Search

We demonstrate that a broad class of modular inflation models predicts the emergence of new physics within an energy range of approximately $10^{15}\, \mathrm{GeV}$ to $10^{17} \, \mathrm{GeV}$. This prediction arises by comparing the moduli-dependent species scale with observational constraints on inflation. Specifically, we illustrate this within the context of $SL(2, \mathbb{Z})$-modular inflation models by re-expressing inflationary observables in terms of the species scale. We further discuss the implications of this approach for generic Calabi-Yau threefolds, showing that this reformulation allows us to directly constrain the fundamental parameters related to the geometry of extra dimensions, specifically the second Chern numbers., Comment: 6 pages, 1 figure

Topology optimization is an essential tool in computational engineering, for example, to improve the design and efficiency of flow channels. At the same time, Ising machines, including digital or quantum annealers, have been used as efficient solvers for combinatorial optimization problems. Beyond combinatorial optimization, recent works have demonstrated applicability to other engineering tasks by tailoring corresponding problem formulations. In this study, we present a novel Ising machine formulation for computing design updates during topology optimization with the goal of minimizing dissipation energy in flow channels. We explore the potential of this approach to improve the efficiency and performance of the optimization process. To this end, we conduct experiments to study the impact of various factors within the novel formulation. Additionally, we compare it to a classical method using the number of optimization steps and the final values of the objective function as indicators of the time intensity of the optimization and the performance of the resulting designs, respectively. Our findings show that the proposed update strategy can accelerate the topology optimization process while producing comparable designs. However, it tends to be less exploratory, which may lead to lower performance of the designs. These results highlight the potential of incorporating Ising formulations for optimization tasks but also show their limitations when used to compute design updates in an iterative optimization process. In conclusion, this work provides an efficient alternative for design updates in topology optimization and enhances the understanding of integrating Ising machine formulations in engineering optimization.

A low-dissipation numerical method for compressible gas-liquid two-phase flow with phase change on unstructured grids is proposed. The governing equations adopt the six-equation model. The non-conservative terms included in the volume fraction and total energy equations of the six-equation model are defined on cell boundaries using second-order accurate approximations and calculated without interpolating the spatial derivatives. To capture discontinuities such as contact discontinuities and gas-liquid interfaces with low dissipation, the MUSCL-THINC/QQ-BVD scheme, which combines the Monotone Upstream-centered Schemes for Conservation Laws (MUSCL) method and the Tangent Hyperbola for INterface Capturing method with Quadratic surface representation and Gaussian Quadrature (THINC/QQ) method, is employed. The MUSCL method is one of the mainstream numerical solvers for compressible flows, achieving second-order accuracy for smooth solutions, but it introduces excessive numerical dissipation errors near discontinuous solutions. The THINC/QQ method uses a reconstruction function developed for interface capturing on unstructured grids, making use of a sigmoidal function with a quadratic surface. By combining these reconstruction functions according to the Boundary Variation Diminishing (BVD) principle, the MUSCL method is selected for smooth solutions, while the THINC/QQ method is chosen for discontinuous solutions, preserving the solution structure accurately. Several benchmark tests are solved, demonstrating that the MUSCL-THINC/QQ-BVD scheme not only captures contact discontinuities with low dissipation but also resolves dynamically generated gas-liquid interfaces due to phase changes clearly.

This paper explores the problem of 3D human pose estimation from only low-level acoustic signals. The existing active acoustic sensing-based approach for 3D human pose estimation implicitly assumes that the target user is positioned along a line between loudspeakers and a microphone. Because reflection and diffraction of sound by the human body cause subtle acoustic signal changes compared to sound obstruction, the existing model degrades its accuracy significantly when subjects deviate from this line, limiting its practicality in real-world scenarios. To overcome this limitation, we propose a novel method composed of a position discriminator and reverberation-resistant model. The former predicts the standing positions of subjects and applies adversarial learning to extract subject position-invariant features. The latter utilizes acoustic signals before the estimation target time as references to enhance robustness against the variations in sound arrival times due to diffraction and reflection. We construct an acoustic pose estimation dataset that covers diverse human locations and demonstrate through experiments that our proposed method outperforms existing approaches., Comment: Accepted at BMVC2024

We construct a locally profinite set of cardinality $\aleph_{\omega}$ with infinitely many first cohomology classes of which any distinct finite product does not vanish. Building on this, we construct the first example of a nondescendable faithfully flat map between commutative rings of cardinality $\aleph_{\omega}$ within Zermelo--Fraenkel set theory., Comment: 7 pages

