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This paper focuses on remainder estimates of the magnetic $L^p$-Hardy inequalities for $1

Point tracking is a challenging task in computer vision, aiming to establish point-wise correspondence across long video sequences. Recent advancements have primarily focused on temporal modeling techniques to improve local feature similarity, often overlooking the valuable semantic consistency inherent in tracked points. In this paper, we introduce a novel approach leveraging language embeddings to enhance the coherence of frame-wise visual features related to the same object. Our proposed method, termed autogenic language embedding for visual feature enhancement, strengthens point correspondence in long-term sequences. Unlike existing visual-language schemes, our approach learns text embeddings from visual features through a dedicated mapping network, enabling seamless adaptation to various tracking tasks without explicit text annotations. Additionally, we introduce a consistency decoder that efficiently integrates text tokens into visual features with minimal computational overhead. Through enhanced visual consistency, our approach significantly improves tracking trajectories in lengthy videos with substantial appearance variations. Extensive experiments on widely-used tracking benchmarks demonstrate the superior performance of our method, showcasing notable enhancements compared to trackers relying solely on visual cues., Comment: accepted by ACM MM 2024

The digital correlator is one of the most crucial data processing components of a radio telescope array. With the scale of radio interferometeric array growing, many efforts have been devoted to developing a cost-effective and scalable correlator in the field of radio astronomy. In this paper, a 192-input digital correlator with six CASPER ROACH2 boards and seven GPU servers has been deployed as the digital signal processing system for Tianlai cylinder pathfinder located in Hongliuxia observatory. The correlator consists of 192 input signals (96 dual-polarization), 125-MHz bandwidth, and full-Stokes output. The correlator inherits the advantages of the CASPER system, for example, low cost, high performance, modular scalability, and a heterogeneous computing architecture. With a rapidly deployable ROACH2 digital sampling system, a commercially expandable 10 Gigabit switching network system, and a flexible upgradable GPU computing system, the correlator forms a low-cost and easily-upgradable system, poised to support scalable large-scale interferometeric array in the future., Comment: 12 pages, 13 figures, accepted for publication in Frontiers in Astronomy and Space Sciences, section Astronomical Instrumentation

The 1S hyperfine splitting in hydrogen is measured to an impressive ppt precision and will soon be measured to ppm precision in muonic hydrogen. The latter measurement will rely on theoretical predictions, which are limited by knowledge of the proton polarizability effect $\Delta_\text{pol}$. Data-driven evaluations of $\Delta_\text{pol}$ have long been in significant tension with baryon chiral perturbation theory. Here we present improved results for $\Delta_\text{pol}$ driven by new spin structure data, reducing the long-standing tension between theory and experiment and halving the dominating uncertainty in hyperfine splitting calculations.

Variability can be the pathway to understanding the physical processes in astrophysical jets, however, the high-cadence observations required to test particle acceleration models are still missing. Here we report on the first attempt to produce continuous, >24 hour polarization light curves of blazars using telescopes distributed across the globe and the rotation of the Earth to avoid the rising Sun. Our campaign involved 16 telescopes in Asia, Europe, and North America. We observed BL Lacertae and CGRaBS J0211+1051 for a combined 685 telescope hours. We find large variations in the polarization degree and angle for both sources in sub-hour timescales as well as a ~180 degree rotation of the polarization angle in CGRaBS J0211+1051 in less than two days. We compared our high-cadence observations to Particle-In-Cell magnetic reconnection and turbulent plasma simulations. We find that although the state of the art simulation frameworks can produce a large fraction of the polarization properties, they do not account for the entirety of the observed polarization behavior in blazar jets., Comment: 20 pages, 15 figures, 2 tables, accepted for publication in A&A. The data used in the paper are available here: https://doi.org/10.7910/DVN/IETSXS

