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A novel method was developed to detect double-$\Lambda$ hypernuclear events in nuclear emulsions using machine learning techniques. The object detection model, the Mask R-CNN, was trained using images generated by Monte Carlo simulations, image processing, and image-style transformation based on generative adversarial networks. Despite being exclusively trained on $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ events, the model achieved a detection efficiency of 93.8$\%$ for $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ and 82.0$\%$ for $\prescript{5\ }{\Lambda\Lambda}{\rm{H}}$ events in the produced images. In addition, the model demonstrated its ability to detect the $\prescript{6\ }{\Lambda\Lambda}{\rm{He}}$ event named the Nagara event, which is the only uniquely identified double-$\Lambda$ hypernuclear event reported to date. It also exhibited a proper segmentation of the event topology. Furthermore, after analyzing 0.2$\%$ of the entire emulsion data from the J-PARC E07 experiment utilizing the developed approach, six new candidates for double-$\Lambda$ hypernuclear events were detected, suggesting that more than 2000 double-strangeness hypernuclear events were recorded in the entire dataset. This method is sufficiently effective for mining more latent double-$\Lambda$ hypernuclear events recorded in nuclear emulsion sheets by reducing the time required for manual visual inspection by a factor of five hundred.

We study if and when mod-2 anomalies can be canceled by the Green-Schwarz mechanism with the introduction of an antisymmetric tensor field $B_{\mu\nu}$. As explicit examples, we examine $SU(2)$ and more general $Sp(n)$ gauge theories in four and eight dimensions. We find that the mod-2 anomalies of 8d $\mathcal{N}=1$ $Sp(n)$ gauge theory can be canceled, as expected from it having a string theory realization, while the mod-2 Witten anomaly of 4d $SU(2)$ and $Sp(n)$ gauge theory cannot be canceled in this manner., Comment: 31 pages

This study investigates the formation of primordial black holes (PBHs) resulting from the collapse of adiabatic fluctuations with large amplitudes and non-Gaussianity. Ref. \cite{Uehara:2024yyp} showed that fluctuations with large amplitudes lead to the formation of type B PBHs, characterized by the existence of the bifurcating trapping horizons, distinct from the more common type A PBHs without a bifurcating trapping horizon. We focus on the local type non-Gaussianity characterized by the curvature perturbation $\zeta$ given by a function of a Gaussian random variable $\zeta_{\rm G}$ as $\beta\zeta=-\ln(1-\beta \zeta_{\rm G})$ with a parameter $\beta$. Then we examine how the non-Gaussianity influences the dynamics and the type of PBH formed, particularly focusing on type II fluctuations, where the areal radius varies non-monotonically with the coordinate radius. Our findings indicate that, for $\beta>-2$, the threshold for distinguishing between type A and type B PBHs decreases with increasing $\beta$ similarly to the threshold for black hole formation. Additionally, for large positive values of $\beta$, the threshold for type B PBHs approaches that for type II fluctuations. We also find that, for a sufficiently large negative value of $\beta\lesssim-4.0$, the threshold value is in the type II region of $\mu$, i.e., there are fluctuations of type II that do not form black holes. Lastly, we calculate the PBH mass for several values of $\beta$. Then we observe that the final mass monotonically increases with the initial amplitude within the parameter region of type A PBHs, which differs from previous analytical expectations., Comment: 20pages, 14figures

It is essential to examine the physical or chemical properties of molecular gas in starburst galaxies to reveal the underlying mechanisms characterizing starbursts. We used non-negative matrix factorization (NMF) to extract individual molecular or physical components involved in the star formation process in NGC\,253. We used images of 148 transitions from 44 different species of the ALMA large program ALCHEMI. Additionally, we included the continuum images at ALMA Bands 3 and 7 from the same dataset. For the five NMF components (NF1--5), we obtained that their distributions correspond to various basic phenomena related to star formation: i) low-density gas extended through the galactic central molecular zone (NF2), ii) shocks (NF3), iii) starburst regions (NF4), and iv) young star-forming regions (NF5). The other component (NF1) is related to excitation; three components obtained by NMF (NF3, 1, and 5) show a strong dependence upon the upper state energies of transitions, and represent low-, intermediate-, and high-excitation, respectively. We also compared our results using principal component analysis (PCA) previously applied to the same dataset. Molecular components extracted from NMF are similar to the ones obtained from PCA. However, NMF is better at extracting components associated with a single physical component, while a single component in PCA usually contains information on multiple physical components. This is especially true for features with weak intensities like emission from outflows. Our results suggest that NMF can be one of promising methods interpreting molecular line survey data, especially in the upcoming era of wide-band receivers., Comment: 22 pages, 19 figures, 2 tables. accepted for Publication of the Astronomical Society of Japan. Author's original version

We present 850 $\mu$m polarization observations of the IC 348 star-forming region in the Perseus molecular cloud as part of the B-fields In STar-forming Region Observation (BISTRO) survey. We study the magnetic properties of two cores (HH 211 MMS and IC 348 MMS) and a filamentary structure of IC 348. We find that the overall field tends to be more perpendicular than parallel to the filamentary structure of the region. The polarization fraction decreases with intensity, and we estimate the trend by power-law and the mean of the Rice distribution fittings. The power indices for the cores are much smaller than 1, indicative of possible grain growth to micron size in the cores. We also measure the magnetic field strengths of the two cores and the filamentary area separately by applying the Davis-Chandrasekhar-Fermi method and its alternative version for compressed medium. The estimated mass-to-flux ratios are 0.45-2.20 and 0.63-2.76 for HH 211 MMS and IC 348 MMS, respectively, while the ratios for the filament is 0.33-1.50. This result may suggest that the transition from subcritical to supercritical conditions occurs at the core scale ($\sim$ 0.05 pc) in the region. In addition, we study the energy balance of the cores and find that the relative strength of turbulence to the magnetic field tends to be stronger for IC 348 MMS than HH 211 MMS. The result could potentially explain the different configurations inside the two cores: a single protostellar system in HH 211 MMS and multiple protostars in IC 348 MMS., Comment: Accepted for publication in ApJ. 21 pages, 12 figures