We investigate the possibility and current limitations of flow computations using quantum annealers by solving a fundamental flow problem on Ising machines. As a fundamental problem, we consider the one-dimensional advection-diffusion equation. We formulate it in a form suited to Ising machines (i.e., both classical and quantum annealers), perform extensive numerical tests on a classical annealer, and finally test it on an actual quantum annealer. To make it possible to process with an Ising machine, the problem is formulated as a minimization problem of the residual of the governing equation discretized using either the spectral method or the finite difference method. The resulting system equation is then converted to the Quadratic Unconstrained Binary Optimization (QUBO) form though quantization of variables. It is found in the numerical tests using a classical annealer that the spectral method requiring smaller number of variables has a particular merit over the finite difference method because the accuracy deteriorates with the increase of the number of variables. We also found that the computational error varies depending on the condition number of the coefficient matrix. In addition, we extended it to a two-dimensional problem and confirmed its fundamental applicability. From the numerical test using a quantum annealer, however, it turns out that the computation using a quantum annealer is still challenging due largely to the structural difference from the classical annealer, which leaves a number of issues toward its practical use., Comment: 26 pages, 8 figures

We review lattice results related to pion, kaon, $D$-meson, $B$-meson, and nucleon physics with the aim of making them easily accessible to the nuclear and particle physics communities. More specifically, we report on the determination of the light-quark masses, the form factor $f_+(0)$ arising in the semileptonic $K \to \pi$ transition at zero momentum transfer, as well as the decay-constant ratio $f_K/f_\pi$ and its consequences for the CKM matrix elements $V_{us}$ and $V_{ud}$. We review the determination of the $B_K$ parameter of neutral kaon mixing as well as the additional four $B$ parameters that arise in theories of physics beyond the Standard Model. For the heavy-quark sector, we provide results for $m_c$ and $m_b$ as well as those for the decay constants, form factors, and mixing parameters of charmed and bottom mesons and baryons. These are the heavy-quark quantities most relevant for the determination of CKM matrix elements and the global CKM unitarity-triangle fit. We review the status of lattice determinations of the strong coupling constant $\alpha_s$. We review the determinations of nucleon charges from the matrix elements of both isovector and flavour-diagonal axial, scalar and tensor local quark bilinears, and momentum fraction, helicity moment and the transversity moment from one-link quark bilinears. We also review determinations of scale-setting quantities. Finally, in this review we have added a new section on the general definition of the low-energy limit of the Standard Model., Comment: 435 pages, 53 Figures, 190 tables. arXiv admin note: substantial text overlap with arXiv:2111.09849, arXiv:1902.08191

We report the re-measurement of the $a$-axis spin susceptibility component in an early-stage sample of the spin-triplet superconductor UTe$_2$ with the transition temperature of $T_{\rm SC}$ = 1.6 K. Using Knight-shift measurements along the $b$ axis and at a 10-degree tilt from the $b$ axis towards the $a$ axis, we accurately determined the $a$-axis component without directly measuring the $a$-axis Knight shift. Our results reveal a decrease of approximately 3\% in the $a$-axis spin susceptibility in the superconducting state under $a$-axis magnetic field $\mu_0 H_a \sim 0.1$ T, indicating that the spin susceptibility decreases similarly in both early-stage and ultraclean samples with $T_{\rm SC}$ = 2.1 K. The previously reported absence of the reduction in Knight shift is attributed to the missing of signal from the superconducting region and to the detection of residual signals from the non-superconducting region instead. We also found that the decrease in the $a$-axis spin susceptibility is immediately suppressed with increasing the $a$-axis magnetic field and is estimated to be completely suppressed at around 1.5 T due to superconducting spin rotation., Comment: 5 pages, 3 figures

We propose a method for generating optical cat states in propagating pulses based on cavity quantum electrodynamics (QED). This scheme uses multiple four-level systems (4LSs) inside an optical cavity as an emitter. Time-modulating driving stimulates the emitter to produce a superposition of coherent states entangled with the 4LSs. The postselection of an appropriate state of the 4LSs leads to a multicomponent cat state in a propagating pulse. Taking atomic decay and cavity loss into account, we optimize the cavity external loss rate to maximize the fidelity. We find that its optimum value is formulated similarly to that of other generation methods for propagating states, which suggests a universal property of cavity-QED systems interacting with fields outside the cavity., Comment: Main text: 5 pages, 5 figures, Appendix: 6 pages, 1 figure

We report the magnetoresistance of high-quality single crystals of UTe2 with Tc=2.1K in high magnetic fields up to 36T, with the field direction between the b and c-axes. From the angular dependence of the upper critical field Hc2, we found that the field-reentrant superconducting phase near H // b-axis extends up to a field angle (24 deg) from the b to c-axis, where another field-reentrant superconducting phase begins to appear above the metamagnetic transition field, Hm. Our results suggest that the field-reentrant superconductivity below Hm near the b-axis is closely related to the superconductivity above Hm when the field is tilted toward the c-axis. Superconductivity appears to be robust when the field direction is maintained perpendicular to the magnetization easy axis, implying that fluctuations boosting superconductivity may persist. At first glance, these findings resemble the field-reentrant (reinforced) superconductivity observed in ferromagnetic superconductors URhGe and UCoGe, where Ising-type ferromagnetic fluctuations play a crucial role. However, in UTe2, the fluctuations are more complex. The angular dependence of the upper critical field Hc2 contrasts with that of the initial slope of Hc2 near Tc, revealing the anisotropic field response of fluctuations. Thanks to the high-quality samples, quantum oscillations were detected for field directions close to the c-axis using magnetoresistance (Shubnikov-de Haas effect) and torque (de Haas-van Alphen effect) measurements. The angular dependence of frequencies is in good agreement with those observed previously using the field-modulation technique, confirming quasi-two-dimensional Fermi surfaces., Comment: 6 pages, 4 figures, accepted for publication in J. Phys. Soc. Jpn

