-rate quantum low-density parity-check (LDPC) codes gather considerable attention as a way to reduce the space overhead, but problematically, the existing fault-tolerant protocols for such quantum LDPC codes sacrifice the other factors. Here we construct a new fault-tolerant protocol to meet these requirements simultaneously based on more recent progress on the techniques for concatenated codes rather than quantum LDPC codes, achieving a constant space overhead, a high threshold, and flexibility in modular architecture designs. In particular, under a physical error rate of $0.1\%$, our protocol reduces the space overhead to achieve the logical CNOT error rates $10^{-10}$ and $10^{-24}$ by more than $90 \%$ and $97 \%$, respectively, compared to the protocol for the surface code. Furthermore, our protocol achieves the threshold of $2.4 \%$ under a conventional circuit-level error model, substantially outperforming that of the surface code. The use of concatenated codes also naturally introduces abstraction layers essential for the modularity of FTQC architectures. These results indicate that the code-concatenation approach opens a way to significantly save qubits in realizing FTQC while fulfilling the other essential requirements for the practical protocol design., Comment: 8+19 pages, 3+15 figures

The existence of cosmic dark matter and neutrino properties are long-standing problems in cosmology and particle physics. These problems have been investigated by using radiation detectors. We will discuss the application of inorganic crystal scintillators to studies on dark matter and neutrino properties. A large volume and high-purity inorganic crystal is a promising detector for investigating dark matter and neutrino.

Recent JWST observations with superb angular resolution have revealed the existence of clumpy galaxies at high redshift through the detection of rest-frame optical emission lines. We use the FirstLight simulation to study the properties of (sub-)galactic clumps that are bright in [OIII] 5007$\mathrm{\mathring{A}}$ line with flux greater than $\sim 10^{-18} \, {\rm erg\, s^{-1}\, cm^{-2}}$, to be detected by JWST. For 62 simulated galaxies that have stellar masses of $(0.5-6) \times 10^{10} \, M_\odot$ at $z=5$, we find clumps in 1828 snapshots in the redshift range $z = 9.5-5.5$. The clumps are identified by the surface density of star formation rate. About one-tenth of the snapshots show the existence of clumpy systems with two or more components. Most of the clumps are formed by mergers and can be characterized by their ages; central clumps dominated by stellar populations older than 50 Myr, and off-centered clumps dominated by younger stellar populations with specific star formation rates of $\sim 50 \, {\rm Gyr^{-1}}$. The latter type of young clumps is formed from gas debris in the tidal tails of major mergers with baryonic mass ratios of $1 \leq q < 4$. The merger-induced clumps are short-lived, and merge within a dynamical time of several tens million years. The number density of the clumpy systems is estimated to be $\sim 10^{-5}\, {\rm cMpc^{-3}}$, which is large enough to be detected in recent JWST surveys., Comment: Version accepted for publication in ApJ. 19 pages, 10 figures, 3 tables, references added

This work is motivated by the growing demand for reproducible machine learning. We study the stochastic multi-armed bandit problem. In particular, we consider a replicable algorithm that ensures, with high probability, that the algorithm's sequence of actions is not affected by the randomness inherent in the dataset. We observe that existing algorithms require $O(1/\rho^2)$ times more regret than nonreplicable algorithms, where $\rho$ is the level of nonreplication. However, we demonstrate that this additional cost is unnecessary when the time horizon $T$ is sufficiently large for a given $\rho$, provided that the magnitude of the confidence bounds is chosen carefully. We introduce an explore-then-commit algorithm that draws arms uniformly before committing to a single arm. Additionally, we examine a successive elimination algorithm that eliminates suboptimal arms at the end of each phase. To ensure the replicability of these algorithms, we incorporate randomness into their decision-making processes. We extend the use of successive elimination to the linear bandit problem as well. For the analysis of these algorithms, we propose a principled approach to limiting the probability of nonreplication. This approach elucidates the steps that existing research has implicitly followed. Furthermore, we derive the first lower bound for the two-armed replicable bandit problem, which implies the optimality of the proposed algorithms up to a $\log\log T$ factor for the two-armed case.

Session types are a type discipline for describing and specifying communication behaviours of concurrent processes. Session subtyping, firstly introduced by Gay and Hole, is widely used for enlarging typability of session programs. This paper gives the complexity analysis of three algorithms for subtyping of synchronous binary session types. First, we analyse the complexity of the algorithm from the original paper, which is based on an inductive tree search. We then introduce its optimised version, which improves the complexity, but is still exponential against the size of the two types. Finally, we propose a new quadratic algorithm based on a graph search using the concept of $\mathcal{XYZW}$-simulation, recently introduced by Silva et al., Comment: 14 pages, 5 figures. Full version of a paper submitted to PLACES 2024

Speed responses of motors, especially Permanent Magnet Synchronous Motors (PMSMs), are increasing in importance for recent applications, such as electric vehicles or quadrotors. These applications require quick acceleration performance. However, commercial controllers are based mainly on Proportional-Integral (PI) controllers, which are suitable for eliminating steady-state errors but unsuitable for transient response optimization. In this paper, we replaced whole conventional controllers with an end-to-end Recurrent Neural Network (RNN) that has a regularized transition matrix. Our end-to-end controller directly minimizes the transient response time on the basis of optimal control theory. Computer-simulated results show that speed response indices improved using the RNN rather than a PI controller, while both were under comparable power losses. The current vector trajectories of the RNN showed that the RNN could automatically determine arbitrary trajectories in the flux-weakening region in accordance with an arbitrarily designed loss function. In contrast, the traditional flux-weakening methods using PI controllers have pre-determined current vector trajectories.