We present a new approach to creating photorealistic and relightable head avatars from a phone scan with unknown illumination. The reconstructed avatars can be animated and relit in real time with the global illumination of diverse environments. Unlike existing approaches that estimate parametric reflectance parameters via inverse rendering, our approach directly models learnable radiance transfer that incorporates global light transport in an efficient manner for real-time rendering. However, learning such a complex light transport that can generalize across identities is non-trivial. A phone scan in a single environment lacks sufficient information to infer how the head would appear in general environments. To address this, we build a universal relightable avatar model represented by 3D Gaussians. We train on hundreds of high-quality multi-view human scans with controllable point lights. High-resolution geometric guidance further enhances the reconstruction accuracy and generalization. Once trained, we finetune the pretrained model on a phone scan using inverse rendering to obtain a personalized relightable avatar. Our experiments establish the efficacy of our design, outperforming existing approaches while retaining real-time rendering capability., Comment: SIGGRAPH Asia 2024. Website: https://junxuan-li.github.io/urgca-website/

Fashion aesthetic evaluation is the task of estimating how well the outfits worn by individuals in images suit them. In this work, we examine the zero-shot performance of GPT-4V on this task for the first time. We show that its predictions align fairly well with human judgments on our datasets, and also find that it struggles with ranking outfits in similar colors. The code is available at https://github.com/st-tech/gpt4v-fashion-aesthetic-evaluation.

Evidence for similar chemical characteristics around low- and high-mass protostars has been found: in particular, a variety of carbon-chain species and complex organic molecules (COMs) are formed around them. On the other hand, the chemical compositions around intermediate-mass (IM; $2 M_{\odot} < m_* <8 M_{\odot}$) protostars have not been studied with large samples. In particular, it is unclear the extent to which carbon-chain species are formed around them. We aim to obtain the chemical compositions, particularly focusing on carbon-chain species, towards a sample of IM protostars. We have conducted Q-band (31.5-50 GHz) line survey observations towards eleven mainly intermediate-mass protostars with the Yebes 40 m radio telescope. The target protostars were selected from a sub-sample of the source list of the SOFIA Massive (SOMA) Star Formation project. Nine carbon-chain species (HC$_3$N, HC$_5$N, C$_3$H, C$_4$H, $linear-$H$_2$CCC, $cyclic-$C$_3$H$_2$, CCS, C$_3$S, and CH$_3$CCH), three COMs (CH$_3$OH, CH$_3$CHO, and CH$_3$CN), H$_2$CCO, HNCO, and four simple sulfur (S)-bearing species ($^{13}$CS, C$^{34}$S, HCS$^+$, H$_2$CS) have been detected. The rotational temperatures of HC$_5$N are derived to be $\sim20-30$ K in three IM protostars and they are very similar compared to those around low- and high-mass protostars. These results indicate that carbon-chain molecules are formed in lukewarm ($\sim20-30$ K) gas around the IM protostars by the Warm Carbon-Chain Chemistry (WCCC) process. Carbon-chain formation occurs ubiquitously in the warm gas around protostars across a wide range of stellar masses. Carbon-chain molecules and COMs coexist around most of the target IM protostars, which is similar to the situation in low- and high-mass protostars. The chemical characteristics around protostars are common in the low-, intermediate- and high-mass regimes., Comment: Accepted for publication in the Astronomy and Astrophysics (A&A)

We study a flaring activity of the HSP Mrk421 that was characterized from radio to very-high-energy (VHE; E $>0.1$TeV) gamma rays with MAGIC, Fermi-LAT, Swift, XMM-Newton and several optical and radio telescopes. These observations included, for the first time for a gamma-ray flare of a blazar, simultaneous X-ray polarization measurements with IXPE. We find substantial variability in both X-rays and VHE gamma rays throughout the campaign, with the highest VHE flux above 0.2 TeV occurring during the IXPE observing window, and exceeding twice the flux of the Crab Nebula. However, the VHE and X-ray spectra are on average softer, and the correlation between these two bands weaker that those reported in previous flares of Mrk421. IXPE reveals an X-ray polarization degree significantly higher than that at radio and optical frequencies. The X-ray polarization angle varies by $\sim$100$^\circ$ on timescales of days, and the polarization degree changes by more than a factor 4. The highest X-ray polarization degree reaches 26%, around which a X-ray counter-clockwise hysteresis loop is measured with XMM-Newton. It suggests that the X-ray emission comes from particles close to the high-energy cutoff, hence possibly probing an extreme case of the Turbulent Extreme Multi-Zone model. We model the broadband emission with a simplified stratified jet model throughout the flare. The polarization measurements imply an electron distribution in the X-ray emitting region with a very high minimum Lorentz factor, which is expected in electron-ion plasma, as well as a variation of the emitting region size up to a factor of three during the flaring activity. We find no correlation between the fluxes and the evolution of the model parameters, which indicates a stochastic nature of the underlying physical mechanism. Such behaviour would be expected in a highly turbulent electron-ion plasma crossing a shock front., Comment: Submitted to Astronomy and Astrophysics. Corresponding authors: Axel Arbet-Engels, Lea Heckmann, David Paneque