Trust and interpretability are crucial for the use of Artificial Intelligence (AI) in scientific research, but current models often operate as black boxes offering limited transparency and justifications for their outputs. We introduce AiSciVision, a framework that specializes Large Multimodal Models (LMMs) into interactive research partners and classification models for image classification tasks in niche scientific domains. Our framework uses two key components: (1) Visual Retrieval-Augmented Generation (VisRAG) and (2) domain-specific tools utilized in an agentic workflow. To classify a target image, AiSciVision first retrieves the most similar positive and negative labeled images as context for the LMM. Then the LMM agent actively selects and applies tools to manipulate and inspect the target image over multiple rounds, refining its analysis before making a final prediction. These VisRAG and tooling components are designed to mirror the processes of domain experts, as humans often compare new data to similar examples and use specialized tools to manipulate and inspect images before arriving at a conclusion. Each inference produces both a prediction and a natural language transcript detailing the reasoning and tool usage that led to the prediction. We evaluate AiSciVision on three real-world scientific image classification datasets: detecting the presence of aquaculture ponds, diseased eelgrass, and solar panels. Across these datasets, our method outperforms fully supervised models in low and full-labeled data settings. AiSciVision is actively deployed in real-world use, specifically for aquaculture research, through a dedicated web application that displays and allows the expert users to converse with the transcripts. This work represents a crucial step toward AI systems that are both interpretable and effective, advancing their use in scientific research and scientific discovery.

This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. In order for multiple robots to perform tasks more efficiently, it is necessary to manage the precedence dependencies between tasks. Although multi-robot decentralized and centralized task planners using LLMs have been proposed, none of these studies focus on precedence dependencies from the perspective of task efficiency or leverage traditional optimization methods. It addresses key challenges in managing dependencies between skills and optimizing task allocation. LiP-LLM consists of three steps: skill list generation and dependency graph generation by LLMs, and task allocation using linear programming. The LLMs are utilized to generate a comprehensive list of skills and to construct a dependency graph that maps the relationships and sequential constraints among these skills. To ensure the feasibility and efficiency of skill execution, the skill list is generated by calculated likelihood, and linear programming is used to optimally allocate tasks to each robot. Experimental evaluations in simulated environments demonstrate that this method outperforms existing task planners, achieving higher success rates and efficiency in executing complex, multi-robot tasks. The results indicate the potential of combining LLMs with optimization techniques to enhance the capabilities of multi-robot systems in executing coordinated tasks accurately and efficiently. In an environment with two robots, a maximum success rate difference of 0.82 is observed in the language instruction group with a change in the object name.

Measurements of the response function of the PIENU NaI(T$\ell$) and CsI crystal calorimeter using a monochromatic 70 MeV/c positron beam at various incidence angles are described. The experimental setup and relevant physical processes involved were simulated using Geant4 to reproduce positron energy spectra. Monte Carlo simulations were compared with experimental data across ten calorimeter-beam angles and showed good agreement. This allowed the validation of simulation parameters that were essential for precise measurements of pion decays., Comment: 7 pages, 9 figures

We determine the Galois module structure of the ring of integers for all cubic fields using roots of the generic cyclic cubic polynomial $f_n(X)=X^3-nX^2-(n+3)X-1$. Let $L_n=\mathbb Q(\rho_n)$ be a cyclic cubic field with Galois group $G:={\rm Gal}(L_n/\mathbb Q)$, where $\rho_n$ is a root of $f_n (X)$, and ${\mathcal O}_{L_n}$ the ring of integers of $L_n$. We explicitly give the generator of the free module ${\mathcal O}_{L_n}$ of rank $1$ over the associated order ${\mathcal A}_{L_n/\mathbb Q}:= \{ x\in \mathbb Q [G] \, |\, x\, {\mathcal O}_L \subset {\mathcal O}_L \}$ by using the roots of $f_n(X)$.