In cross-modal music processing, translation between visual, auditory, and semantic content opens up new possibilities as well as challenges. The construction of such a transformative scheme depends upon a benchmark corpus with a comprehensive data infrastructure. In particular, the assembly of a large-scale cross-modal dataset presents major challenges. In this paper, we present the MOSA (Music mOtion with Semantic Annotation) dataset, which contains high quality 3-D motion capture data, aligned audio recordings, and note-by-note semantic annotations of pitch, beat, phrase, dynamic, articulation, and harmony for 742 professional music performances by 23 professional musicians, comprising more than 30 hours and 570 K notes of data. To our knowledge, this is the largest cross-modal music dataset with note-level annotations to date. To demonstrate the usage of the MOSA dataset, we present several innovative cross-modal music information retrieval (MIR) and musical content generation tasks, including the detection of beats, downbeats, phrase, and expressive contents from audio, video and motion data, and the generation of musicians' body motion from given music audio. The dataset and codes are available alongside this publication (https://github.com/yufenhuang/MOSA-Music-mOtion-and-Semantic-Annotation-dataset)., Comment: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024. 14 pages, 7 figures. Dataset is available on: https://github.com/yufenhuang/MOSA-Music-mOtion-and-Semantic-Annotation-dataset/tree/main and https://zenodo.org/records/11393449

We propose to measure the energy correlator in quarkonium production, which tracks the energy deposited in the calorimeter $\chi$-angular distance away from the identified quarkonium. The observable eliminates the need for jets while sustaining the perturbative predictive power. Analyzing the power correction to the energy correlator, we demonstrate the novel observable supplies a unique gateway to probing the hadronization, especially when $\cos\chi\gtrsim 0$ in the quarkonium rest frame where the perturbative emissions are depleted due to the dead-cone effects. We expect the quarkonium energy correlator to add a new dimension to quarkonium studies., Comment: 7 pages, 4 figures + supplemental materials (3 pages)

This paper focuses on optimal constants and optimizers of the second order Caffarelli-Kohn-Nirenberg inequalities. Firstly, we aim to study optimal constants and optimizers for the following second order Caffarelli-Kohn-Nirenberg inequality in radial space: let $N\ge1$, $t\ge p>1$, \begin{equation}\label{0.1} \left(\int_{\mathbb{R}^N} \frac{|\Delta u|^p}{|x|^{p\alpha}} \mathrm{d}x\right)^{\frac{1}{p}} \left[\int_{\mathbb{R}^N} \frac{\left|\nabla u\right|^{\frac{p(t-1)}{p-1}}} {|x|^{\frac{p(t-1)}{p-1}\beta}} \mathrm{d}x\right]^{\frac{p-1}{p}} \ge C(N,p,t,\alpha,\beta) \int_{\mathbb{R}^N} \frac{\left|\nabla u\right|^t}{|x|^{t\gamma}} \mathrm{d}x. \end{equation} Secondly, we establish second order $L^p$-Caffarelli-Kohn-Nirenberg identities, and obtain optimal constants and optimizers of the second order $L^p$-Caffarelli-Kohn-Nirenberg inequalities (i.e., $p=t$ in \eqref{0.1}) in general space. Lastly, under some more general assumptions, we consider the optimal weighted second order Heisenberg Uncertainty Principles, which complements the recent work [``The sharp second order Caffareli-Kohn-Nirenberg inequality and stability estimates for the sharp second order uncertainty principle'', 2022, arXiv:2102.01425]. This paper's main novelty lies in the fact that we research the optimal versions of the second order Caffarelli-Kohn-Nirenberg inequalities \eqref{0.1} in radial space or in general space, and also establish the second order $L^p$-Caffarelli-Kohn-Nirenberg identities.