OT 081 is a well-known, luminous blazar that is remarkably variable in many energy bands. We present the first broadband study of the source which includes very-high-energy (VHE, $E>$100\,GeV) $\gamma$-ray data taken by the MAGIC and H.E.S.S. imaging Cherenkov telescopes. The discovery of VHE $\gamma$-ray emission happened during a high state of $\gamma$-ray activity in July 2016, observed by many instruments from radio to VHE $\gamma$-rays. We identify four states of activity of the source, one of which includes VHE $\gamma$-ray emission. Variability in the VHE domain is found on daily timescales. The intrinsic VHE spectrum can be described by a power-law with index $3.27\pm0.44_{\rm stat}\pm0.15_{\rm sys}$ (MAGIC) and $3.39\pm0.58_{\rm stat}\pm0.64_{\rm sys}$ (H.E.S.S.) in the energy range of 55--300\,GeV and 120--500\,GeV, respectively. The broadband emission cannot be sucessfully reproduced by a simple one-zone synchrotron self-Compton model. Instead, an additional external Compton component is required. We test a lepto-hadronic model that reproduces the dataset well and a proton-synchrotron dominated model that requires an extreme proton luminosity. Emission models that are able to successfully represent the data place the emitting region well outside of the Broad Line Region (BLR) to a location at which the radiative environment is dominated by the infrared thermal radiation field of the dusty torus. In the scenario described by this flaring activity, the source appears to be an FSRQ, in contrast with past categorizations. This suggests that the source can be considered to be a transitional blazar, intermediate between BL~Lac and FSRQ objects., Comment: Accepted on MNRAS Corresponding authors: M. Manganaro, J. Becerra Gonz\'alez, M. Seglar-Arroyo, D. A. Sanchez

In the present-day universe, the most massive galaxies are ellipticals located in the cores of galaxy clusters, harboring the heaviest super-massive black holes (SMBHs). However the mechanisms that drive the early growth phase and subsequent transformation of these morphology and kinematics of galaxies remain elusive. Here we report (sub)kiloparsec scale observations of stars, gas, and dust in ADF22.A1, a bright dusty starburst galaxy at z=3.1, hosting a heavily obscured active galactic nucleus and residing in a proto-cluster core. ADF22.A1 is a giant spiral galaxy with the kinematics of a rotating disk with rotation velocity Vrot=530+/-10km/s and diameter larger than 30 kpc. The high specific stellar angular momentum of this system, j*=3400+/-600 kpc km/s, requires a mechanism to effectively spin-up ADF22.A1, indicating the importance of accretion from the cosmic web to supply both gas and angular momentum to galaxies in their early gas-rich starburst phase. In its inner region, gas flows along dust lanes in a bar connected with the bright dusty core and the estimated mass ratio of a bulge to SMBH matches the local relation, suggesting that bars are a key mechanism to shape the early co-evolution of these components. Comparison with cosmological simulations shows that ADF22.A1 will likely evolve into a massive elliptical at the present day, experiencing a significant reduction in angular momentum associated with subsequent galaxy mergers., Comment: 13 pages, 12 figures. Submitted

Powerful, galactic outflows driven by Active Galactic Nuclei (AGNs) are commonly considered as a main mechanism to regulate star formation in massive galaxies. Ultra- and hyper-luminous IR galaxies (U/HyLIRGs) are thought to represent a transition phase of galaxies from a rapidly growing period to a quiescent status as gas swept out by outflows, providing a laboratory to investigate outflows and their feedback effects on the hosts. In this paper we report recent Gemini and ALMA observations of a HyLIRG, J1126 at $z=0.46842$, which has been identified with a puzzling co-existence of a fast ionized outflow ($>2000$ km s$^{-1}$) and an intense starburst (star formation rate of 800 $M_{\odot}$ yr$^{-1}$). The Gemini observation shows the fast ionized outflow is extended to several kpc with a mass-loss rate of 180 $M_{\odot}$ yr$^{-1}$. A massive molecular outflow with a high mass-loss rate (2500 $M_{\odot}$ yr$^{-1}$) is revealed by ALMA. The multi-phase outflows show large factors of momentum boost and loading of kinetic power, indicating a driving by thermal pressure of a nuclear hot wind and/or radiation pressure of a highly obscured AGN. In addition to ejection of kinetic energy, it is also found that the powerful outflow can induce an ionizing shock in the galaxy disk and enhance the excitation and dissociation of molecular gas. The powerful outflow probably results in an instantaneous negative feedback and shows potential to regulate the host growth in a long term., Comment: 35 pages, 26 figures, accepted to be published in ApJ

We present Agent-to-Sim (ATS), a framework for learning interactive behavior models of 3D agents from casual longitudinal video collections. Different from prior works that rely on marker-based tracking and multiview cameras, ATS learns natural behaviors of animal and human agents non-invasively through video observations recorded over a long time-span (e.g., a month) in a single environment. Modeling 3D behavior of an agent requires persistent 3D tracking (e.g., knowing which point corresponds to which) over a long time period. To obtain such data, we develop a coarse-to-fine registration method that tracks the agent and the camera over time through a canonical 3D space, resulting in a complete and persistent spacetime 4D representation. We then train a generative model of agent behaviors using paired data of perception and motion of an agent queried from the 4D reconstruction. ATS enables real-to-sim transfer from video recordings of an agent to an interactive behavior simulator. We demonstrate results on pets (e.g., cat, dog, bunny) and human given monocular RGBD videos captured by a smartphone., Comment: Project page: https://gengshan-y.github.io/agent2sim-www/