The existence of multiple superconducting phases induced by either pressure or magnetic field is one of the most striking features of superconductivity of UTe$_2$, among the many unusual superconducting properties of this system. Here we report thermodynamic measurements of the superconducting phase diagram combining pressure and magnetic fields up to 30 T. We show that the ambient pressure, high-field, superconducting phase evolves continuously with pressure to join the high-pressure, zero-field superconducting phase. This proves that these two phases are one and the same, and must have the same order parameter., Comment: 5 pages, 5 figure + supplementary material

We develop an on-shell approach to study black hole mergers. Since, asymptotically, the initial and final states can be described by point-like spinning particles, we propose a massive three-point amplitude for the merger of two Schwarzschild black holes into a Kerr black hole. This three-point amplitude and the spectral function of the final state are fully determined by kinematics and the model-independent input about the black hole merger which is described by a complete absorption process. Using the Kosower-Maybee-O'Connell (KMOC) formalism, we then reproduce the classical conservation laws for momentum and angular momentum after the merger. As an application, we use the proposed three-point to compute the graviton emission amplitude, from which we extract the merger waveform to all orders in spin but leading in gravitational coupling. Up to sub-subleading order in spin, this matches the classical soft graviton theorem. We conclude with a comparison to black hole perturbation theory, which gives complementary amplitudes which are non-perturbative in the gravitational coupling but to leading order in the extreme mass ratio limit. This also highlights how boundary conditions on a Schwarzschild background can be used to rederive the proposed on-shell amplitudes for merger processes., Comment: 44 pages

In this paper, we propose to pre-train audio encoders using synthetic patterns instead of real audio data. Our proposed framework consists of two key elements. The first one is Masked Autoencoder (MAE), a self-supervised learning framework that learns from reconstructing data from randomly masked counterparts. MAEs tend to focus on low-level information such as visual patterns and regularities within data. Therefore, it is unimportant what is portrayed in the input, whether it be images, audio mel-spectrograms, or even synthetic patterns. This leads to the second key element, which is synthetic data. Synthetic data, unlike real audio, is free from privacy and licensing infringement issues. By combining MAEs and synthetic patterns, our framework enables the model to learn generalized feature representations without real data, while addressing the issues related to real audio. To evaluate the efficacy of our framework, we conduct extensive experiments across a total of 13 audio tasks and 17 synthetic datasets. The experiments provide insights into which types of synthetic patterns are effective for audio. Our results demonstrate that our framework achieves performance comparable to models pre-trained on AudioSet-2M and partially outperforms image-based pre-training methods., Comment: Submitted to ICASSP'25

The mass shift a spin-1 particle moving in the nuclear medium will depend on its polarization direction. To study polarization-independent mass shifts in the medium, we explore methods to isolate each polarization direction of spin-1 mesons through the angular-dependent two-body decay modes. Specifically, we study $\phi\to K^{+}K^{-}$, $\rho\to\pi\pi$, $K^{*}\to K\pi$, $\phi\to e^{+}e^{-}$ and $K_{1}\to\rho K(K^{*}\pi)$ decays. While each polarization mode can be isolated through angular dependencies, accomplishing the decomposition for the $K_1$ meson further requires measuring the polarization of the $\rho(K^*)$ meson. Concerning $K^{*}$ and $K_1$ mesons, since both particles have vacuum widths smaller than 100 MeV, they are ideal candidates for experimentally measuring chiral partners. The simultaneous observation of mass shifts of these chiral partners would provide valuable insights into the contribution of chiral symmetry breaking to the generation of hadron masses., Comment: Proceeding for the Reimi Workshop "Hadron interactions with strangeness and charm", held in Jeju on June 27-28, 2024

Building large-scale quantum computers requires an interqubit-coupling scheme with a high on-off ratio to avoid unwanted crosstalk coming from residual coupling and to enable fast multi-qubit operations. We propose a $ZZ$-coupling scheme for two Kerr-cat qubits with a frequency-tunable coupler. By making four relevant states of the two Kerr-cat qubits quadruply degenerate, we can switch off the $ZZ$ coupling. By partially lifting the level degeneracy, we can switch it on. We theoretically show that an experimentally feasible circuit model suppresses the residual $ZZ$ coupling. Moreover, our circuit can realize $R_{ZZ}(-\pi/2)$-gate fidelity higher than $99.999\%$ within $25\,$ns when decoherence is ignored., Comment: 9 pages, 5 figures

Major retinal layer segmentation methods from OCT images assume that the retina is flattened in advance, and thus cannot always deal with retinas that have changes in retinal structure due to ophthalmopathy and/or curvature due to myopia. To eliminate the use of flattening in retinal layer segmentation for practicality of such methods, we propose novel data augmentation methods for OCT images. Formula-driven data augmentation (FDDA) emulates a variety of retinal structures by vertically shifting each column of the OCT images according to a given mathematical formula. We also propose partial retinal layer copying (PRLC) that copies a part of the retinal layers and pastes it into a region outside the retinal layers. Through experiments using the OCT MS and Healthy Control dataset and the Duke Cyst DME dataset, we demonstrate that the use of FDDA and PRLC makes it possible to detect the boundaries of retinal layers without flattening even retinal layer segmentation methods that assume flattening of the retina., Comment: The 11th OMIA Workshop on MICCAI 2024

