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This study extended noncanonical warm inflation to the nonminimal derivative coupling scenario. The fundamental equations, including the evolution equations and the slow roll equations of this new framework, were derived. The enlarged damping term, which encompasses both gravitationally enhanced friction and thermal damping, resulted in a well overdamped inflationary process, ensuring that the slow roll approximations can be satisfactorily satisfied. A linear stability analysis corroborated the viability of this approach, yielding significantly relaxed slow roll conditions within the context of noncanonical warm inflation with nonminimal derivative coupling. Subsequently, the density fluctuations in this new framework were analyzed, leading to approximately analytic results for the power spectrum, spectral index, and related quantities. Both the energy scale at horizon crossing and the tensor-to-scalar ratio decreased considerably because of the effects of thermal damping and nonminimal derivative coupling. The upper bound for field excursion remained safely sub-Planckian in this inflationary scenario. Thus we reached a successful and meaningful model to broad the scope of warm inflation., Comment: 16 pages, 0 figures

The $s\to u$ weak decays of heavy flavor hadrons play a unique role in the field of heavy flavor physics. In this work, we investigate the $s\to u$ decays of singly heavy baryons. We first obtain the form factors in the light-front approach under the three-quark picture, and then apply them to give some predictions on the semileptonic decays. Due to the extremely small phase space, lepton flavor universality (LFU) is sensitive to the masses of leptons, and precise measurement of LFU is expected to be an important tool for testing the standard model. We find that a commonly used method for extracting form factors in the literature is no longer applicable at this time. We also point out the correct way to thoroughly discuss the heavy quark limit for these decays., Comment: 19 pages, no figures, 5 tables

Presently, punctuation restoration models are evaluated almost solely on well-structured, scripted corpora. On the other hand, real-world ASR systems and post-processing pipelines typically apply towards spontaneous speech with significant irregularities, stutters, and deviations from perfect grammar. To address this discrepancy, we introduce SponSpeech, a punctuation restoration dataset derived from informal speech sources, which includes punctuation and casing information. In addition to publicly releasing the dataset, we contribute a filtering pipeline that can be used to generate more data. Our filtering pipeline examines the quality of both speech audio and transcription text. We also carefully construct a ``challenging" test set, aimed at evaluating models' ability to leverage audio information to predict otherwise grammatically ambiguous punctuation. SponSpeech is available at https://github.com/GitHubAccountAnonymous/PR, along with all code for dataset building and model runs., Comment: 8 pages, 7 tables, 1 figure, Recognition Technologies, Inc. Technical Report

Using X-ray tomography, we experimentally investigate granular segregation phenomena in a mixture of particles with different densities under quasi-static cyclic shear. We quantitatively characterize their height distributions at steady states by minimizing effective free energy based on a segregation temperature that captures the competition between the mixing entropy and gravitational potential energy. We find this temperature coincides with Edwards' compactivity within error under various pressures and cyclic shear amplitudes. Therefore, we find that granular segregation in quasi-static conditions can be fundamentally explained by an effective granular thermodynamic framework including real energy terms based on the Edwards statistical ensemble., Comment: 18 pages, 5 figures

In traditional QCD sum rules, the simple hadron spectral density model of ``delta-function-type ground state + theta-function-type continuous spectrum" determines that there is no perfect parameter selection. In recent years, inverse problem methods, especially the inverse matrix method, have shown better handling of QCD sum rules. This work continues to develop the inverse matrix method. Considering that the narrow-width approximation may still be a good approximation, we separate the contribution of the ground state from the spectral density. Then follow the general steps of the inverse matrix method to extract physical quantities such as decay constants that we are sometimes more interested in., Comment: 13 pages, 6 figures

Non-Fermi liquids, particularly the universal strange metal, are ubiquitously observed in strongly correlated materials, that includes the high-$T_c$ cuprates, ruthenate oxides and twisted bilayer graphenes. The unprecedent tunablity of these two-dimensional (2D) systems provides access towards the Lifshitz transition where the Fermi surface exhibits van Hove singularity (VHS) saddle points. Despite extensive investigation on the ordering instabilities, the critical phenomenon induced by the VHS are rarely explored. Here, we investigate the NFL behaviors at Lifshitz transition in the 2D magnetic heterostructure interface, where the Fermi surface undergoes a convex-to-concave topological transition. We uncover an exotic NFL phase at the VHS that dominates over other Fermi surface points in the low-energy limit. At finite energies, it crossovers to the well-known marginal Fermi liquid (MFL). In the finite-temperature regimes, we demonstrate that the universal strange metal transport emerges both in the MFL phase, and unexpectedly, in the exotic NFL phase which is induced by solely by the spatially uniform Yukawa interaction. This non-vanishing optical conductivity is largely attributed to the Galilean invariance breaking at VHS. Furthermore, we propose that the non-magnetic ARPES can directly probe the exotic NFL features at heterostructure interface. Our findings explore the interplay of VHS in lower dimension, disorder and strong interactions, which paves a novel path to study the high-$T_c$ superconductivity, 2D magnetism and spintronics., Comment: 44 pages, 8 figures

