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We construct backreacted geometries dual to the supersymmetric mass deformation of the IKKT matrix model. They are Euclidean type IIB supergravity solutions given in terms of an electrostatic potential, having $SO(7)\times SO(3)$ isometry and 16 supersymmetries. Quantizing the fluxes, we find that the supergravity solutions are in one-to-one correspondence with fuzzy sphere vacua of the matrix model., Comment: 22 pages + appendices, 3 figures

We introduce PLaMo-100B, a large-scale language model designed for Japanese proficiency. The model was trained from scratch using 2 trillion tokens, with architecture such as QK Normalization and Z-Loss to ensure training stability during the training process. Post-training techniques, including Supervised Fine-Tuning and Direct Preference Optimization, were applied to refine the model's performance. Benchmark evaluations suggest that PLaMo-100B performs well, particularly in Japanese-specific tasks, achieving results that are competitive with frontier models like GPT-4. The base model is available at https://huggingface.co/pfnet/plamo-100b.

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

In this paper, we give closed form expressions of the Frobenius number for the triple of the $2$-step star numbers $an(n-2) + 1$ for an integer $a \geq 4$. These numbers have been studied from different aspects for some $a$'s. These numbers can also be considered as variations of the well known star numbers of the form $6n(n-1) + 1$. We also give closed form expressions of the Sylvester number (genus) for the triple of the $2$-step star numbers.

In this paper, we propose and design a new task called audio moment retrieval (AMR). Unlike conventional language-based audio retrieval tasks that search for short audio clips from an audio database, AMR aims to predict relevant moments in untrimmed long audio based on a text query. Given the lack of prior work in AMR, we first build a dedicated dataset, Clotho-Moment, consisting of large-scale simulated audio recordings with moment annotations. We then propose a DETR-based model, named Audio Moment DETR (AM-DETR), as a fundamental framework for AMR tasks. This model captures temporal dependencies within audio features, inspired by similar video moment retrieval tasks, thus surpassing conventional clip-level audio retrieval methods. Additionally, we provide manually annotated datasets to properly measure the effectiveness and robustness of our methods on real data. Experimental results show that AM-DETR, trained with Clotho-Moment, outperforms a baseline model that applies a clip-level audio retrieval method with a sliding window on all metrics, particularly improving Recall1@0.7 by 9.00 points. Our datasets and code are publicly available in https://h-munakata.github.io/Language-based-Audio-Moment-Retrieval.

Current audio-visual representation learning can capture rough object categories (e.g., ``animals'' and ``instruments''), but it lacks the ability to recognize fine-grained details, such as specific categories like ``dogs'' and ``flutes'' within animals and instruments. To address this issue, we introduce DETECLAP, a method to enhance audio-visual representation learning with object information. Our key idea is to introduce an audio-visual label prediction loss to the existing Contrastive Audio-Visual Masked AutoEncoder to enhance its object awareness. To avoid costly manual annotations, we prepare object labels from both audio and visual inputs using state-of-the-art language-audio models and object detectors. We evaluate the method of audio-visual retrieval and classification using the VGGSound and AudioSet20K datasets. Our method achieves improvements in recall@10 of +1.5% and +1.2% for audio-to-visual and visual-to-audio retrieval, respectively, and an improvement in accuracy of +0.6% for audio-visual classification., Comment: under review

Self-supervised speech representation learning has become essential for extracting meaningful features from untranscribed audio. Recent advances highlight the potential of deriving discrete symbols from the features correlated with linguistic units, which enables text-less training across diverse tasks. In particular, sentence-level Self-Distillation of the pretrained HuBERT (SD-HuBERT) induces syllabic structures within latent speech frame representations extracted from an intermediate Transformer layer. In SD-HuBERT, sentence-level representation is accumulated from speech frame features through self-attention layers using a special CLS token. However, we observe that the information aggregated in the CLS token correlates more with speaker identity than with linguistic content. To address this, we propose a speech-only self-supervised fine-tuning approach that separates syllabic units from speaker information. Our method introduces speaker perturbation as data augmentation and adopts a frame-level training objective to prevent the CLS token from aggregating paralinguistic information. Experimental results show that our approach surpasses the current state-of-the-art method in most syllable segmentation and syllabic unit quality metrics on Librispeech, underscoring its effectiveness in promoting syllabic organization within speech-only models., Comment: Accepted by IEEE SLT 2024

Recently, the concept of the $p$-numerical semigroup with $p$-symmetric properties has been introduced. When $p=0$, the classical numerical semigroup with symmetric properties is recovered. In this paper, we further study the $p$-numerical semigroup with $p$-almost symmetric properties. We also give $p$-generalized formulas of Watanabe and Johnson, and introduce $p$-Arf numerical semigroup and study its properties.

