arXiv subjects

Gang Li

Publications and source records attributed to Gang Li.

At least 253 records · Page 14Linked to original sources

arXiv2024

Role of Data-driven Regional Growth Model in Shaping Brain Folding Patterns

The surface morphology of the developing mammalian brain is crucial for understanding brain function and dysfunction. Computational modeling offers valuable insights into the underlying mechanisms for early brain folding. Recent findings indicate significant regional variations in brain tissue growth, while the role of these variations in cortical development remains unclear. In this study, we unprecedently explored how regional cortical growth affects brain folding patterns using computational simulation. We first developed growth models for typical cortical regions using machine learning (ML)-assisted symbolic regression, based on longitudinal real surface expansion and cortical thickness data from prenatal and infant brains derived from over 1,000 MRI scans of 735 pediatric subjects with ages ranging from 29 post-menstrual weeks to 24 months. These models were subsequently integrated into computational software to simulate cortical development with anatomically realistic geometric models. We comprehensively quantified the resulting folding patterns using multiple metrics such as mean curvature, sulcal depth, and gyrification index. Our results demonstrate that regional growth models generate complex brain folding patterns that more closely match actual brains structures, both quantitatively and qualitatively, compared to conventional uniform growth models. Growth magnitude plays a dominant role in shaping folding patterns, while growth trajectory has a minor influence. Moreover, multi-region models better capture the intricacies of brain folding than single-region models. Our results underscore the necessity and importance of incorporating regional growth heterogeneity into brain folding simulations, which could enhance early diagnosis and treatment of cortical malformations and neurodevelopmental disorders such as cerebral palsy and autism.

q-bio.NC↗

arXiv2024

Asteroseismic Signatures of Core Magnetism and Rotation in Hundreds of Low-Luminosity Red Giants

Red Giant stars host solar-like oscillations which have mixed character, being sensitive to conditions both in the outer convection zone and deep within the interior. The properties of these modes are sensitive to both core rotation and magnetic fields. While asteroseismic studies of the former have been done on a large scale, studies of the latter are currently limited to tens of stars. We aim to produce the first large catalogue of both magnetic and rotational perturbations. We jointly constrain these parameters by devising an automated method for fitting the power spectra directly. We successfully apply the method to 302 low-luminosity red giants. We find a clear bimodality in core rotation rate. The primary peak is at $δν_{\mathrm{rot}}$ = 0.32 $μ$Hz, and the secondary at $δν_{\mathrm{rot}}$ = 0.47 $μ$Hz. Combining our results with literature values, we find that the percentage of stars rotating much more rapidly than the population average increases with evolutionary state. We measure magnetic splittings of 2$σ$ significance in 23 stars. While the most extreme magnetic splitting values appear in stars with masses > 1.1M$_{\odot}$, implying they formerly hosted a convective core, a small but statistically significant magnetic splitting is measured at lower masses. Asymmetry between the frequencies of a rotationally split multiplet has previously been used to diagnose the presence of a magnetic perturbation. We find that of the stars with a significant detection of magnetic perturbation, 43\% do not show strong asymmetry. We find no strong evidence of correlation between the rotation and magnetic parameters.

astro-ph.SR↗

arXiv2024

Calculable neutrino Dirac mass matrix and one-loop $\bar θ$ in the minimal left-right symmetric model

We revisit the contribution to the strong CP parameter $\bar θ$ from leptonic CP violation at one-loop level in the minimal left-right symmetric model in the case of generalized parity as the left-right symmetry. The Hermitian neutrino Dirac mass matrix $M_D$ can be calculated using the light and heavy neutrino masses and mixings. We propose a parametrization of the right-handed neutrino mixing matrix $V_R$ and construct the heavy neutrino mass that maintains the Hermiticity of $M_D$. We further apply it to evaluate the one-loop $\barθ$, denoted as $\bar θ_{loop}$, as a function of the sterile neutrino masses for explicit examples of $V_R$. By requiring the magnitude of $\bar θ_{loop}\lesssim 10^{-10}$, we derive the upper limits on the sterile neutrino masses, which are within reach of direct searches at the Large Hadron Collider and neutrinoless double beta decay experiments. Furthermore, our parametrization is pertinent for other phenomenological investigations.