We have performed three-dimensional thunderstorm real simulations using the two-moment and three-moment bulk microphysics schemes in the Weather Research and Forecasting (WRF) model. We have analyzed three cases to understand the potential differences between the double-moment (Morrison-2M) and National Taiwan University triple-moment (NTU-3M) microphysics parameterizations in capturing the characteristics of lightning events over the Indian subcontinent. Despite general resemblances in these schemes, the simulations reveal distinct differences in storm structure, cloud hydrometeors formation, and precipitation. The lightning flash counts from the in situ lightning detection network (LDN) are also used to compare the simulation of storms. The Lightning Potential Index (LPI) is computed for Morrison-2M and NTU-3M microphysics schemes and compared it with the Lightning Detection Network (LDN) observation. In most cases, the Morrison-2M shows more LPI than the NTU-3M scheme. Both the schemes also differ in simulating rainfall and other thermodynamical, dynamical, and microphysical parameters in the model. Here, we have attempted to identify the basic differences between these two schemes, which may be responsible for the discrepancies in the simulations. In particular, the Morrison-2M produced much higher surface precipitation rates. The effects on the size distributions cloud hydrometeors between two microphysical schemes are important to simulate the biases in the precipitation and lightning flash counts. The inclusions of ice crystal shapes are responsible for many of the key differences between the two microphysics simulations. Different approaches in treating cloud ice, snow, and graupel may have an impact on the simulation of lightning and precipitation. Results show that the simulation of lightning events is sensitive to microphysical parameterization schemes in NWP models.

Layered transition metal chalcogenides have stimulated a wide research interest due to their many exotic physical properties. In this paper, we studied the magnetotransport properties of the exfoliated TaNiTe5, a recently discovered Dirac nodal-line semimetal. A giant positive magnetoresistance (MR) is observed when the current is parallel to the crystallographic c axis, while it is strongly diminished when the current flows along the a axis. The observed giant MR is gradually suppressed either on reducing the thickness of nanoflake or on increasing temperature. By performing MR measurement in tilted magnetic fields, the interlayer coupling is found to be weakened both by reducing the thickness and by increasing temperature. We propose a mechanism of electron-electron interaction-assisted interlayer transport as a origin of the giant MR. The mechanism is likely to provide a explanation for the giant MR in other layered materials., Comment: 21 pages, 7 figures, 1 table

We study the single parton fragmentation functions (FFs) at the input factorization scale $\mu_0\gtrsim 2m_Q$, with heavy quark mass $m_Q$, in the soft gluon factorization (SGF) approach. We express the FFs in terms of perturbatively calculable short distance hard parts for producing a heavy quark-antiquark pair in all possible states, convoluted with corresponding soft gluon distribution for the hadronization of the pair to a heavy quarkonium. We compute the perturbative short distance hard parts for producing a heavy quark pair in all possible $S$-wave and $P$-wave states up to $O(\alpha_s^2)$. With our results, the SGF can be further used to study the heavy quarkonium production at the hadron colliders and heavy quarkonium production within a jet., Comment: 19 pages, 0 figures. arXiv admin note: text overlap with arXiv:2304.04552

We present a comprehensive investigation on the mass function (MF) of a snake-like stellar structure in the solar neighbourhood, building on our previous discovery. To ensure the reliability of the data, we reselect the member stars of the Stellar ``Snake'' in the latest {\it Gaia} Data Release 3 using the same approach as the initial series of articles. We also precisely measure the physical parameters of the clusters within the Stellar Snake. In light of the high completeness of the member stars in the cluster regions, we develop a simulated model color-magnitude diagram-based inference method to derive the mass function, binary fraction, and mass-ratio distribution of the clusters in the Stellar Snake. Notably, despite their similar ages and metallicity, we discover systematic variations in the MFs along the elongation direction of the Snake in the mass range of 0.5 to 2.0 M$_\odot$. The ``head'' of the Snake conforms to a canonical initial mass function with a power-law slope of $\alpha\sim-2.3$. Extending towards the ``tail,'' the MF becomes more top-light, indicating a deficiency of massive stars within these clusters. This result provides evidence for the delayed formation of massive stars in the clusters. Such clues give support to the hypothesis that the Stellar Snake constitutes as a hierarchically primordial structure., Comment: 19 pages, 15 figures, Accepted for publication on MNRAS