Layered material $\beta$-IrSn$_4$ ($I4_1/acd$, $D^{20}_{4h}$, #142), whose electron bands have symmetry-enforced Dirac points, was investigated using high-quality single crystals. It exhibits a pronounced linear field-dependence of magnetoresistance (LMR), which cannot be explained by currently existing models. Structures in the field-angle dependence of magnetoresistance and Hall resistivity are attributable to the Fermi surface topology; the presence of open orbits is inferred. At the superconducting (SC) transition, the specific-heat jump exhibits a significant increase in applied fields, revealing the type-I SC nature. This feature is attributable to the high Fermi velocity of linearly dispersive multibands. To clarify the mechanism of the puzzling LMR, investigations into the topological nature of those multibands in applied fields are highly desired.

Multibiometrics, which uses multiple biometric traits to improve recognition performance instead of using only one biometric trait to authenticate individuals, has been investigated. Previous studies have combined individually acquired biometric traits or have not fully considered the convenience of the system.Focusing on a single face image, we propose a novel multibiometric method that combines five biometric traits, i.e., face, iris, periocular, nose, eyebrow, that can be extracted from a single face image. The proposed method does not sacrifice the convenience of biometrics since only a single face image is used as input.Through a variety of experiments using the CASIA Iris Distance database, we demonstrate the effectiveness of the proposed multibiometrics method., Comment: APSIPA ASC 2024

We report the first measurement of the azimuthal anisotropy of J$/\psi$ at forward rapidity ($1.2<|\eta|<2.2$) in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV at the Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The second Fourier coefficient ($v_2$) of the azimuthal distribution of $J/\psi$ is determined as a function of the transverse momentum ($p_T$) using the event-plane method. The measurements were performed for several selections of collision centrality: 0\%--50\%, 10\%--60\%, and 10\%-40\%. We find that in all cases the values of $v_2(p_T)$, which quantify the elliptic flow of J$/\psi$, are consistent with zero. The results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the J$/\psi$ within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{_{NN}}}=200$ GeV., Comment: 369 authors from 72 institutions, 12 pages, 7 figures, 5 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We present the first forward-rapidity measurements of elliptic anisotropy of open-heavy-flavor muons at the BNL Relativistic Heavy Ion Collider. The measurements are based on data samples of Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The measurements are performed in the pseudorapidity range $1.2<|\eta|<2$ and cover transverse momenta $1

Based on his claims in 1990, Rosenberg conjectured in 1997 that the negative algebraic $K$-groups of C*-algebras are invariant under continuous homotopy. Contrary to his expectation, we prove that such invariance holds for $K_{-1}$ of arbitrary Banach rings by establishing a certain continuity result. We also construct examples demonstrating that similar continuity results do not hold for lower $K$-groups., Comment: 10 pages

Four-wheel independent drive and steering vehicle (4WIDS Vehicle, Swerve Drive Robot) has the ability to move in any direction by its eight degrees of freedom (DoF) control inputs. Although the high maneuverability enables efficient navigation in narrow spaces, obtaining the optimal command is challenging due to the high dimension of the solution space. This paper presents a navigation architecture using the Model Predictive Path Integral (MPPI) control algorithm to avoid collisions with obstacles of any shape and reach a goal point. The key idea to make the problem easier is to explore the optimal control input in a reasonably reduced dimension that is adequate for navigation. Through evaluation in simulation, we found that selecting the sampling space of MPPI greatly affects navigation performance. In addition, our proposed controller which switches multiple sampling spaces according to the real-time situation can achieve balanced behavior between efficiency and safety. Source code is available at https://github.com/MizuhoAOKI/mppi_swerve_drive_ros

Understanding the rapid formation of supermassive black holes (SMBHs) in the early universe requires an understanding of how stellar mass grows in the host galaxies. Here, we perform an analysis of rest-frame optical spectra and imaging from JWST of two quasar host galaxies at z>6 which exhibit Balmer absorption lines. These features in the stellar continuum indicate a lack of young stars, similar to low-redshift post-starburst galaxies whose star formation was recently quenched. We find that the stellar mass (log(M_* / M_sun) > 10.6) of each quasar host grew in a starburst episode at redshift 7 or 8. One of the targets exhibits little ongoing star formation, as evidenced by the photometric signature of the Balmer break and a lack of spatially resolved H-alpha emission, placing it well below the star formation main sequence at z = 6. The other galaxy is transitioning to a quiescent phase; together, the two galaxies represent the most distant massive post-starburst galaxies known. The maturity of these two galaxies is further supported by the stellar velocity dispersions of their host galaxies, placing them slightly above the upper end of the local M_BH - sigma_* relation. The properties of our two post-starburst galaxies, each hosting an active SMBH with log(M_BH / M_sun) > 9, suggests that black holes played a major role in shaping the formation of the first massive galaxies in the Universe., Comment: 24 pages, 7 figures, submitted to a Nature journal