Capturing molecular knowledge with representation learning approaches holds significant potential in vast scientific fields such as chemistry and life science. An effective and generalizable molecular representation is expected to capture the consensus and complementary molecular expertise from diverse views and perspectives. However, existing works fall short in learning multi-view molecular representations, due to challenges in explicitly incorporating view information and handling molecular knowledge from heterogeneous sources. To address these issues, we present MV-Mol, a molecular representation learning model that harvests multi-view molecular expertise from chemical structures, unstructured knowledge from biomedical texts, and structured knowledge from knowledge graphs. We utilize text prompts to model view information and design a fusion architecture to extract view-based molecular representations. We develop a two-stage pre-training procedure, exploiting heterogeneous data of varying quality and quantity. Through extensive experiments, we show that MV-Mol provides improved representations that substantially benefit molecular property prediction. Additionally, MV-Mol exhibits state-of-the-art performance in multi-modal comprehension of molecular structures and texts. Code and data are available at https://github.com/PharMolix/OpenBioMed., Comment: 12 pages, 4 figures

We analyze more than 15 years of the \gr\ data, obtained with the Large Area Telescope (LAT) onboard {\it the Fermi Gamma-ray Space Telescope (Fermi)}, for the region of the young supernova remnant (SNR) RCW~103, since the nearby source 4FGL J1616.2$-$5054e, counterpart to HESS~J1616$-$518 and $\simeq$13\,arcmin away from the SNR, is determined to be extended in the more recent Fermi-LAT source catalog. Different templates for 4FGL J1616.2$-$5054e and RCW~103 are tested, and we find that a point source with a power-law (PL) spectrum at the southern limb of the SNR best describes the detected gamma-ray emission. The photon index of the PL emission is $\Gamma\simeq 2.31$(or $\alpha\simeq 2.4$ in a Log-Parabola model) , softer than the previously reported $\Gamma\simeq 2.0$ when the counterpart to HESS~J1616$-$518 was considered to be a point source (which likely caused mis-identification of extended emission at RCW~103). In order to produce the \gr\ emission in a hadronic scenario, we estimate that protons with an index$\sim$2.4 PL energy distribution are needed. These results fit with those from multi-wavelength observations that have indicated the remnant at the southern limb is interacting with a molecular cloud., Comment: 7 pages, 4 figures, 2 tables, accepted for publication in ApJ

We theoretically study the two-dimensional metal that is coupled to critical magnons and features van Hove singularities on the Fermi surface. When there is only translationally invariant SYK-liked Yukawa interaction, van Hove points suppress the contribution from the part of the Fermi surface away from them, dominating and exhibiting non-Fermi-liquid behavior. When introducing disordered Yukawa coupling, it leads to a crossover from non-Fermi-liquid to marginal-Fermi-liquid, and the marginal-Fermi-liquid region exhibits the $T\ln (1/T)$ specific heat and temperature-linear resistivity of strange metal. By solving the gap equation, we provide the critical temperature for superconductor induced by van Hove singularities and point out the possible emergence of pair-density-wave superconductor. Our theory may become a new mechanism for understanding non-Fermi-liquid or marginal-Fermi-liquid phenomenons., Comment: 14 pages, 5 figures

We investigate the interference of two-dimensional Bose-Einstein condensates in micro-gravity, which influenced by the interaction strength, initial momentum, gravitational potential and phase difference. We demonstrate that the gravitational potential from the Earth can change the density distribution and phase distribution of the condensate's wave function. As time evolves, a portion of the gravitational potential energy of the microscopic particles can be converted into kinetic energy, which changes the motion of the microscopic particles, and leads to the varying of the density and phase distribution of the wave function. Nevertheless, the influences of the Earth's gravity on the wave function can be eliminated by the micro-gravity environment, which confirmed by many micro-gravity cold atom experiments. Our results present the influences of gravity and other parameters on interference of Bose-Einstein condensates, which help us to reveal the intrinsic natures of the related theoretical predictions and experimental phenomena. Furthermore, our work builds a bridge between the related physical phenomena and our physical intuition about the Bose-Einstein condensates in micro-gravity environment.