We initiate the S-matrix bootstrap analysis of theories with non-invertible symmetries in (1+1) dimensions. Our previous work showed that crossing symmetry of S-matrices in such theories is modified, with modification characterized by the fusion category data. By imposing unitarity, symmetry and the modified crossing, we constrain the space of consistent S-matrices, identifying integrable theories with non-invertible symmetries at the cusps of allowed regions. We also extend the modified crossing rules to cases where vacua transform in non-regular representations of fusion category, utilizing a connection to a dual category $\mathscr C^{*}_{\mathscr{M}}$ and Symmetry Topological Field Theory (SymTFT). This highlights the utility of SymTFT in the analysis of scattering amplitudes., Comment: 33 pages plus appendices, v3: references added, typos corrected, appendix added

To clarify a holographic modified thermodynamic relation, the present study applies a general formulation for cosmological equations in a flat FLRW universe to the first law of thermodynamics, using the Bekenstein-Hawking entropy $S_{\rm{BH}}$ and a dynamical Kodama-Hayward temperature $T_{\rm{KH}}$. For the general formulation, both an effective pressure $p_{e}$ of cosmological fluids for dissipative universes (e.g., bulk viscous cosmology) and an extra driving term $f_{\Lambda}(t)$ for non-dissipative universes (e.g., time-varying $\Lambda (t)$ cosmology) are phenomenologically assumed. When $f_{\Lambda}(t)$ is constant, the modified thermodynamic relation is equivalent to the formulation of the first law in standard cosmology. One side of this modified relation describes thermodynamic quantities in the bulk and can be divided into two time-derivative terms, namely $\dot{\rho}$ and $\dot{V}$ terms, where $\rho$ is the mass density of cosmological fluids and $V$ is the Hubble volume. Using the Gibbons-Hawking temperature $T_{\rm{GH}}$, the other side of this relation, $T_{\rm{KH}} \dot{S}_{\rm{BH}}$, can be formulated as the sum of $T_{\rm{GH}} \dot{S}_{\rm{BH}}$ and $[(T_{\rm{KH}}/T_{\rm{GH}}) -1] T_{\rm{GH}} \dot{S}_{\rm{BH}}$, which are equivalent to the $\dot{\rho}$ and $\dot{V}$ terms, respectively, with the magnitude of the $\dot{V}$ term being proportional to the square of the $\dot{\rho}$ term. In addition, the modified thermodynamic relation for constant $f_{\Lambda}(t)$ is examined by applying the equipartition law of energy on the horizon. This modified thermodynamic relation reduces to a kind of extended holographic-like connection when a constant $T_{\rm{KH}}$ universe is considered. The evolution of thermodynamic quantities is also discussed, using a constant $T_{\rm{KH}}$ model, extending a previous analysis [Phys. Rev. D 108, 083515 (2023) (arXiv:2306.11285)]., Comment: 17 pages, 3 figures

We propose Lighthouse, a user-friendly library for reproducible video moment retrieval and highlight detection (MR-HD). Although researchers proposed various MR-HD approaches, the research community holds two main issues. The first is a lack of comprehensive and reproducible experiments across various methods, datasets, and video-text features. This is because no unified training and evaluation codebase covers multiple settings. The second is user-unfriendly design. Because previous works use different libraries, researchers set up individual environments. In addition, most works release only the training codes, requiring users to implement the whole inference process of MR-HD. Lighthouse addresses these issues by implementing a unified reproducible codebase that includes six models, three features, and five datasets. In addition, it provides an inference API and web demo to make these methods easily accessible for researchers and developers. Our experiments demonstrate that Lighthouse generally reproduces the reported scores in the reference papers. The code is available at https://github.com/line/lighthouse., Comment: accepted at EMNLP2024 - system demonstration track