We report 850 $\mu$m continuum polarization observations toward the filamentary high-mass star-forming region NGC 2264, taken as part of the B-fields In STar forming Regions Observations (BISTRO) large program on the James Clerk Maxwell Telescope (JCMT). These data reveal a well-structured non-uniform magnetic field in the NGC 2264C and 2264D regions with a prevailing orientation around 30 deg from north to east. Field strengths estimates and a virial analysis for the major clumps indicate that NGC 2264C is globally dominated by gravity while in 2264D magnetic, gravitational, and kinetic energies are roughly balanced. We present an analysis scheme that utilizes the locally resolved magnetic field structures, together with the locally measured gravitational vector field and the extracted filamentary network. From this, we infer statistical trends showing that this network consists of two main groups of filaments oriented approximately perpendicular to one another. Additionally, gravity shows one dominating converging direction that is roughly perpendicular to one of the filament orientations, which is suggestive of mass accretion along this direction. Beyond these statistical trends, we identify two types of filaments. The type-I filament is perpendicular to the magnetic field with local gravity transitioning from parallel to perpendicular to the magnetic field from the outside to the filament ridge. The type-II filament is parallel to the magnetic field and local gravity. We interpret these two types of filaments as originating from the competition between radial collapsing, driven by filament self-gravity, and the longitudinal collapsing, driven by the region's global gravity., Comment: Accepted for publication in the Astrophysical Journal. 43 pages, 32 figures, and 4 tables (including Appendix)

The detection of anomalies in multivariate time series data is crucial for various practical applications, including smart power grids, traffic flow forecasting, and industrial process control. However, real-world time series data is usually not well-structured, posting significant challenges to existing approaches: (1) The existence of missing values in multivariate time series data along variable and time dimensions hinders the effective modeling of interwoven spatial and temporal dependencies, resulting in important patterns being overlooked during model training; (2) Anomaly scoring with irregularly-sampled observations is less explored, making it difficult to use existing detectors for multivariate series without fully-observed values. In this work, we introduce a novel framework called GST-Pro, which utilizes a graph spatiotemporal process and anomaly scorer to tackle the aforementioned challenges in detecting anomalies on irregularly-sampled multivariate time series. Our approach comprises two main components. First, we propose a graph spatiotemporal process based on neural controlled differential equations. This process enables effective modeling of multivariate time series from both spatial and temporal perspectives, even when the data contains missing values. Second, we present a novel distribution-based anomaly scoring mechanism that alleviates the reliance on complete uniform observations. By analyzing the predictions of the graph spatiotemporal process, our approach allows anomalies to be easily detected. Our experimental results show that the GST-Pro method can effectively detect anomalies in time series data and outperforms state-of-the-art methods, regardless of whether there are missing values present in the data. Our code is available: https://github.com/huankoh/GST-Pro., Comment: Accepted by Information Fusion

The seasonal prediction of the Indian summer monsoon (ISM) and Monsoon Intraseasonal Oscillations (MISO), as well as the Madden Julian Oscillations (MJO) that strongly modulate MISO, is important to the country for water and crop management. We have analyzed the precipitation, convection, and total cloud fraction (TCF) in the sixth Coupled Model Intercomparison Projects (CMIP6). This study highlights the significant differences in simulating MISO and MJO between the two groups of selected CMIP6 models and physical reasons behind them. The mean and intraseasonal features of MISO and MJO varied significantly in CMIP6 models, which are linked with a better depiction of convection and total cloud fraction. The probability distributions of rainfall and OLR in CMIP6 models indicate significant variations in simulating ISM precipitating clouds. TaiESM1 and IITM-ESM demonstrate improvements in capturing the MISO features. TaiESM1 depicts better eastward propagation of MJO during both summer and winter. The biases in OLR and TCF are also less in the IITM-ESM and TaiESM1 models than in CanESM5 and FGOALS-g3. The results demonstrate the importance of cloud and convection in CMIP6 models to depict realistic MISO and MJO and provide a road map for improving ISM climate prediction and projections. Keywords: ISM rainfall, CMIP6 models, MISO, MJO