Pre-training video transformers generally requires a large amount of data, presenting significant challenges in terms of data collection costs and concerns related to privacy, licensing, and inherent biases. Synthesizing data is one of the promising ways to solve these issues, yet pre-training solely on synthetic data has its own challenges. In this paper, we introduce an effective self-supervised learning framework for videos that leverages readily available and less costly static images. Specifically, we define the Pseudo Motion Generator (PMG) module that recursively applies image transformations to generate pseudo-motion videos from images. These pseudo-motion videos are then leveraged in masked video modeling. Our approach is applicable to synthetic images as well, thus entirely freeing video pre-training from data collection costs and other concerns in real data. Through experiments in action recognition tasks, we demonstrate that this framework allows effective learning of spatio-temporal features through pseudo-motion videos, significantly improving over existing methods which also use static images and partially outperforming those using both real and synthetic videos. These results uncover fragments of what video transformers learn through masked video modeling., Comment: ECCV 2024

The objective of this study is to establish a gradient-free topology optimization framework that facilitates more global solution searches to avoid entrapping in undesirable local optima, especially in problems with strong non-linearity. The framework utilizes a data-driven multifidelity topology design, where solution candidates resulting from low-fidelity optimization problems are iteratively updated by a variational auto-encoder (VAE) and high-fidelity (HF) evaluation. A key step in the solution update involves constructing HF models by extruding VAE-generated material distributions to a constant thickness (the HF modeling parameter) across all candidates, which limits exploration of the parameter space and requires extensive parametric studies outside the optimization loop. To achieve comprehensive optimization in a single run, we propose a multi-channel image data architecture that stores material distributions and HF modeling parameters in separate channels, allowing simultaneous optimization of the HF parameter space. We demonstrated the efficacy of the proposed framework by solving a maximum stress minimization problem, characterized by strong non-linearity due to its minimax formulation.

The superconducting diode effect (SDE), where zero-resistance states appear nonreciprocally during current injection, is receiving tremendous interest in both fundamental and applied physics because the SDE is a novel manifestation of symmetry breaking and enables the creation of a novel diode without energy loss. In particular, magnetic-field-free SDEs have been extensively investigated because of their potential to serve as building blocks for superconducting circuit technology. In this letter, we report the field-free SDE in a layered superconductor, FeSe. Its underlying physics is clarified by systematic controlled experiments to be an interplay of a large thermoelectric response and geometrical asymmetry in FeSe. Our findings can pave a new avenue for the construction of novel material and device platforms utilizing SDEs., Comment: 16 pages, 5 figures

Clausen--Scholze introduced the notion of solid spectrum in their condensed mathematics program. We demonstrate that the solidification of algebraic $K$-theory recovers two known constructions: the semitopological $K$-theory of a real (associative) algebra and the topological (aka operator) $K$-theory of a real Banach algebra., Comment: 23 pages

In this work, we investigate the understudied effect of the training data used for image super-resolution (SR). Most commonly, novel SR methods are developed and benchmarked on common training datasets such as DIV2K and DF2K. However, we investigate and rethink the training data from the perspectives of diversity and quality, {thereby addressing the question of ``How important is SR training for SR models?''}. To this end, we propose an automated image evaluation pipeline. With this, we stratify existing high-resolution image datasets and larger-scale image datasets such as ImageNet and PASS to compare their performances. We find that datasets with (i) low compression artifacts, (ii) high within-image diversity as judged by the number of different objects, and (iii) a large number of images from ImageNet or PASS all positively affect SR performance. We hope that the proposed simple-yet-effective dataset curation pipeline will inform the construction of SR datasets in the future and yield overall better models., Comment: Accepted to ECCV2024

The mini proceedings of the "Fourth International Workshop on the Extension Project for the J-PARC Hadron Experimental Facility (HEF-ex 2024) [https://kds.kek.jp/event/46965]" held at J-PARC, February 19-21, 2024, are presented. The workshop was devoted to discussing the physics case that connects both the present and the future Hadron Experimental Facility at J-PARC, covering a wide range of topics in flavor, hadron, and nuclear physics related to both experimental and theoretical activities being conducted at the facility.