hep-ph↗

arXiv2024

GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization

Pre-trained language models are increasingly being used in multi-document summarization tasks. However, these models need large-scale corpora for pre-training and are domain-dependent. Other non-neural unsupervised summarization approaches mostly rely on key sentence extraction, which can lead to information loss. To address these challenges, we propose a lightweight yet effective unsupervised approach called GLIMMER: a Graph and LexIcal features based unsupervised Multi-docuMEnt summaRization approach. It first constructs a sentence graph from the source documents, then automatically identifies semantic clusters by mining low-level features from raw texts, thereby improving intra-cluster correlation and the fluency of generated sentences. Finally, it summarizes clusters into natural sentences. Experiments conducted on Multi-News, Multi-XScience and DUC-2004 demonstrate that our approach outperforms existing unsupervised approaches. Furthermore, it surpasses state-of-the-art pre-trained multi-document summarization models (e.g. PEGASUS and PRIMERA) under zero-shot settings in terms of ROUGE scores. Additionally, human evaluations indicate that summaries generated by GLIMMER achieve high readability and informativeness scores. Our code is available at https://github.com/Oswald1997/GLIMMER.

cs.CL↗

arXiv2024

UICrit: Enhancing Automated Design Evaluation with a UICritique Dataset

Automated UI evaluation can be beneficial for the design process; for example, to compare different UI designs, or conduct automated heuristic evaluation. LLM-based UI evaluation, in particular, holds the promise of generalizability to a wide variety of UI types and evaluation tasks. However, current LLM-based techniques do not yet match the performance of human evaluators. We hypothesize that automatic evaluation can be improved by collecting a targeted UI feedback dataset and then using this dataset to enhance the performance of general-purpose LLMs. We present a targeted dataset of 3,059 design critiques and quality ratings for 983 mobile UIs, collected from seven experienced designers. We carried out an in-depth analysis to characterize the dataset's features. We then applied this dataset to achieve a 55% performance gain in LLM-generated UI feedback via various few-shot and visual prompting techniques. We also discuss future applications of this dataset, including training a reward model for generative UI techniques, and fine-tuning a tool-agnostic multi-modal LLM that automates UI evaluation.

cs.HC↗

arXiv2024

Production of hidden-heavy and double-heavy hadronic molecules at the $Z$ factory of CEPC

With a clean environment and high collision energy, the Circular Electron Positron Collider (CEPC) would be an excellent facility for heavy flavor physics. Using the Monte Carlo event generator Pythia, we simulate the production of the charmed (bottom) hadron pairs in the electron-positron collisions at the $Z$ factory of CEPC, and the inclusive production rates for typical candidates of the hidden/double-charm and hidden/double-bottom $S$-wave hadronic molecules are estimated at an order-of-magnitude level with the final state interactions after the hadron pair production. The predicted cross sections for the hidden-charm meson-meson molecules $X(3872)$ and $Z_c(3900)$ are at $\rm{pb}$ level, which are about two to three orders of magnitude larger than the production cross sections for the double-charm meson-meson molecules $T_{cc}$ and $T_{cc}^{*}$, as the double-charmed ones require the production of two pairs of $c\bar{c}$ from the $Z$ boson decay. The production cross sections for the hidden-charm pentaquark states $P_{c}$ and $P_{cs}$ as meson-baryon molecules are a few to tens of fb, which are about one magnitude larger than those of the possible hidden-charm baryon-antibaryon and double-charm meson-baryon molecules. In the bottom sector, the production cross sections for the $Z_b$ states as $B^{(*)}\bar{B}^{*}$ molecules are about tens to hundreds of fb, indicating $10^6$ - $10^7$ events from a two-year operation of CEPC, and the expected events from the double-bottom molecules are about 2 - 5 orders of magnitude smaller than the $Z_b$ states. Our results shows great prospects of probing heavy exotic hadrons at CEPC.

hep-ph↗

arXiv2024

TIC441725813: A new bright hybrid sdB pulsator with differential core/envelope rotation

We present the detailed analysis of a new hybrid (p- and g-mode) sdB pulsator, TIC441725813 (TYC 4427-1021-1), discovered and monitored by TESS over 670 days. The TESS light curves available for this star were analysed using prewhitening techniques to extract mode frequencies accurately. The pulsation spectrum is then interpreted through methods that include asymptotic period spacing relationships and rotational multiplets identification. We also exploited a high signal-to-noise ratio (S/N), low-resolution spectrum of TIC441725813 using grids of non-local thermodynamic equilibrium (NLTE) model atmospheres to derive its atmospheric parameters. Interestingly, several frequency multiplets interpreted as rotational splittings of deep-probing g-modes indicate a slow rotation period of at least $85.3 \pm 3.6$ day, while splittings of mostly envelope-probing p-modes suggest a significantly shorter rotation period of $17.9 \pm 0.7$ day, which implies the core (mainly the helium mantle with possibly the deeper partially-mixed helium-burning core that it surrounds) rotates at least ~4.7 times slower than the envelope. The radial velocity curves indicate that TIC441725813 is in a close binary system with a low-luminosity companion, possibly a white dwarf. While elusive in the available TESS photometry, a low-frequency signal that would correspond to a period of $\sim 6.7$ h is found, albeit at low S/N. TIC441725813 is a particularly interesting sdB star whose envelope rotates faster than the core. We hypothesise that this might be caused by the effects of tidal interaction with a companion, although in the present case, the presence of such a companion will have to be further investigated. This analysis paves the way toward a more detailed seismic probing of TIC441725813 using optimisation techniques, which will be presented in a second paper.