We assess the capabilities of the LiteBIRD mission to map the hot gas distribution in the Universe through the thermal Sunyaev-Zeldovich (SZ) effect. Our analysis relies on comprehensive simulations incorporating various sources of Galactic and extragalactic foreground emission, while accounting for specific instrumental characteristics of LiteBIRD, such as detector sensitivities, frequency-dependent beam convolution, inhomogeneous sky scanning, and $1/f$ noise. We implement a tailored component-separation pipeline to map the thermal SZ Compton $y$-parameter over 98% of the sky. Despite lower angular resolution for galaxy cluster science, LiteBIRD provides full-sky coverage and, compared to the Planck satellite, enhanced sensitivity, as well as more frequency bands to enable the construction of an all-sky $y$-map, with reduced foreground contamination at large and intermediate angular scales. By combining LiteBIRD and Planck channels in the component-separation pipeline, we obtain an optimal $y$-map that leverages the advantages of both experiments, with the higher angular resolution of the Planck channels enabling the recovery of compact clusters beyond the LiteBIRD beam limitations, and the numerous sensitive LiteBIRD channels further mitigating foregrounds. The added value of LiteBIRD is highlighted through the examination of maps, power spectra, and one-point statistics of the various sky components. After component separation, the $1/f$ noise from LiteBIRD is effectively mitigated below the thermal SZ signal at all multipoles. Cosmological constraints on $S_8=\sigma_8\left(\Omega_{\rm m}/0.3\right)^{0.5}$ obtained from the LiteBIRD-Planck combined $y$-map power spectrum exhibits a 15% reduction in uncertainty compared to constraints from Planck alone. This improvement can be attributed to the increased portion of uncontaminated sky available in the LiteBIRD-Planck combined $y$-map., Comment: 38 pages, 13 figures, abstract shortened. Updated to match version accepted by JCAP

Domestic service robots (DSRs) that support people in everyday environments have been widely investigated. However, their ability to predict and describe future risks resulting from their own actions remains insufficient. In this study, we focus on the linguistic explainability of DSRs. Most existing methods do not explicitly model the region of possible collisions; thus, they do not properly generate descriptions of these regions. In this paper, we propose the Nearest Neighbor Future Captioning Model that introduces the Nearest Neighbor Language Model for future captioning of possible collisions, which enhances the model output with a nearest neighbors retrieval mechanism. Furthermore, we introduce the Collision Attention Module that attends regions of possible collisions, which enables our model to generate descriptions that adequately reflect the objects associated with possible collisions. To validate our method, we constructed a new dataset containing samples of collisions that can occur when a DSR places an object in a simulation environment. The experimental results demonstrated that our method outperformed baseline methods, based on the standard metrics. In particular, on CIDEr-D, the baseline method obtained 25.09 points, whereas our method obtained 33.08 points., Comment: Accepted for presentation at Advanced Robotics 24

In this study, we considered the problem of estimating epidemiological parameters based on physics-informed neural networks (PINNs). In practice, not all trajectory data corresponding to the population estimated by epidemic models can be obtained, and some observed trajectories are noisy. Learning PINNs to estimate unknown epidemiological parameters using such partial observations is challenging. Accordingly, we introduce the concept of algebraic observability into PINNs. The validity of the proposed PINN, named as an algebraically observable PINNs, in terms of estimation parameters and prediction of unobserved variables, is demonstrated through numerical experiments.

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 GRAINE project observes cosmic gamma-rays, using a balloon-borne emulsion-film-based telescope in the sub-GeV/GeV energy band. We reported in our previous balloon experiment in 2018, GRAINE2018, the detection of the known brightest source, Vela pulsar, with the highest angular resolution ever reported in an energy range of $>$80 MeV. However, the emulsion scanning system used in the experiment was designed to achieve a high-speed scanning, and it was not accurate enough to ensure the optimum spacial resolution of the emulsion film and limited the performance. Here, we report a new high-precision scanning system that can be used to greatly improve the observation result of GRAINE2018 and also be employed in future experiments. The system involves a new algorithm that recognizes each silver grain on an emulsion film and is capable of measuring tracks with a positional resolution for the passing points of tracks of almost the same as the intrinsic resolution of nuclear emulsion film ($\sim$70 nm). This resolution is approximately one order of magnitude smaller than that obtained with the high-speed scanning system. With this system, an angular resolution for gamma-rays of 0.1$^\circ$ at 1 GeV is expected to be achieved. Furthermore, we successfully combine the new high-precision system with the existing high-speed system, establishing the system to make a high-speed and high-precision measurement. Employing these systems, we reanalyze the gamma-ray events detected previously by only the high-speed system in GRAINE2018 and obtain an about three times higher angular resolution (0.22$^\circ$) in 500--700 MeV than the original value. The high-resolution observation may bring new insights into the gamma-ray emission from the Galactic center region and may realize polarization measurements of high-energy cosmic gamma-rays., Comment: 20 pages, 11 figures