In this paper, we consider rational hypergeometric series of the form \[\frac{p}{\pi}= \sum_{k=0}^\infty u_k\quad\text{with}\quad u_k=\frac{\left(\frac{1}{2}\right)_k \left(q\right)_k \left(1-q\right)_k}{(k!)^3}(r+s\,k)\,t^k,\] where $(a)_k$ denotes the Pochhammer symbol and $p,q,r,s,t$ are algebraic coefficients. Using only the first $n+1$ terms of this series, we define the remainder \[\mathcal{R}_n = \frac{p}{\pi} - \sum_{k=0}^n u_k=\sum_{k=n+1}^\infty u_k.\] We consider an asymptotic expansion of $\mathcal{R}_n$. More precisely, we provide a recursive relation for determining the coefficients $c_j$ such that \[ \mathcal{R}_n = \frac{\left(\frac{1}{2}\right)_n \left(q\right)_n \left(1-q\right)_n}{n!^3}nt^n\left(\sum_{j=0}^{J-1}\frac{c_j}{n^j}+\mathcal{O}\left(n^{-J}\right)\right),\qquad n \rightarrow \infty.\] Here we need $J<\infty$ to approximate $\mathcal{R}_n$, because (like the Stirling series) this series diverges if $J\rightarrow\infty$. By applying our recursive relation to the Chudnovsky formula, we solve an open problem posed by Han and Chen., Comment: 12 pages

In recent years, certain luminous extragalactic optical transients have been observed to last only a few days. Their short observed duration implies a different powering mechanism from the most common luminous extragalactic transients (supernovae) whose timescale is weeks. Some short-duration transients, most notably AT2018cow, display blue optical colours and bright radio and X-ray emission. Several AT2018cow-like transients have shown hints of a long-lived embedded energy source, such as X-ray variability, prolonged ultraviolet emission, a tentative X-ray quasiperiodic oscillation, and large energies coupled to fast (but subrelativistic) radio-emitting ejecta. Here we report observations of minutes-duration optical flares in the aftermath of an AT2018cow-like transient, AT2022tsd (the "Tasmanian Devil"). The flares occur over a period of months, are highly energetic, and are likely nonthermal, implying that they arise from a near-relativistic outflow or jet. Our observations confirm that in some AT2018cow-like transients the embedded energy source is a compact object, either a magnetar or an accreting black hole., Comment: 79 pages, 3 figures (main text) + 7 figures (extended data) + 2 figures (supplementary information). Published online in Nature on 15 November 2023

Multi-fidelity (MF) methods are gaining popularity for enhancing surrogate modeling and design optimization by incorporating data from various low-fidelity (LF) models. While most existing MF methods assume a fixed dataset, adaptive sampling methods that dynamically allocate resources among fidelity models can achieve higher efficiency in the exploring and exploiting the design space. However, most existing MF methods rely on the hierarchical assumption of fidelity levels or fail to capture the intercorrelation between multiple fidelity levels and utilize it to quantify the value of the future samples and navigate the adaptive sampling. To address this hurdle, we propose a framework hinged on a latent embedding for different fidelity models and the associated pre-posterior analysis to explicitly utilize their correlation for adaptive sampling. In this framework, each infill sampling iteration includes two steps: We first identify the location of interest with the greatest potential improvement using the high-fidelity (HF) model, then we search for the next sample across all fidelity levels that maximize the improvement per unit cost at the location identified in the first step. This is made possible by a single Latent Variable Gaussian Process (LVGP) model that maps different fidelity models into an interpretable latent space to capture their correlations without assuming hierarchical fidelity levels. The LVGP enables us to assess how LF sampling candidates will affect HF response with pre-posterior analysis and determine the next sample with the best benefit-to-cost ratio. Through test cases, we demonstrate that the proposed method outperforms the benchmark methods in both MF global fitting (GF) and Bayesian Optimization (BO) problems in convergence rate and robustness. Moreover, the method offers the flexibility to switch between GF and BO by simply changing the acquisition function.