astro-ph.SR↗

arXiv2024

Nuclear matrix elements of neutrinoless double-beta decay in covariant density functional theory with different mechanisms

Nuclear matrix elements (NMEs) for neutrinoless double-beta ($0νββ$) decay in candidate nuclei play a crucial role in interpreting results from current experiments and in designing future ones. Accurate NME values serve as important nuclear inputs for constraining parameters in new physics, such as neutrino mass and the Wilson coefficients of lepton-number-violating (LNV) operators. In this study, we present a comprehensive calculation of NMEs for $0νββ$ decay in $^{76}$Ge, $^{82}$Se, $^{100}$Mo, $^{130}$Te, and $^{136}$Xe, using nuclear wave functions obtained from multi-reference covariant density functional theory (MR-CDFT). We employ three types of transition potentials at the leading order in chiral effective field theory. Our results, along with recent data, are utilized to constrain the coefficients of LNV operators. The results demonstrate that the combined NMEs based on the Feynman diagrams at the hadronic scale for the nonstandard mechanisms lead to uncertainty by different nuclear models comparable to that for the standard mechanism. The use of NMEs from various nuclear models does not dramatically change the parameter space intervals for the coefficients, although MR-CDFT yields the most stringent constraint. Furthermore, our NMEs can also be used to perform a more comprehensive analysis with multiple isotopes.

nucl-th↗

arXiv2024

Parrot: Pareto-optimal Multi-Reward Reinforcement Learning Framework for Text-to-Image Generation

Recent works have demonstrated that using reinforcement learning (RL) with multiple quality rewards can improve the quality of generated images in text-to-image (T2I) generation. However, manually adjusting reward weights poses challenges and may cause over-optimization in certain metrics. To solve this, we propose Parrot, which addresses the issue through multi-objective optimization and introduces an effective multi-reward optimization strategy to approximate Pareto optimal. Utilizing batch-wise Pareto optimal selection, Parrot automatically identifies the optimal trade-off among different rewards. We use the novel multi-reward optimization algorithm to jointly optimize the T2I model and a prompt expansion network, resulting in significant improvement of image quality and also allow to control the trade-off of different rewards using a reward related prompt during inference. Furthermore, we introduce original prompt-centered guidance at inference time, ensuring fidelity to user input after prompt expansion. Extensive experiments and a user study validate the superiority of Parrot over several baselines across various quality criteria, including aesthetics, human preference, text-image alignment, and image sentiment.

cs.CV↗

arXiv2024

Electronic Correlation and Pseudogap-like Behavior of High-Temperature Superconductor La3Ni2O7

High-temperature superconductivity (HTSC) remains one of the most challenging and fascinating mysteries in condensed matter physics. Recently, superconductivity with transition temperature exceeding liquid-nitrogen temperature is discovered in La3Ni2O7 at high pressure, which provides a new platform to explore the unconventional HTSC. In this work, using high-resolution angle-resolved photoemission spectroscopy and ab-initio calculation, we systematically investigate the electronic structures of La3Ni2O7 at ambient pressure. Our experiments are in nice agreement with ab-initio calculations after considering an orbital-dependent band renormalization effect. The strong electron correlation effect pushes a flat band of d_(z^2 ) orbital component below the Fermi level (EF), which is predicted to locate right at EF under high pressure. Moreover, the d_(x^2-y^2 ) band shows a pseudogap-like behavior with suppressed spectral weight and diminished quasiparticle peak near EF. Our findings provide important insights into the electronic structure of La3Ni2O7, which will shed light on the understanding of the unconventional superconductivity in nickelates.