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

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

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Autonomous driving, particularly navigating complex and unanticipated scenarios, demands sophisticated reasoning and planning capabilities. While Multi-modal Large Language Models (MLLMs) offer a promising avenue for this, their use has been largely confined to understanding complex environmental contexts or generating high-level driving commands, with few studies extending their application to end-to-end path planning. A major research bottleneck is the lack of large-scale annotated datasets encompassing vision, language, and action. To address this issue, we propose CoVLA (Comprehensive Vision-Language-Action) Dataset, an extensive dataset comprising real-world driving videos spanning more than 80 hours. This dataset leverages a novel, scalable approach based on automated data processing and a caption generation pipeline to generate accurate driving trajectories paired with detailed natural language descriptions of driving environments and maneuvers. This approach utilizes raw in-vehicle sensor data, allowing it to surpass existing datasets in scale and annotation richness. Using CoVLA, we investigate the driving capabilities of MLLMs that can handle vision, language, and action in a variety of driving scenarios. Our results illustrate the strong proficiency of our model in generating coherent language and action outputs, emphasizing the potential of Vision-Language-Action (VLA) models in the field of autonomous driving. This dataset establishes a framework for robust, interpretable, and data-driven autonomous driving systems by providing a comprehensive platform for training and evaluating VLA models, contributing to safer and more reliable self-driving vehicles. The dataset is released for academic purpose.

We investigate the independent chiral zero modes on the orbifolds from the Atiyah-Segal-Singer fixed point theorem. The required information for this calculation includes the fixed points of the orbifold and the manner in which the spatial symmetries act on these points, unlike previous studies that necessitated the calculation of zero modes. Since the fixed point theorem can be applied to any fermionic theory on any orbifold, it allows us to determine the index even on orbifolds where the calculation of zero modes is challenging or in the presence of non-trivial gauge configurations. We compute the indices on the $T^{2}/ \mathbb{Z}_N\,(N=2,3,4,6)$ and $T^{4}/ \mathbb{Z}_N\,(N=2,3,5)$ as examples. Furthermore, we also attempt to compute the indices on a Coxeter orbifold related to the $D_4$ lattice., Comment: 34 pages

Cosmological collider signals of primordial non-Gaussianity arise at tree level when an extra scalar has Hubble mass during inflation. We critically review the formalism finding that a large class of inflationary theories, based on Planck-scale physics, predict a scalar bi-spectrum around the gravitational floor level. This mild signal arises for example in $R^2$ gravity, in the regime where its gravitational scalar has Hubble-scale mass. Signals much above the gravitational floor arise in theories where scalars undergo multiple turns during inflation, thanks to sub-Planckian physics., Comment: 33 pages, 7 figures. v2: version to appear on JHEP, references added. Webinar presentation: https://youtu.be/KweuhqBxhuE

Advancing defensive mechanisms against adversarial attacks in generative models is a critical research topic in machine learning. Our study focuses on a specific type of generative models - Variational Auto-Encoders (VAEs). Contrary to common beliefs and existing literature which suggest that noise injection towards training data can make models more robust, our preliminary experiments revealed that naive usage of noise augmentation technique did not substantially improve VAE robustness. In fact, it even degraded the quality of learned representations, making VAEs more susceptible to adversarial perturbations. This paper introduces a novel framework that enhances robustness by regularizing the latent space divergence between original and noise-augmented data. Through incorporating a paired probabilistic prior into the standard variational lower bound, our method significantly boosts defense against adversarial attacks. Our empirical evaluations demonstrate that this approach, termed Robust Augmented Variational Auto-ENcoder (RAVEN), yields superior performance in resisting adversarial inputs on widely-recognized benchmark datasets.

Measurements of the upper atmosphere at ~100 km are important to investigate climate change, space weather forecasting, and the interaction between the Sun and the Earth. Atmospheric occultations of cosmic X-ray sources are an effective technique to measure the neutral density in the upper atmosphere. We are developing the instrument SUIM dedicated to continuous observations of atmospheric occultations. SUIM will be mounted on a platform on the exterior of the International Space Station for six months and pointed at the Earth's rim to observe atmospheric absorption of the cosmic X-ray background (CXB). In this paper, we conducted a feasibility study of SUIM by estimating the CXB statistics and the fraction of the non-X-ray background (NXB) in the observed data. The estimated CXB statistics are enough to evaluate the atmospheric absorption of CXB for every 15 km of altitude. On the other hand, the NXB will be dominant in the X-ray spectra of SUIM. Assuming that the NXB per detection area of SUIM is comparable to that of the soft X-ray Imager onboard Hitomi, the NXB level will be much higher than the CXB one and account for ~80% of the total SUIM spectra., Comment: 5 pages, 5 figures, Proceedings of SPIE Astronomical Telescopes and Instrumentation 2024

In this study, we propose a shared control method for teleoperated mobile robots using brain-machine interfaces (BMI). The control commands generated through BMI for robot operation face issues of low input frequency, discreteness, and uncertainty due to noise. To address these challenges, our method estimates the user's intended goal from their commands and uses this goal to generate auxiliary commands through the autonomous system that are both at a higher input frequency and more continuous. Furthermore, by defining the confidence level of the estimation, we adaptively calculated the weights for combining user and autonomous commands, thus achieving shared control.