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gamma-ray sources and precise measurements of the already discovered ones. To achieve these goals, both hardware and data analysis must employ cutting-edge techniques. This also applies to the LST-1, the first IACT built for the CTAO, which is currently taking data on the Canary island of La Palma. This paper introduces a new event reconstruction technique for IACT data, aiming to improve the image reconstruction quality and the discrimination between the signal and the background from misidentified hadrons and electrons. The technique models the development of the extensive air shower signal, recorded as a waveform per pixel, seen by CTAO telescopes' cameras. Model parameters are subsequently passed to random forest regressors and classifiers to extract information on the primary particle. The new reconstruction was applied to simulated data and to data from observations of the Crab Nebula performed by the LST-1. The event reconstruction method presented here shows promising performance improvements. The angular and energy resolution, and the sensitivity, are improved by 10 to 20% over most of the energy range. At low energy, improvements reach up to 22%, 47%, and 50%, respectively. A future extension of the method to stereoscopic analysis for telescope arrays will be the next important step., Comment: Accepted in A&A

Some datasets with the described content and order of occurrence of sounds have been released for conversion between environmental sound and text. However, there are very few texts that include information on the impressions humans feel, such as "sharp" and "gorgeous," when they hear environmental sounds. In this study, we constructed a dataset with impression captions for environmental sounds that describe the impressions humans have when hearing these sounds. We used ChatGPT to generate impression captions and selected the most appropriate captions for sound by humans. Our dataset consists of 3,600 impression captions for environmental sounds. To evaluate the appropriateness of impression captions for environmental sounds, we conducted subjective and objective evaluations. From our evaluation results, we indicate that appropriate impression captions for environmental sounds can be generated.

Recent research on explainable recommendation generally frames the task as a standard text generation problem, and evaluates models simply based on the textual similarity between the predicted and ground-truth explanations. However, this approach fails to consider one crucial aspect of the systems: whether their outputs accurately reflect the users' (post-purchase) sentiments, i.e., whether and why they would like and/or dislike the recommended items. To shed light on this issue, we introduce new datasets and evaluation methods that focus on the users' sentiments. Specifically, we construct the datasets by explicitly extracting users' positive and negative opinions from their post-purchase reviews using an LLM, and propose to evaluate systems based on whether the generated explanations 1) align well with the users' sentiments, and 2) accurately identify both positive and negative opinions of users on the target items. We benchmark several recent models on our datasets and demonstrate that achieving strong performance on existing metrics does not ensure that the generated explanations align well with the users' sentiments. Lastly, we find that existing models can provide more sentiment-aware explanations when the users' (predicted) ratings for the target items are directly fed into the models as input. We will release our code and datasets upon acceptance.

We investigate the stability of a vortex ring in a miscible two-component Bose-Einstein condensate confined in a harmonic potential, where the vortex cores in the two components are initially overlapped. Solving the Gross-Pitaevskii equation numerically, we find that the overlapped vortex rings in the two components are dynamically unstable against separation and that they can form linked vortex rings, resulting in a three-dimensional skyrmion. The parameter range for spontaneous skyrmion generation is determined by the Bogoliubov analysis, Comment: 8 pages, 5 figures, 3 movies

The local modes of trapped ions can be used to construct an analog quantum simulator and a digital quantum computer. However, the control of the phonon hopping remains diffi cult because it proceeds among all the local modes through the Coulomb coupling. We propose a method to cancel the phonon hopping among a given set of local modes by applying a sequence of phase shift gates implemented through the modulation of the trap potential. We analyze the error scaling in the algorithm to treat three or more modes and show that the error can be suppressed by repeating the pulse sequence. The duration of the phase shift gate in the present method can be as short as a few microseconds, which is an order of magnitude faster than the laser-based method. This short duration of the phase shift gate facilitates the suppression of the gate error. The present method can be applied to the simulation of bosonic systems as well as to the continuous variable encoding of quantum computing using trapped ions., Comment: 11 pages, 7 figures

Acceleration of positive muons from thermal energy to $100~$keV has been demonstrated. Thermal muons were generated by resonant multi-photon ionization of muonium atoms emitted from a sheet of laser-ablated aerogel. The thermal muons were first electrostatically accelerated to $5.7~$keV, followed by further acceleration to 100 keV using a radio-frequency quadrupole. The transverse normalized emittance of the accelerated muons in the horizontal and vertical planes were $0.85 \pm 0.25 ~\rm{(stat.)}~^{+0.22}_{-0.13} ~\rm{(syst.)}~\pi~$mm$\cdot$mrad and $0.32\pm 0.03~\rm{(stat.)} ^{+0.05}_{-0.02} ~\rm{(syst.)}~\pi~$mm$\cdot$mrad, respectively. The measured emittance values demonstrated phase space reduction by a factor of $2.0\times 10^2$ (horizontal) and $4.1\times 10^2$ (vertical) allowing good acceleration efficiency. These results pave the way to realize the first-ever muon accelerator for a variety of applications in particle physics, material science, and other fields.