cond-mat.supr-con↗

arXiv2024

Charmless decays of the spin-2 partner of $X(3872)$

The Belle collaboration recently reported a promising candidate for the spin-2 $D^*\bar{D}^*$ partner of the $X(3872)$, called the $X_2$ for short, having a mass of $(4014.3 \pm 4.0 \pm 1.5)~\mathrm{MeV}$ and a width of $(4 \pm 11 \pm 6)~\mathrm{MeV} $. In present work, we assume the $X_2$ as a pure molecule of the $D^*\bar{D}^*$ under three cases, i.e., pure neutral components ($θ= 0$), isospin singlet ($θ= π/4$) and neutral components dominant ($θ= π/6$), where $θ$ is a phase angle describing the proportion of neutral and charged constituents. Using an effective Lagrangian approach, we calculated the partial widths of $X_2\to VV$ and $X_2 \to PP$ ($V$ and $P$ stand for light vector and pseudoscalar mesons, respectively). The predicted decay widths of $X_2 \to VV$ can reach a few hundreds of $\mathrm{keV}$, while the decay widths of $X_2 \to PP$ are about several tens of $\mathrm{keV}$. In addition, the effects from the proportion of neutral and charged constituent on the decay widths of $X_2\to VV$ and $PP$ are also investigated. We hope that the present calculations will be checked experimentally in the future.

hep-ph↗

arXiv2024

Channel Modeling Aided Dataset Generation for AI-Enabled CSI Feedback: Advances, Challenges, and Solutions

The AI-enabled autoencoder has demonstrated great potential in channel state information (CSI) feedback in frequency division duplex (FDD) multiple input multiple output (MIMO) systems. However, this method completely changes the existing feedback strategies, making it impractical to deploy in recent years. To address this issue, this paper proposes a channel modeling aided data augmentation method based on a limited number of field channel data. Specifically, the user equipment (UE) extracts the primary stochastic parameters of the field channel data and transmits them to the base station (BS). The BS then updates the typical TR 38.901 model parameters with the extracted parameters. In this way, the updated channel model is used to generate the dataset. This strategy comprehensively considers the dataset collection, model generalization, model monitoring, and so on. Simulations verify that our proposed strategy can significantly improve performance compared to the benchmarks.

eess.SP↗

arXiv2024

Single spin asymmetry $ A _{ U L } ^ { \sin ( 2 ϕ_ { h } ) }$ in dihadron production in SIDIS

The paper calculates the helicity-dependent dihadron fragmentation function (DiFF), by extending the dihadron spectator model and examine the single longitudinal spin asymmetry $A^{\sin(2ϕ_h)}_{UL}$ from dihadron in semi-inclusive inelastic scattering (SIDIS). This function elucidates the relationship between the longitudinal polarization of the fragmented quark and the transverse momentum of the resulting hadron pairs. A study by the COMPASS collaboration detected a minimal signal in their experimental search for this azimuthal asymmetry in SIDIS. Here, we use the spectator model to calculate the unknown T-odd dihadron fragmentation function $H_1^\perp$. Adopting collinear factorization to describe the data, avoiding the transverse momentum dependent factorization and the associated resummation effects, helping us understand the asymmetry and explaining why the signal is so weak. We involve the approach of transverse momentum dependence in the model calculations, in order to formulate the differential cross sections and the spin asymmetries in terms of the collinear parton distributions and the collinear DiFFs. A transverse momentum factor analysis method was used, in which the transverse momentum of the final hadron pairs was not integrated. The asymmetry of $sin(2ϕ_h)$ in COMPASS kinematics was calculated and compared with experimental data. In addition, predictions for the same asymmetry are also presented for HERMES and the Electron Ion Collider.

hep-ph↗

arXiv2024

Enhancing Automated Audio Captioning via Large Language Models with Optimized Audio Encoding

Automated audio captioning (AAC) is an audio-to-text task to describe audio contents in natural language. Recently, the advancements in large language models (LLMs), with improvements in training approaches for audio encoders, have opened up possibilities for improving AAC. Thus, we explore enhancing AAC from three aspects: 1) a pre-trained audio encoder via consistent ensemble distillation (CED) is used to improve the effectivity of acoustic tokens, with a querying transformer (Q-Former) bridging the modality gap to LLM and compress acoustic tokens; 2) we investigate the advantages of using a Llama 2 with 7B parameters as the decoder; 3) another pre-trained LLM corrects text errors caused by insufficient training data and annotation ambiguities. Both the audio encoder and text decoder are optimized by low-rank adaptation (LoRA). Experiments show that each of these enhancements is effective. Our method obtains a 33.0 SPIDEr-FL score, outperforming the winner of DCASE 2023 Task 6A.