We uncover a hub-filament system associated with massive star formation in the G083.097$+$03.270. Diagnosed with simultaneous $^{12}$CO, $^{13}$CO, and C$^{18}$O line observations, the region is found to host two distinct and elongated filaments having separate velocity components, interacting spatially and kinematically, that appear to have seeded the formation of a dense hub at the intersection. A large velocity spread at the hub in addition to clear bridging feature connecting the filaments in velocity are indicating merging of filaments. Along the filaments axis, the velocity gradient reveals a global gas motion with an increasing velocity dispersion inward to the hub signifying turbulence. Altogether, the clustering of Class I sources, a high excitation temperature, a high column density, and presence of a massive outflow at the central hub suggest enhanced star formation. We propose that merging of large-scale filaments and velocity gradients along filaments are the driving factors in the mass accumulation process at the hub that have sequentially led to the massive star formation. With two giant filaments merging to coincide with a hub therein with ongoing star formation, this site serves as a benchmark for the `filaments to clusters' star-forming paradigm., Comment: 12 pages, 7 figures, 1 table, accepted for publication in ApJ

The dynamic steering of a beam reflected from a photonic structure supporting Tamm plasmon polariton is demonstrated. The phase and amplitude of the reflected wave are adjusted by modulating the refractive index of a transparent conductive oxide layer by applying a bias voltage. It is shown that the proposed design allows for two-dimensional beam steering by deflecting the light beam along the polar and azimuthal angles.

Multivariate time-series anomaly detection is critically important in many applications, including retail, transportation, power grid, and water treatment plants. Existing approaches for this problem mostly employ either statistical models which cannot capture the non-linear relations well or conventional deep learning models (e.g., CNN and LSTM) that do not explicitly learn the pairwise correlations among variables. To overcome these limitations, we propose a novel method, correlation-aware spatial-temporal graph learning (termed CST-GL), for time series anomaly detection. CST-GL explicitly captures the pairwise correlations via a multivariate time series correlation learning module based on which a spatial-temporal graph neural network (STGNN) can be developed. Then, by employing a graph convolution network that exploits one- and multi-hop neighbor information, our STGNN component can encode rich spatial information from complex pairwise dependencies between variables. With a temporal module that consists of dilated convolutional functions, the STGNN can further capture long-range dependence over time. A novel anomaly scoring component is further integrated into CST-GL to estimate the degree of an anomaly in a purely unsupervised manner. Experimental results demonstrate that CST-GL can detect anomalies effectively in general settings as well as enable early detection across different time delays., Comment: 17 pages, double columns, 10 tables, 3 figures. Accepted to IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Using membership of 85 open clusters from previous studies (Pang et al. 2021a,b, 2022b; Li et al. 2021) based on Gaia DR3 data, we identify binary candidates in the color-magnitude diagram, for systems with mass ratio q > 0.4. The binary fraction is corrected for incompleteness at different distances due to the Gaia angular resolution limit. We find a decreasing binary fraction with increasing cluster age, with substantial scatter. For clusters with a total mass > 200$M_\odot$, the binary fraction is independent of cluster mass. The binary fraction depends strongly on stellar density. Among four types of cluster environments, the lowest-density filamentary and fractal stellar groups have the highest mean binary fraction: 23.6% and 23.2%, respectively. The mean binary fraction in tidal-tail clusters is 20.8%, and is lowest in the densest halo-type clusters: 14.8%. We find clear evidence of early disruptions of binary stars in the cluster sample. The radial binary fraction depends strongly on the cluster-centric distance across all four types of environments, with the smallest binary fraction within the half-mass radius $r_h$, and increasing towards a few $r_h$. Only hints of mass segregation is found in the target clusters. The observed amount of mass segregation is not significant to generate a global effect inside the target clusters. We evaluate the bias of unresolved binary systems (assuming a primary mass of 1$M_\odot$) in 1D tangential velocity, which is 0.1-1$\,\rm km\,s^{-1}$. Further studies are required to characterize the internal star cluster kinematics using Gaia proper motions.

Optical bistability is fundamental for all-optical switches, but typically requires high-Q cavities with micrometer sizes. Through boosting nonlinearity with photo-thermo-optical effects, we achieve bistability in a silicon Mie resonator with a volume size of 10-3 um3 and Q-factor < 10, both are record-low. Furthermore, bistable scattering naturally leads to large super-linear emission-excitation power dependence, which we applied to enhance optical resolution by more than 3 times. Our work paves the way toward nanoscale photonics computation and label-free semiconductor nano-inspection.