Loss spikes, a phenomenon in which the loss value diverges suddenly, is a fundamental issue in the pre-training of large language models. This paper supposes that the non-uniformity of the norm of the parameters is one of the causes of loss spikes. Here, in training of neural networks, the scale of the gradients is required to be kept constant throughout the layers to avoid the vanishing and exploding gradients problem. However, to meet these requirements in the Transformer model, the norm of the model parameters must be non-uniform, and thus, parameters whose norm is smaller are more sensitive to the parameter update. To address this issue, we propose a novel technique, weight scaling as reparameterization (WeSaR). WeSaR introduces a gate parameter per parameter matrix and adjusts it to the value satisfying the requirements. Because of the gate parameter, WeSaR sets the norm of the original parameters uniformly, which results in stable training. Experimental results with the Transformer decoders consisting of 130 million, 1.3 billion, and 13 billion parameters showed that WeSaR stabilizes and accelerates training and that it outperformed compared methods including popular initialization methods., Comment: EMNLP2024 accepted

Building on Beilinson's work, ``constructible sheaves are holonomic,'' we introduce the notion of holonomicity for \'etale sheaves, without assuming a priori constructibility. Over a perfect base field, we establish the converse of Beilinson's result, showing that holonomic sheaves are indeed constructible. This can be seen as an \'etale analogue of Kashiwara's theorem on holonomic ${\mathcal D}_X$-modules., Comment: 12 pages

The nature of the magnetic ground state of highly frustrated systems remained puzzling to this day. Here, we have performed multifrequency electron spin resonance (ESR) measurements on a putative quantum spin liquid compound $\kappa$-(BEDT-TTF)$_2$Ag$_2$(CN)$_3$, which is a rare example of $S = 1/2$ spins on a triangular lattice. At high temperatures, the spin susceptibility exhibits a weak temperature dependence which can be described by the Heisenberg model with an antiferromagnetic exchange interaction of strength $J/k_B \approx 175$ K. At low temperatures, however, the rapid drop of the static spin susceptibility, together with monotonic decrease of the ESR linewidth indicates that strong singlet correlations develop below a pairing energy scale $T^*$ accompanied by a spin gap. On the other hand, a weak Curie-like spin susceptibility and the angular dependence of the linewidth suggest additional contribution from impurity spins. We propose the gradual formation of spin singlets with an inhomogeneous spin gap at low temperatures.

Utterances by L2 speakers can be unintelligible due to mispronunciation and improper prosody. In computer-aided language learning systems, textual feedback is often provided using a speech recognition engine. However, an ideal form of feedback for L2 speakers should be so fine-grained that it enables them to detect and diagnose unintelligible parts of L2 speakers' utterances. Inspired by language teachers who correct students' pronunciation through a voice-to-voice process, this pilot study utilizes a unique semi-parallel dataset composed of non-native speakers' (L2) reading aloud, shadowing of native speakers (L1) and their script-shadowing utterances. We explore the technical possibility of replicating the process of an L1 speaker's shadowing L2 speech using Voice Conversion techniques, to create a virtual shadower system. Experimental results demonstrate the feasibility of the VC system in simulating L1's shadowing behavior. The output of the virtual shadower system shows a reasonable similarity to the real L1 shadowing utterances in both linguistic and acoustic aspects., Comment: Accepted by APSIPA ASC 2024. arXiv admin note: text overlap with arXiv:2409.11742

We study superconductivity in Ammann-Beenker quasicrystals under magnetic field. By assuming an intrinsic $s$-wave pairing interaction and solving for mean-field equations self-consistently, we find gapless superconductivity in the quasicrystals at and near half filling. We show that gapless superconductivity originates in broken translational symmetry and confined states unique to the quasicrystals. When Rashba spin-orbit coupling is present, the quasicrystalline gapless superconductor can be topologically nontrivial and characterized by a nonzero pseudospectrum invariant given by a spectral localizer. The gapless topological superconducting phase exhibits edge states with near-zero energy. These findings suggest that quasicrystals can be a unique platform for realizing gapless superconductivity with nontrivial topology., Comment: 6 pages, 3 figures, and Supplemental Material (3 pages, 5 figures)

The electron antinuetrino flux limits are presented for the brightest gamma-ray burst (GRB) of all time, GRB221009A, over a range of 1.8-200 MeV using the Kamioka Liquid Scintillator Anti Neutrino Detector (KamLAND). Using a variety of time windows to search for electron antineutrinos coincident with the GRB, we set an upper limit on the flux under the assumption of various neutrino source spectra. No excess was observed in any time windows ranging from seconds to days around the event trigger time. The limits are compared to the results presented by IceCube., Comment: 8 pages, 3 figures, 1 table

In this study, we consider the problem of predicting task success for open-vocabulary manipulation by a manipulator, based on instruction sentences and egocentric images before and after manipulation. Conventional approaches, including multimodal large language models (MLLMs), often fail to appropriately understand detailed characteristics of objects and/or subtle changes in the position of objects. We propose Contrastive $\lambda$-Repformer, which predicts task success for table-top manipulation tasks by aligning images with instruction sentences. Our method integrates the following three key types of features into a multi-level aligned representation: features that preserve local image information; features aligned with natural language; and features structured through natural language. This allows the model to focus on important changes by looking at the differences in the representation between two images. We evaluate Contrastive $\lambda$-Repformer on a dataset based on a large-scale standard dataset, the RT-1 dataset, and on a physical robot platform. The results show that our approach outperformed existing approaches including MLLMs. Our best model achieved an improvement of 8.66 points in accuracy compared to the representative MLLM-based model., Comment: Accepted for presentation at CoRL2024