We introduce the Parity-Odd Power (POP) spectra, a novel set of observables for probing parity violation in cosmological $N$-point statistics. POP spectra are derived from composite fields obtained by applying nonlinear transformations, involving also gradients, curls, and filtering functions, to a scalar field. This compresses the parity-odd trispectrum into a power spectrum. These new statistics offer several advantages: they are computationally fast to construct, estimating their covariance is less demanding compared to estimating that of the full parity-odd trispectrum, and they are simple to model theoretically. We measure the POP spectra on simulations of a scalar field with a specific parity-odd trispectrum shape. We compare these measurements to semi-analytic theoretical calculations and find agreement. We also explore extensions and generalizations of these parity-odd observables., Comment: 18 pages, 5 figures

This paper proposes an audio fingerprinting model with holographic reduced representation (HRR). The proposed method reduces the number of stored fingerprints, whereas conventional neural audio fingerprinting requires many fingerprints for each audio track to achieve high accuracy and time resolution. We utilize HRR to aggregate multiple fingerprints into a composite fingerprint via circular convolution and summation, resulting in fewer fingerprints with the same dimensional space as the original. Our search method efficiently finds a combined fingerprint in which a query fingerprint exists. Using HRR's inverse operation, it can recover the relative position within a combined fingerprint, retaining the original time resolution. Experiments show that our method can reduce the number of fingerprints with modest accuracy degradation while maintaining the time resolution, outperforming simple decimation and summation-based aggregation methods., Comment: accepted at Interspeech 2024

We propose UNIVERSE++, a universal speech enhancement method based on score-based diffusion and adversarial training. Specifically, we improve the existing UNIVERSE model that decouples clean speech feature extraction and diffusion. Our contributions are three-fold. First, we make several modifications to the network architecture, improving training stability and final performance. Second, we introduce an adversarial loss to promote learning high quality speech features. Third, we propose a low-rank adaptation scheme with a phoneme fidelity loss to improve content preservation in the enhanced speech. In the experiments, we train a universal enhancement model on a large scale dataset of speech degraded by noise, reverberation, and various distortions. The results on multiple public benchmark datasets demonstrate that UNIVERSE++ compares favorably to both discriminative and generative baselines for a wide range of qualitative and intelligibility metrics., Comment: 5 pages, 5 figures, accepted at Interspeech 2024

We extend our study of integrable structures in large $N_c$ QCD$_2$ to a broad class of theories called the generalized QCD, which are given by the Lagrangian $\mathcal{L}\propto {\rm tr}\,B\wedge F- {\rm tr}\,V(B)$ coupled to quarks in the fundamental representation. We recast the Bethe-Salpeter equation for the meson spectrum into a TQ-Baxter equation and determine a transfer matrix in a closed form for any given polynomial $V(B)$. Using this reformulation, we derive the asymptotic expansion of energy levels and wavefunctions. Examining the analytic structure of the spectrum as a function of the coefficients of $V(B)$, we determine the region of couplings where the theory admits a positive and discrete spectrum of mesons. Furthermore, we uncover a multi-sheeted structure with infinitely many multi-critical points, where several mesons become simultaneously massless. Lastly, we illustrate that this structure persists in the large-representation limit of the generalized QCD with the SU(2) gauge group., Comment: 62 pages; v2: Added Appendix E: "Non-critical spontaneous symmetry breaking of PT-symmetry", typos corrected

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a $1.8\sigma$ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied., Comment: 8 pages, 6 figures

We study correlation functions on the Coulomb branch of planar $\mathcal{N} = 4$ super-Yang- Mills theory (SYM), and their relationship with integrability, the operator product expansion (OPE), the sum rule, the large charge expansion, and holography. First, we compute one-point functions of arbitrary scalar operators at weak coupling and derive a compact spin-chain representation. We next study the two-point functions of chiral primaries at one loop and find that the radius of convergence of OPE in position space is infinite. We estimate the asymptotic growth of the OPE data based on this finding. Finally, we propose a concrete nonperturbative formula that connects the correlation functions on the Coulomb branch with the correlation functions with large charge insertions at the conformal point and provide a holographic interpretation based on a large D3-brane in AdS. The formula extends the known connection between the large charge sector and the Coulomb branch for rank-1 theories to the large $N$ limit., Comment: 51 pages