cs.SD↗

arXiv2024

Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework

This paper introduces a robust zero-trust architecture (ZTA) tailored for the decentralized system that empowers efficient remote work and collaboration within IoT networks. Using blockchain-based federated learning principles, our proposed framework includes a robust aggregation mechanism designed to counteract malicious updates from compromised clients, enhancing the security of the global learning process. Moreover, secure and reliable trust computation is essential for remote work and collaboration. The robust ZTA framework integrates anomaly detection and trust computation, ensuring secure and reliable device collaboration in a decentralized fashion. We introduce an adaptive algorithm that dynamically adjusts to varying user contexts, using unsupervised clustering to detect novel anomalies, like zero-day attacks. To ensure a reliable and scalable trust computation, we develop an algorithm that dynamically adapts to varying user contexts by employing incremental anomaly detection and clustering techniques to identify and share local and global anomalies between nodes. Future directions include scalability improvements, Dirichlet process for advanced anomaly detection, privacy-preserving techniques, and the integration of post-quantum cryptographic methods to safeguard against emerging quantum threats.

cs.CR↗

arXiv2024

Oscillation Frequencies of Moderately Rotating Delta Scuti Stars: Asymmetric Mode Splittings Due to Non-spherical Distortion

We find that the observed pressure-mode rotational splittings of slowly/moderately rotating Delta Scuti stars and Beta Cephei stars mostly have a positive asymmetry. That is, the left frequency spacing is larger than the right spacing in the dipole mode splitting triplets and the $l=2$ mode splitting multiplets (considering $m=1, 0, -1$ modes only). This is in agreement with the second-order perturbative effect of the rotational non-spherical distortion: both the prograde and retrograde modes have their frequencies shifted towards lower values relative to the $m=0$ modes. We thus study the rotational perturbation both in the first and second order, as well as the near-degeneracy mode coupling effect in MESA models representing Delta Scuti stars. For faster rotators, the near-degeneracy mode coupling between the nearest radial and quadrupole modes can significantly shift the $m=0$ modes, reduce the splitting asymmetry, and even change its sign. We find the theoretical splitting asymmetry from the second-order non-spherical distortion is larger than observed asymmetry. To facilitate future detections, we predict correlations between splitting asymmetry, splitting amplitude, and pulsation frequency. We also discuss additional factors that can influence splitting asymmetry, including embedded magnetic fields, resonant mode coupling, and binarity.

astro-ph.SR↗

arXiv2024

FineDiffusion: Scaling up Diffusion Models for Fine-grained Image Generation with 10,000 Classes

The class-conditional image generation based on diffusion models is renowned for generating high-quality and diverse images. However, most prior efforts focus on generating images for general categories, e.g., 1000 classes in ImageNet-1k. A more challenging task, large-scale fine-grained image generation, remains the boundary to explore. In this work, we present a parameter-efficient strategy, called FineDiffusion, to fine-tune large pre-trained diffusion models scaling to large-scale fine-grained image generation with 10,000 categories. FineDiffusion significantly accelerates training and reduces storage overhead by only fine-tuning tiered class embedder, bias terms, and normalization layers' parameters. To further improve the image generation quality of fine-grained categories, we propose a novel sampling method for fine-grained image generation, which utilizes superclass-conditioned guidance, specifically tailored for fine-grained categories, to replace the conventional classifier-free guidance sampling. Compared to full fine-tuning, FineDiffusion achieves a remarkable 1.56x training speed-up and requires storing merely 1.77% of the total model parameters, while achieving state-of-the-art FID of 9.776 on image generation of 10,000 classes. Extensive qualitative and quantitative experiments demonstrate the superiority of our method compared to other parameter-efficient fine-tuning methods. The code and more generated results are available at our project website: https://finediffusion.github.io/.

cs.CV↗

arXiv2024

Mott insulating phase and coherent-incoherent crossover across magnetic phase transition in 2D antiferromagnetic CrSBr

In two-dimensional van der Waals magnetic materials, the interplay between magnetism and electron correlation can give rise to new ground states and lead to novel transport and optical properties. A fundamental question in these materials is how the electron correlation manifests and interacts with the magnetic orders. In this study, we demonstrate that the recently discovered 2D antiferromagnetic material, CrSBr, is a Mott insulator, through the combined use of resonant and temperature-dependent angle-resolved photoemission spectroscopy techiniques, supplemented by dynamical mean-field theory analysis. Intriguingly, we found that as the system transitions from the antiferromagnetic to the paramagnetic phases, its Mott bands undergo a reconfiguration, and a coherent-incoherent crossover, driven by the dissolution of the magnetic order. Our findings reveal a distinctive evolution of band structure associated with magnetic phase transitions, shedding light on the investigation of intricate interplay between correlation and magnetic orders in strongly correlated van der Waals magnetic materials.

cond-mat.str-el↗