Instruments for gamma-ray astronomy at Very High Energies ($E>100\,{\rm GeV}$) have traditionally derived their scientific results through proprietary data and software. Data standardisation has become a prominent issue in this field both as a requirement for the dissemination of data from the next generation of gamma-ray observatories and as an effective solution to realise public data legacies of current-generation instruments. Specifications for a standardised gamma-ray data format have been proposed as a community effort and have already been successfully adopted by several instruments. We present the first production of standardised data from the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) telescopes. We converted $166\,{\rm h}$ of observations from different sources and validated their analysis with the open-source software Gammapy. We consider six data sets representing different scientific and technical analysis cases and compare the results obtained analysing the standardised data with open-source software against those produced with the MAGIC proprietary data and software. Aiming at a systematic production of MAGIC data in this standardised format, we also present the implementation of a database-driven pipeline automatically performing the MAGIC data reduction from the calibrated down to the standardised data level. In all the cases selected for the validation, we obtain results compatible with the MAGIC proprietary software, both for the manual and for the automatic data productions. Part of the validation data set is also made publicly available, thus representing the first large public release of MAGIC data. This effort and this first data release represent a technical milestone toward the realisation of a public MAGIC data legacy., Comment: Accepted for publication in the Journal of High Energy Astrophysics

We investigate static, axially symmetric spacetimes without naked singularities that are constructed by patching Weyl class spacetimes with the flat spacetimes. Once the exterior geometry is specified, the junction conditions determine the shape of a thin shell, which is the boundary between the two patched spacetimes, and the distribution of the energy and pressure on this shell, leaving a parameter representing the shell size free. We examine the cases where the exterior of the shell is given by Curzon--Chazy or Zipoy--Voorhees spacetimes. For each case, we find a lower bound on the shell size. Additionally, we find that the weak and null energy conditions are satisfied for any shell size, while the dominant energy condition is satisfied for sufficiently large shells. These results provide concrete examples of non-singular spacetimes with non-spherically symmetric exteriors that respect the energy conditions., Comment: 15 pages, 10 figures

The phase noise of low-noise oscillators is conventionally measured by the cross-spectrum method (CSM), which has a complicated setup. We developed an alternative method called zero-crossing analysis with a double recorder setup (ZCA-DRS) that has much simpler configuration, which we previously demonstrated to measure phase noise in the audible frequency range. In this study we conducted experiments using ZCA-DRS to measure phase noise in the radiofrequency range. A temperature-compensated crystal oscillator was used to generate a periodic signal at 27 MHz. The results demonstrated that the obtained single-side band spectrum was almost the same as that obtained by CSM. The measurement sensitivity was limited by the jitter of the internal clock and noise of the analog-to-digital converter. Thus, ZCA-DRS can be used as an alternative to CSM for phase noise measurement in the radiofrequency range., Comment: 8 pages, 10 figures

The precise determination of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements is very important, because it could be a clue to new physics beyond Standard Theory. This is particular true of $V_{ud}$, because it is the main contribution to the unitary condition of the CKM matrix elements. The level of accuracy for the test of the unitarity involving the element $V_{ud}$ is now of the order of $10^{-4}$. Because the precise data for $V_{ud}$ is usually extracted from super-allowed nuclear $\beta$ decay, it is quite significant to investigate the breaking of SU(3) flavor symmetry on the weak vector coupling constant in nuclear matter. The purpose of this paper is to investigate how the isoscalar scalar ($\sigma$) and the isovector scalar ($\delta$ or $a_0$) mean-fields affect the weak vector and axial-vector coupling constants for semileptonic baryon (neutron, $\Lambda$ or $\Xi^-$) decay in asymmetric nuclear matter. To do so, we use the quark-meson coupling (QMC) model, where nuclear matter consists of nucleons including quark degrees of freedom bound by the self-consistent exchange of scalar and vector mesons. We pay careful attention to the center of mass correction to the quark currents in matter. We then find that, for neutron $\beta$ decay in asymmetric nuclear matter, the defect of the vector coupling constant due to the $\delta$ field can be of the order of $10^{-4}$ at the nuclear saturation density, which is the same amount as the level of the current uncertainty in the measurements. It is also interesting that, in neutron-rich matter, there exists a certain low density at which isospin symmetry is restored, that is, the $u$-$d$ quark mass difference vanishes. We conclude that the effect of the isoscalar scalar and the isovector scalar fields should be considered in baryon semileptonic decays in nuclei., Comment: 49 pages, 13 figures, 6 tables, Matching to the version accepted for publication as a Regular Article in Physical Review D

We introduce a pro-cdh topology on formal schemes and prove that the $\infty$-topos of pro-cdh sheaves of spaces has an optimal bound of homotopy dimension. This remedies a defect for a pro-cdh topology on schemes introduced in [KS23]. As an application, we give a topos-theoretic interpretation of Weibel's vanishing of negative K-theory and motivic cohomology of Elmanto and Morrow.