The Galactic Center Excess (GCE) $\gamma$-ray emission detected with the Large Area Telescope onboard the {\it Fermi Gamma-ray Space Telescope} has been considered as a possible sign for dark matter (DM) annihilation, but other possibilities such as the millisecond pulsar (MSP) origin have also been suggested. As a spectral fitting method, constructed based on properties of $\gamma$-ray MSPs, has been developed, we apply this method to the study of the GCE emission for the purpose of probing the MSP origin for the GCE. A number of $\sim$1660 MSPs can provide a fit to the spectrum of the GCE emission upto $\sim$10\,GeV, but the higher energy part of the spectrum requires additional emission components. We further carry out a stacking analysis of 30--500\,GeV data for relatively nearby $\gamma$-ray MSPs, and the resulting flux upper limits are still lower than those of the GCE emission. We consider the single DM annihilation channel $\tau^{+}\tau^{-}$ or channel $b\bar{b}$,or the combination of the two for comparison, and find they generally can provide better fits than MSPs. Combination of MSPs plus a DM channel are also tested, and MSPs plus the DM channel $b\bar{b}$ can always provide better fits. Comparing this combination case to the pure DM channel $b\bar{b}$, the MSP contribution is found to be marginally needed., Comment: 13 pages, 8 figures, 2 tables, submitted to ApJ

Intrigued by recent high-energy study results for nearby galaxies with gamma-ray emission and in particular NGC~1068 that has been detected as a neutrino-emitting source by the IceCube Neutrino Observatory, we conduct detailed analysis of the $\gamma$-ray data for the galaxies NGC~1068 and NGC~253, obtained with the Large Area Telescope onboard {\it the Fermi Gamma-ray Space Telescope}. By checking for their possible spectral features and then constructing light curves in corresponding energy ranges, we identify spectral-change activity from NGC ~1068 in $\geq$2\,GeV energy range and long-term detection significance changes for NGC~253 in $\geq$5\,GeV energy range. In the former, the emission appears harder in two half-year time periods than that in the otherwise `quiescent' state. In the latter, a $\sim$2-times detection significance decrease after MJD~57023 is clearly revealed by the test-statistic maps we obtain. Considering studies carried out and models proposed for the $\gamma$-ray emissions of the two sources, we discuss the implications of our findings. We suspect that the jet (or outflow) in NGC~1068 might contribute to the \gr\ emission. The nature of the long-term detection significance change for NGC~253 is not clear, but since the part of the GeV emission may be connected to the very-high-energy (VHE) emission from the center of the galaxy, it could be further probed with VHE observations., Comment: 10 pages, 7 figures, 2 tables, revised by incorporating Referee's comments, accepted for publication in ApJ

PSR~J0631+1036 is a middle-aged pulsar with properties similar to those of the nearby Geminga pulsar. It is bright in $\gamma$-rays, and has been noted as the only source possibly associated with the TeV source 3HWC J0631+107 (also the LHAASO J0631+1040). For understanding the nature of the TeV source, we analyze the GeV $\gamma$-ray data obtained with the Large Area Telescope (LAT) onboard {\it the Fermi Gamma-ray Space Telescope} for the source region. We are able to remove the pulsar's emission from the region from timing analysis, and find that the region is rather clean without possible GeV $\gamma$-ray emission present as the counterpart to the TeV source. By comparing this pulsar to Geminga and considering the spectral feature of the TeV source, we argue that it is likely the TeV halo powered by the pulsar., Comment: 5 pages, 4 figures, 1 tables, to appear on ApJ

Molecular knowledge resides within three different modalities of information sources: molecular structures, biomedical documents, and knowledge bases. Effective incorporation of molecular knowledge from these modalities holds paramount significance in facilitating biomedical research. However, existing multimodal molecular foundation models exhibit limitations in capturing intricate connections between molecular structures and texts, and more importantly, none of them attempt to leverage a wealth of molecular expertise derived from knowledge graphs. In this study, we introduce MolFM, a multimodal molecular foundation model designed to facilitate joint representation learning from molecular structures, biomedical texts, and knowledge graphs. We propose cross-modal attention between atoms of molecular structures, neighbors of molecule entities and semantically related texts to facilitate cross-modal comprehension. We provide theoretical analysis that our cross-modal pre-training captures local and global molecular knowledge by minimizing the distance in the feature space between different modalities of the same molecule, as well as molecules sharing similar structures or functions. MolFM achieves state-of-the-art performance on various downstream tasks. On cross-modal retrieval, MolFM outperforms existing models with 12.13% and 5.04% absolute gains under the zero-shot and fine-tuning settings, respectively. Furthermore, qualitative analysis showcases MolFM's implicit ability to provide grounding from molecular substructures and knowledge graphs. Code and models are available on https://github.com/BioFM/OpenBioMed., Comment: 31 pages, 15 figures, and 15 tables