We mathematically show an equality between the index of a Dirac operator on a flat continuum torus and the $\eta$ invariant of the Wilson Dirac operator with a negative mass when the lattice spacing is sufficiently small. Unlike the standard approach, our formulation using $K$-theory does not require the Ginsparg-Wilson relation or the modified chiral symmetry on the lattice. We prove that a one-parameter family of continuum massive Dirac operators and the corresponding Wilson Dirac operators belong to the same equivalence class of the $K^1$ group at a finite lattice spacing. Their indices, which are evaluated by the spectral flow or equivalently by the $\eta$ invariant at finite masses, are proved to be equal., Comment: 51 pages, 3 figures

We introduce trianguline deformation spaces $X_{\tri} (\overline{\rho})$ for a $\GSp_{2n}$-valued residual representation $\overline{\rho} \colon {\mathcal{G}}_K \to \GSp_{2n} (k)$, where $k$ is a finite field of characteristic $p > 0$ and ${\mathcal{G}}_K$ is the absolute Galois group of a finite extension $K / {\mathbb{Q}}_p$, and study their properties. We show Zariski density of the crystalline points on the rigid generic fiber ${\mathfrak{X}}_{\overline{\rho}}$ of the framed deformation space of $\overline{\rho}$ under some conditions., Comment: 34 pages

The upper atmosphere at the altitude of 60-110 km, the mesosphere and lower thermosphere (MLT), has the least observational data of all atmospheres due to the difficulties of in-situ observations. Previous studies demonstrated that atmospheric occultation of cosmic X-ray sources is an effective technique to investigate the MLT. Aiming to measure the atmospheric density of the MLT continuously, we are developing an X-ray camera, "Soipix for observing Upper atmosphere as Iss experiment Mission (SUIM)", dedicated to atmospheric observations. SUIM will be installed on the exposed area of the International Space Station (ISS) and face the ram direction of the ISS to point toward the Earth rim. Observing the cosmic X-ray background (CXB) transmitted through the atmosphere, we will measure the absorption column density via spectroscopy and thus obtain the density of the upper atmosphere. The X-ray camera is composed of a slit collimator and two X-ray SOI-CMOS pixel sensors (SOIPIX), and will stand on its own and make observations, controlled by a CPU-embedded FPGA "Zynq". We plan to install the SUIM payload on the ISS in 2025 during the solar maximum. In this paper, we report the overview and the development status of this project., Comment: 5 pages, 2 figures, Proceedings of SPIE Astronomical Telescopes and Instrumentation 2024

Large Language Models (LLMs) have shown remarkable performance in various natural language tasks, but they often struggle with planning problems that require structured reasoning. To address this limitation, the conversion of planning problems into the Planning Domain Definition Language (PDDL) has been proposed as a potential solution, enabling the use of automated planners. However, generating accurate PDDL files typically demands human inputs or correction, which can be time-consuming and costly. In this paper, we propose a novel approach that leverages LLMs and environment feedback to automatically generate PDDL domain and problem description files without the need for human intervention. Our method introduces an iterative refinement process that generates multiple problem PDDL candidates and progressively refines the domain PDDL based on feedback obtained from interacting with the environment. To guide the refinement process, we develop an Exploration Walk (EW) metric, which provides rich feedback signals for LLMs to update the PDDL file. We evaluate our approach on $10$ PDDL environments. We achieve an average task solve rate of 66% compared to a 29% solve rate by GPT-4's intrinsic planning with chain-of-thought prompting. Our work enables the automated modeling of planning environments using LLMs and environment feedback, eliminating the need for human intervention in the PDDL translation process and paving the way for more reliable LLM agents in challenging problems. Our code is available at https://github.com/BorealisAI/llm-pddl-planning, Comment: Neurips 2024

The amount of Magnetic resonance imaging data has grown tremendously recently, creating an urgent need to accelerate data processing, which requires substantial computational resources and time. In this preliminary study, we applied FMRIB Software Library commands on T1-weighted and diffusion-weighted images of a single young adult using the Fugaku supercomputer. The tensor-based measurements and subcortical structure segmentations performed on Fugaku supercomputer were highly consistent with those from conventional systems, demonstrating its reliability and significantly reduced processing time.

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The magnetic skyrmions generated in a centrosymmetric crystal were recently first discovered in Gd2PdSi3. In light of this, we observe the electronic structure by angle-resolved photoemission spectroscopy (ARPES) and unveil its direct relationship with the magnetism in this compound. The Fermi surface and band dispersions are demonstrated to have a good agreement with the density functional theory (DFT) calculations carried out with careful consideration of the crystal superstructure. Most importantly, we find that the three-dimensional Fermi surface has extended nesting which matches well the q-vector of the magnetic order detected by recent scattering measurements. The consistency we find among ARPES, DFT, and the scattering measurements suggests the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction involving itinerant electrons to be the formation mechanism of skyrmions in Gd2PdSi3.