This paper presents a parameter scan technique for BSM signal models based on normalizing flow. Normalizing flow is a type of deep learning model that transforms a simple probability distribution into a complex probability distribution as an invertible function. By learning an invertible transformation between a complex multidimensional distribution, such as experimental data observed in collider experiments, and a multidimensional normal distribution, the normalizing flow model gains the ability to sample (or generate) pseudo experimental data from random numbers and to evaluate a log-likelihood value from multidimensional observed events. The normalizing flow model can also be extended to take multidimensional conditional variables as arguments. Thus, the normalizing flow model can be used as a generator and evaluator of pseudo experimental data conditioned by the BSM model parameters. The log-likelihood value, the output of the normalizing flow model, is a function of the conditional variables. Therefore, the model can quickly calculate gradients of the log-likelihood to the conditional variables. Following this property, it is expected that the most likely set of conditional variables that reproduce the experimental data, i.e. the optimal set of parameters for the BSM model, can be efficiently searched. This paper demonstrates this on a simple dataset and discusses its limitations and future extensions., Comment: Presented at International Symposium on Grids and Clouds (ISGC2024)

The increasing demand for high-quality 3D assets across various industries necessitates efficient and automated 3D content creation. Despite recent advancements in 3D generative models, existing methods still face challenges with optimization speed, geometric fidelity, and the lack of assets for physically based rendering (PBR). In this paper, we introduce 3DTopia-XL, a scalable native 3D generative model designed to overcome these limitations. 3DTopia-XL leverages a novel primitive-based 3D representation, PrimX, which encodes detailed shape, albedo, and material field into a compact tensorial format, facilitating the modeling of high-resolution geometry with PBR assets. On top of the novel representation, we propose a generative framework based on Diffusion Transformer (DiT), which comprises 1) Primitive Patch Compression, 2) and Latent Primitive Diffusion. 3DTopia-XL learns to generate high-quality 3D assets from textual or visual inputs. We conduct extensive qualitative and quantitative experiments to demonstrate that 3DTopia-XL significantly outperforms existing methods in generating high-quality 3D assets with fine-grained textures and materials, efficiently bridging the quality gap between generative models and real-world applications., Comment: Code https://github.com/3DTopia/3DTopia-XL Project Page https://3dtopia.github.io/3DTopia-XL/

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

Radiance fields are powerful and, hence, popular models for representing the appearance of complex scenes. Yet, constructing them based on image observations gives rise to ambiguities and uncertainties. We propose a versatile approach for learning Gaussian radiance fields with explicit and fine-grained uncertainty estimates that impose only little additional cost compared to uncertainty-agnostic training. Our key observation is that uncertainties can be modeled as a low-dimensional manifold in the space of radiance field parameters that is highly amenable to Monte Carlo sampling. Importantly, our uncertainties are differentiable and, thus, allow for gradient-based optimization of subsequent captures that optimally reduce ambiguities. We demonstrate state-of-the-art performance on next-best-view planning tasks, including high-dimensional illumination planning for optimal radiance field relighting quality., Comment: Siggraph Asia 2024 conference

Spin amplification is the process that ideally increases the number of excited spins if there was one excited spin to begin with. Using optimal control techniques to find classical drive pulse shapes, we show that spin amplification can be done in the previously unexplored regime with amplification times comparable to the timescale set by the interaction terms in the Hamiltonian. This is an order of magnitude faster than the previous protocols and makes spin amplification possible even with significant decoherence and inhomogeneity in the spin system. The initial spin excitation can be delocalized over the entire ensemble, which is a more typical situation when a photon is collectively absorbed by the spins. We focus on the superconducting persistent-current artificial atoms as spins, but this approach can be applied to other kinds of strongly-interacting spins, including the Rydberg atoms., Comment: 14 pages, 10 figures

Evaluating speech intelligibility is a critical task in computer-aided language learning systems. Traditional methods often rely on word error rates (WER) provided by automatic speech recognition (ASR) as intelligibility scores. However, this approach has significant limitations due to notable differences between human speech recognition (HSR) and ASR. A promising alternative is to involve a native (L1) speaker in shadowing what nonnative (L2) speakers say. Breakdowns or mispronunciations in the L1 speaker's shadowing utterance can serve as indicators for assessing L2 speech intelligibility. In this study, we propose a speech generation system that simulates the L1 shadowing process using voice conversion (VC) techniques and latent speech representations. Our experimental results demonstrate that this method effectively replicates the L1 shadowing process, offering an innovative tool to evaluate L2 speech intelligibility. Notably, systems that utilize self-supervised speech representations (S3R) show a higher degree of similarity to real L1 shadowing utterances in both linguistic accuracy and naturalness., Comment: Submitted to ICASSP2025 Demo available: https://secondtonumb.github.io/publication_demo/ICASSP_2025/index.html

Matching users with mutual preferences is a critical aspect of services driven by reciprocal recommendations, such as job search. To produce recommendations in such scenarios, one can predict match probabilities and construct rankings based on these predictions. However, this direct match prediction approach often underperforms due to the extreme sparsity of match labels. Therefore, most existing methods predict preferences separately for each direction (e.g., job seeker to employer and employer to job seeker) and then aggregate the predictions to generate overall matching scores and produce recommendations. However, this typical approach often leads to practical issues, such as biased error propagation between the two models. This paper introduces and demonstrates a novel and practical solution to improve reciprocal recommendations in production by leveraging pseudo-match scores. Specifically, our approach generates dense and more directly relevant pseudo-match scores by combining the true match labels, which are accurate but sparse, with relatively inaccurate but dense match predictions. We then train a meta-model to output the final match predictions by minimizing the prediction loss against the pseudo-match scores. Our method can be seen as a best-of-both (BoB) approach, as it combines the high-level ideas of both direct match prediction and the two separate models approach. It also allows for user-specific weights to construct personalized pseudo-match scores, achieving even better matching performance through appropriate tuning of the weights. Offline experiments on real-world job search data demonstrate the superior performance of our BoB method, particularly with personalized pseudo-match scores, compared to existing approaches in terms of finding potential matches.