Tha quantum electrodynamics of particles constrained to move on a plane is not a fully dimensionally reduced theory because the gauge fields through which they interact live in higher dimensions. By constraining the gauge field to the surface of the bulk, we obtain a fully reduced planar Abelian Chern-Simons Higgs model that can describe the vortex dynamics and second-order superconducting-normal phase transitions in planar Chern-Simons superconductors. Dual analyses performed before and after dimensional reduction yield the same Lagrangian for describing the vortex dynamics, indicating the self-consistency of our reduced theory. Compared to ordinary (2+1)-dimensional electrodynamics, we obtain anomalous fermion statistical vortices, consistent with results considering boundary effects. An additional electric charge constraint and different Chern-Simons parameter constraints are also found, which may help define a self-dual conformal field theory. Our renormalization group analysis shows that the quantized critical exponent depends on the Chern-Simons parameter. Quench disorder can bring more stable fixed points with different dynamical critical exponents. If we dimensionally reduce to a curved surface, our theory can also be extended to curved spacetimes, where geometric flow will be introduced and compete with vortex flow., Comment: 17 pages, 8 figures

In recent years, AI models that mine intrinsic patterns from molecular structures and protein sequences have shown promise in accelerating drug discovery. However, these methods partly lag behind real-world pharmaceutical approaches of human experts that additionally grasp structured knowledge from knowledge bases and unstructured knowledge from biomedical literature. To bridge this gap, we propose KEDD, a unified, end-to-end, and multimodal deep learning framework that optimally incorporates both structured and unstructured knowledge for vast AI drug discovery tasks. The framework first extracts underlying characteristics from heterogeneous inputs, and then applies multimodal fusion for accurate prediction. To mitigate the problem of missing modalities, we leverage multi-head sparse attention and a modality masking mechanism to extract relevant information robustly. Benefiting from integrated knowledge, our framework achieves a deeper understanding of molecule entities, brings significant improvements over state-of-the-art methods on a wide range of tasks and benchmarks, and reveals its promising potential in assisting real-world drug discovery., Comment: 10 pages, 6 figures

We report on the detection of a gamma-ray source at the position of the nearby star-forming galaxy (SFG) M83, which is found from our analysis of 14 years of the data obtained with the Large Area Telescope (LAT) on-board {\it Fermi Gamma-ray Space Telescope (Fermi)}. The source is weakly detected, with a significance of $\sim 5\sigma$, and its emission can be described with an exponentially cutoff power law. At a distance of 4.61\,Mpc, the source's gamma-ray luminosity is $\sim 1.4\times 10^{39}$\,erg\,s$^{-1}$, roughly along the correlation line between the \gr\ and IR luminosities determined for nearby SFGs. Because of the weak detection, the source spectrum can not be used for checking its similarity with those of other SFGs. Given the positional matches and the empirical expectation for gamma-ray emission from M83 due to the galaxy's star-forming activity, we conclude that the gamma-ray source is the likely counterpart to m83. The detection thus adds another member to the group of approximately a dozen SFGs, whose \gr\ emissions mostly have a cosmic-ray origin., Comment: 6 pages, 4 figures, 2 tables, accepted for publication in ApJ

Punctuation restoration plays an essential role in the post-processing procedure of automatic speech recognition, but model efficiency is a key requirement for this task. To that end, we present EfficientPunct, an ensemble method with a multimodal time-delay neural network that outperforms the current best model by 1.0 F1 points, using less than a tenth of its inference network parameters. We streamline a speech recognizer to efficiently output hidden layer acoustic embeddings for punctuation restoration, as well as BERT to extract meaningful text embeddings. By using forced alignment and temporal convolutions, we eliminate the need for attention-based fusion, greatly increasing computational efficiency and raising performance. EfficientPunct sets a new state of the art with an ensemble that weights BERT's purely language-based predictions slightly more than the multimodal network's predictions. Our code is available at https://github.com/lxy-peter/EfficientPunct., Comment: 6 pages, 1 figure, 5 tables, paper at IMCOM 2024, technical report at Recognition Technologies, Inc

Granular materials such as sand, powders, and grains are omnipresent in daily life, industrial applications, and earth-science [1]. When unperturbed, they form stable structures that resemble the ones of other amorphous solids like metallic and colloidal glasses [2]. It is commonly conjectured that all these amorphous materials show a universal mechanical response when sheared slowly, i.e., to have an elastic regime, followed by yielding [3]. Here we use X-ray tomography to determine the microscopic dynamics of a cyclically sheared granular system in three dimensions. Independent of the shear amplitude $\Gamma$, the sample shows a cross-over from creep to diffusive dynamics, indicating that granular materials have no elastic response and always yield, in stark contrast to other glasses. The overlap function [4] reveals that at large $\Gamma$ yielding is a simple cross-over phenomenon, while for small $\Gamma$ it shows features of a first order transition with a critical point at $\Gamma\approx 0.1$ at which one finds a pronounced slowing down and dynamical heterogeneity. Our findings are directly related to the surface roughness of granular particles which induces a micro-corrugation to the potential energy landscape, thus creating relaxation channels that are absent in simple glasses. These processes must be understood for reaching an understanding of the complex relaxation dynamics of granular systems.