Heat and disorder are opponents of magnetism. This fact, expressed in Curie's law established more than a century ago, holds even in the highly non-equilibrium interaction of ultra-intense laser pulses with magnetic matter. In contradiction to this, here we demonstrate that optical excitation of a ferromagnet can abrogate the link between temperature and order and observe 100 femtosecond class laser pulses to drive a reduction in spin entropy, concomitant to an increase in spin polarization and magnetic moment persisting after relaxation back to local charge equilibrium. This both establishes disorder as an unexpected resource for magnetic control at ultrafast times and, by the provision of a purely electronic mechanism that does not involve reconfiguration of the crystal lattice, suggests a novel scheme for spin-based signal processing and information storage significantly faster than current methodology.

Imaging polarimetry plays an essential role in various fields since it imparts rich information that cannot be obtained through mere intensity and spectral measurements. To retrieve full Stokes parameters, at least four sensor pixels are required, each of which projects incident light to a different polarization state in the Stokes space. Conventional full-Stokes division-of-focal-plane (DoFP) cameras realize this function by integrating angled polarizers and retarders on top of image sensors. Due to the inevitable absorption at the polarizers, however, the maximum efficiency of these schemes is limited to 50% in theory. Instead of polarizers, three sets of lossless polarization beam splitters can be used to achieve higher-efficiency polarimetry, however, at the cost of reduced spatial resolution due to the need for six redundant sensor pixels. In this paper, we reveal, for the first time to our knowledge, that low-loss four-output polarization splitting (without filtering) is possible using a single-layer dielectric metasurface. Although these four states are not orthogonal to each other, our metasurface enables simultaneous sorting and focusing onto four sensor pixels with an efficiency exceeding 50\%, which is not feasible by a simple combination of space-optic components. The designed metasurface composed of silicon nanoposts is fabricated to experimentally demonstrate complete retrieval of full Stokes parameters at the near-infrared wavelength range from 1500 to 1600 nm with $-$2.28-dB efficiency. Finally, simple imaging polarimetry is demonstrated using a 3$\times$4 superpixel array.

In a multiply hydrogenated polymer of phenalenyl tessellation molecules (PTMs) where spatially overlapping zero modes appear, three parallelly spin-aligned electron spins per PTM are generated by the direct exchange interaction of the strongly correlated electron system, which we used to facilitate the molecular design of a two-dimensional (2D) S = 3/2 Heisenberg spin system on a honeycomb lattice. Density functional theory with the Wannierization method simulations of the electronic structure suggested that an array of nonbonding molecular orbitals (an array of zero modes) appears in the hydrogenated nanographene structure. Our evaluation of the onsite interaction strength indicated that each zero mode becomes half-filled with a spin-active electron by the electron correlation effect. The low-energy subspace of the obtained zero mode-tight-binding model implies the appearance of a 2D antiferromagnetic S = 3/2 Heisenberg system with the entangled quantum spin ground state.

The Lunar Gravitational-wave Antenna (LGWA) is a proposed array of next-generation inertial sensors to monitor the response of the Moon to gravitational waves (GWs). Given the size of the Moon and the expected noise produced by the lunar seismic background, the LGWA would be able to observe GWs from about 1 mHz to 1 Hz. This would make the LGWA the missing link between space-borne detectors like LISA with peak sensitivities around a few millihertz and proposed future terrestrial detectors like Einstein Telescope or Cosmic Explorer. In this article, we provide a first comprehensive analysis of the LGWA science case including its multi-messenger aspects and lunar science with LGWA data. We also describe the scientific analyses of the Moon required to plan the LGWA mission.