In this paper, we provide the semi-analytical solution of the temperature and flow fields of a fluid confined in a narrow space between two parallel plates. The temperature increase is triggered by photothermal effects of fluids and/or boundaries due to the absorption of a focused Gaussian beam irradiated perpendicular to the fluid film, and then the temperature variation induces the flow fields through a buoyancy force and/or thermo-osmotic slip. The semi-analytical solution to this optothermal fluidic system is validated by comparing with the results of numerical simulation, and is applied to typical optothermal fluidic problems. In particular, the optothermal trap of nanoparticles observed in our previous experiment [T. Tsuji, et al., Electrophoresis, 42, 2401 (2021)] is investigated in terms of thermophoretic force and flow drag that are obtained semi-analytically. The semi-analytical solution can be shared through open-source codes that are available to researchers without the background of fluid mechanics., Comment: 19 figures

We present our system (denoted as T05) for the VoiceMOS Challenge (VMC) 2024. Our system was designed for the VMC 2024 Track 1, which focused on the accurate prediction of naturalness mean opinion score (MOS) for high-quality synthetic speech. In addition to a pretrained self-supervised learning (SSL)-based speech feature extractor, our system incorporates a pretrained image feature extractor to capture the difference of synthetic speech observed in speech spectrograms. We first separately train two MOS predictors that use either of an SSL-based or spectrogram-based feature. Then, we fine-tune the two predictors for better MOS prediction using the fusion of two extracted features. In the VMC 2024 Track 1, our T05 system achieved first place in 7 out of 16 evaluation metrics and second place in the remaining 9 metrics, with a significant difference compared to those ranked third and below. We also report the results of our ablation study to investigate essential factors of our system., Comment: Accepted by IEEE SLT 2024. Our MOS prediction system (UTMOSv2) is available in https://github.com/sarulab-speech/UTMOSv2

Tactile perception is vital, especially when distinguishing visually similar objects. We propose an approach to incorporate tactile data into a Vision-Language Model (VLM) for visuo-tactile zero-shot object recognition. Our approach leverages the zero-shot capability of VLMs to infer tactile properties from the names of tactilely similar objects. The proposed method translates tactile data into a textual description solely by annotating object names for each tactile sequence during training, making it adaptable to various contexts with low training costs. The proposed method was evaluated on the FoodReplica and Cube datasets, demonstrating its effectiveness in recognizing objects that are difficult to distinguish by vision alone., Comment: 9 pages, 9 figures, accepted to IROS2024, project page: https://omron-sinicx.github.io/visuo-tactile-recognition/

Given a graph $G$ and two spanning trees $T$ and $T'$ in $G$, Spanning Tree Reconfiguration asks whether there is a step-by-step transformation from $T$ to $T'$ such that all intermediates are also spanning trees of $G$, by exchanging an edge in $T$ with an edge outside $T$ at a single step. This problem is naturally related to matroid theory, which shows that there always exists such a transformation for any pair of $T$ and $T'$. Motivated by this example, we study the problem of transforming a sequence of spanning trees into another sequence of spanning trees. We formulate this problem in the language of matroid theory: Given two sequences of bases of matroids, the goal is to decide whether there is a transformation between these sequences. We design a polynomial-time algorithm for this problem, even if the matroids are given as basis oracles. To complement this algorithmic result, we show that the problem of finding a shortest transformation is NP-hard to approximate within a factor of $c \log n$ for some constant $c > 0$, where $n$ is the total size of the ground sets of the input matroids., Comment: 16 pages, 5 figures

We propose GauFace, a novel Gaussian Splatting representation, tailored for efficient animation and rendering of physically-based facial assets. Leveraging strong geometric priors and constrained optimization, GauFace ensures a neat and structured Gaussian representation, delivering high fidelity and real-time facial interaction of 30fps@1440p on a Snapdragon 8 Gen 2 mobile platform. Then, we introduce TransGS, a diffusion transformer that instantly translates physically-based facial assets into the corresponding GauFace representations. Specifically, we adopt a patch-based pipeline to handle the vast number of Gaussians effectively. We also introduce a novel pixel-aligned sampling scheme with UV positional encoding to ensure the throughput and rendering quality of GauFace assets generated by our TransGS. Once trained, TransGS can instantly translate facial assets with lighting conditions to GauFace representation, With the rich conditioning modalities, it also enables editing and animation capabilities reminiscent of traditional CG pipelines. We conduct extensive evaluations and user studies, compared to traditional offline and online renderers, as well as recent neural rendering methods, which demonstrate the superior performance of our approach for facial asset rendering. We also showcase diverse immersive applications of facial assets using our TransGS approach and GauFace representation, across various platforms like PCs, phones and even VR headsets., Comment: Project Page: https://dafei-qin.github.io/TransGS.github.io/

In this note, after recalling a proof of the Macdonald identities for untwisted affine root systems, we derive the Macdonald identities for twisted affine root systems., Comment: Typos corrected

We explore cross-dialect text-to-speech (CD-TTS), a task to synthesize learned speakers' voices in non-native dialects, especially in pitch-accent languages. CD-TTS is important for developing voice agents that naturally communicate with people across regions. We present a novel TTS model comprising three sub-modules to perform competitively at this task. We first train a backbone TTS model to synthesize dialect speech from a text conditioned on phoneme-level accent latent variables (ALVs) extracted from speech by a reference encoder. Then, we train an ALV predictor to predict ALVs tailored to a target dialect from input text leveraging our novel multi-dialect phoneme-level BERT. We conduct multi-dialect TTS experiments and evaluate the effectiveness of our model by comparing it with a baseline derived from conventional dialect TTS methods. The results show that our model improves the dialectal naturalness of synthetic speech in CD-TTS., Comment: Accepted by IEEE SLT 2024