Purpose: To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen ion therapy. Materials and Methods: Phantoms of polyethylene, gelatin or poly(methyl methacrylate) were irradiated with monoenergetic carbon and oxygen ion beams. Post-irradiation, 4D PET images were acquired and parent $^{11}$C, $^{10}$C and $^{15}$O radionuclides contributions in each voxel were determined from the extracted time activity curves. Experiments were simulated in Geant4 Monte Carlo versions 10-11.1, with three different fragmentation models: binary ion cascade (BIC), quantum molecular dynamics (QMD) and the Liege intranuclear cascade (INCL++) - 30 combinations. Total/parent isotope positron annihilation yields were compared between simulations and experiments using normalised mean squared error and Pearson cross-correlation coefficient. Depth of maximum/distal 50\% peak position yield were also compared. Results: Performance varied considerably across versions and models, with no one best predicting all positron-emitting fragments. BIC in Geant4 10.2 provided the best overall agreement with experimental results in the largest number of test cases. QMD consistently provided the best estimates of both the depth of peak positron yield (10.4 and 10.6) and the distal 50\%-of-peak point (10.2), while BIC also performed well and INCL generally performed the worst across most Geant4 versions. Conclusions: Best spatial prediction of annihilation yield and positron-emitting fragment production during carbon and oxygen ion therapy was found to be 10.2.p03 with BIC or QMD. These version/model combinations are recommended for future heavy ion therapy research., Comment: This manuscript has been submitted to IOP's Journal of Physics in Medicine and Biology, on the 5th of February 2024

We introduce a simple, easy to implement, and computationally efficient tropical convolutional neural network architecture that is robust against adversarial attacks. We exploit the tropical nature of piece-wise linear neural networks by embedding the data in the tropical projective torus in a single hidden layer which can be added to any model. We study the geometry of its decision boundary theoretically and show its robustness against adversarial attacks on image datasets using computational experiments.

An analysis of solar neutrino data from the fourth phase of Super-Kamiokande~(SK-IV) from October 2008 to May 2018 is performed and the results are presented. The observation time of the data set of SK-IV corresponds to $2970$~days and the total live time for all four phases is $5805$~days. For more precise solar neutrino measurements, several improvements are applied in this analysis: lowering the data acquisition threshold in May 2015, further reduction of the spallation background using neutron clustering events, precise energy reconstruction considering the time variation of the PMT gain. The observed number of solar neutrino events in $3.49$--$19.49$ MeV electron kinetic energy region during SK-IV is $65,443^{+390}_{-388}\,(\mathrm{stat.})\pm 925\,(\mathrm{syst.})$ events. Corresponding $\mathrm{^{8}B}$ solar neutrino flux is $(2.314 \pm 0.014\, \rm{(stat.)} \pm 0.040 \, \rm{(syst.)}) \times 10^{6}~\mathrm{cm^{-2}\,s^{-1}}$, assuming a pure electron-neutrino flavor component without neutrino oscillations. The flux combined with all SK phases up to SK-IV is $(2.336 \pm 0.011\, \rm{(stat.)} \pm 0.043 \, \rm{(syst.)}) \times 10^{6}~\mathrm{cm^{-2}\,s^{-1}}$. Based on the neutrino oscillation analysis from all solar experiments, including the SK $5805$~days data set, the best-fit neutrino oscillation parameters are $\rm{sin^{2} \theta_{12,\,solar}} = 0.306 \pm 0.013 $ and $\Delta m^{2}_{21,\,\mathrm{solar}} = (6.10^{+ 0.95}_{-0.81}) \times 10^{-5}~\rm{eV}^{2}$, with a deviation of about 1.5$\sigma$ from the $\Delta m^{2}_{21}$ parameter obtained by KamLAND. The best-fit neutrino oscillation parameters obtained from all solar experiments and KamLAND are $\sin^{2} \theta_{12,\,\mathrm{global}} = 0.307 \pm 0.012 $ and $\Delta m^{2}_{21,\,\mathrm{global}} = (7.50^{+ 0.19}_{-0.18}) \times 10^{-5}~\rm{eV}^{2}$., Comment: 47 pages, 61 figures

Detailed measurements of the spectral structure of cosmic-ray electrons and positrons from 10.6 GeV to 7.5 TeV are presented from over 7 years of observations with the CALorimetric Electron Telescope (CALET) on the International Space Station. Because of the excellent energy resolution (a few percent above 10 GeV) and the outstanding e/p separation (10$^5$), CALET provides optimal performance for a detailed search of structures in the energy spectrum. The analysis uses data up to the end of 2022, and the statistics of observed electron candidates has increased more than 3 times since the last publication in 2018. By adopting an updated boosted decision tree analysis, a sufficient proton rejection power up to 7.5 TeV is achieved, with a residual proton contamination less than 10%. The observed energy spectrum becomes gradually harder in the lower energy region from around 30 GeV, consistently with AMS-02, but from 300 to 600 GeV it is considerably softer than the spectra measured by DAMPE and Fermi-LAT. At high energies, the spectrum presents a sharp break around 1 TeV, with a spectral index change from -3.15 to -3.91, and a broken power law fitting the data in the energy range from 30 GeV to 4.8 TeV better than a single power law with 6.9 sigma significance, which is compatible with the DAMPE results. The break is consistent with the expected effects of radiation loss during the propagation from distant sources (except the highest energy bin). We have fitted the spectrum with a model consistent with the positron flux measured by AMS-02 below 1 TeV and interpreted the electron + positron spectrum with possible contributions from pulsars and nearby sources. Above 4.8 TeV, a possible contribution from known nearby supernova remnants, including Vela, is addressed by an event-by-event analysis providing a higher proton-rejection power than a purely statistical analysis., Comment: main text: 7 pages, 4 figures; supplemental material: 10 pages, 8 figures, 1 table

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)