We report the H, C, and N isotopic compositions of microscale (0.2 to 2$\mu$m) organic matter in samples of asteroid Ryugu and the Orgueil CI carbonaceous chondrite. Three regolith particles of asteroid Ryugu, returned by the Hayabusa2 spacecraft, and several fragments of Orgueil were analyzed by NanoSIMS isotopic imaging. The isotopic distributions of the Ryugu samples from two different collection spots are closely similar to each other and to the Orgueil samples, strengthening the proposed Ryugu-CI chondrite connection. Most individual sub-$\mu$m organic grains have isotopic compositions within error of bulk values, but 2-8% of them are outliers exhibiting large isotopic enrichments or depletions in D, $^{15}$N, and/or $^{13}$C. The H, C and N isotopic compositions of the outliers are not correlated with each other: while some C-rich grains are both D- and $^{15}$N-enriched, many are enriched or depleted in one or the other system. This most likely points to a diversity in isotopic fractionation pathways and thus diversity in the local formation environments for the individual outlier grains. The observation of a relatively small population of isotopic outlier grains can be explained either by escape from nebular and/or parent body homogenization of carbonaceous precursor material or addition of later isotopic outlier grains. The strong chemical similarity of isotopically typical and isotopically outlying grains, as reflected by synchrotron x-ray absorption spectra, suggests a genetic connection and thus favors the former, homogenization scenario. However, the fact that even the least altered meteorites show the same pattern of a small population of outliers on top of a larger population of homogenized grains indicates that some or most of the homogenization occurred prior to accretion of the macromolecular organic grains into asteroidal parent bodies., Comment: Accepted for publication in Earth and Planetary Science Letters. 8 figures (plus 3 supplementary figs), two tables

We present detailed forecasts for the constraints on primordial magnetic fields (PMFs) that will be obtained with the LiteBIRD satellite. The constraints are driven by the effects of PMFs on the CMB anisotropies: the gravitational effects of magnetically-induced perturbations; the effects on the thermal and ionization history of the Universe; the Faraday rotation imprint on the CMB polarization; and the non-Gaussianities induced in polarization anisotropies. LiteBIRD represents a sensitive probe for PMFs and by exploiting all the physical effects, it will be able to improve the current limit coming from Planck. In particular, thanks to its accurate $B$-mode polarization measurement, LiteBIRD will improve the constraints on infrared configurations for the gravitational effect, giving $B_{\rm 1\,Mpc}^{n_{\rm B} =-2.9} < 0.8$ nG at 95% C.L., potentially opening the possibility to detect nanogauss fields with high significance. We also observe a significant improvement in the limits when marginalized over the spectral index, $B_{1\,{\rm Mpc}}^{\rm marg}< 2.2$ nG at 95% C.L. From the thermal history effect, which relies mainly on $E$-mode polarization data, we obtain a significant improvement for all PMF configurations, with the marginalized case, $\sqrt{\langle B^2\rangle}^{\rm marg}<0.50$ nG at 95% C.L. Faraday rotation constraints will take advantage of the wide frequency coverage of LiteBIRD and the high sensitivity in $B$ modes, improving the limits by orders of magnitude with respect to current results, $B_{1\,{\rm Mpc}}^{n_{\rm B} =-2.9} < 3.2$ nG at 95% C.L. Finally, non-Gaussianities of the $B$-mode polarization can probe PMFs at the level of 1 nG, again significantly improving the current bounds from Planck. Altogether our forecasts represent a broad collection of complementary probes, providing conservative limits on PMF characteristics that will be achieved with LiteBIRD., Comment: 51 pages, 24 figures, abstract shortened

In this paper, a novel approach is proposed for learning robot control in contact-rich tasks such as wiping, by developing Diffusion Contact Model (DCM). Previous methods of learning such tasks relied on impedance control with time-varying stiffness tuning by performing Bayesian optimization by trial-and-error with robots. The proposed approach aims to reduce the cost of robot operation by predicting the robot contact trajectories from the variable stiffness inputs and using neural models. However, contact dynamics are inherently highly nonlinear, and their simulation requires iterative computations such as convex optimization. Moreover, approximating such computations by using finite-layer neural models is difficult. To overcome these limitations, the proposed DCM used the denoising diffusion models that could simulate the complex dynamics via iterative computations of multi-step denoising, thus improving the prediction accuracy. Stiffness tuning experiments conducted in simulated and real environments showed that the DCM achieved comparable performance to a conventional robot-based optimization method while reducing the number of robot trials.

We give an explicit formula for the $p$-Frobenius number of triples associated with Diophantine equations $x^2+y^2=z^r$, that is, the largest positive integer that can only be represented in $p$ ways by combining the three integers of the solutions of Diophantine equations $x^2+y^2=z^r$. When $r=2$, the Frobenius number has already been given.

We show that crossing symmetry of S-matrices is modified in certain theories with non-invertible symmetries or anomalies. Focusing on integrable flows to gapped phases in two dimensions, we find that S-matrices derived previously from the bootstrap approach are incompatible with non-invertible symmetries along the flow. We present consistent alternatives, which however violate standard crossing symmetry and obey modified rules dictated by fusion categories. We extend these rules to theories with discrete anomalies., Comment: 7 pages plus supplemental material, v2: references added, typos corrected