arXiv subjects

Liang Li

Publications and source records attributed to Liang Li.

At least 163 records · Page 9Linked to original sources

arXiv2025

Sub-2 Kelvin characterization of nitrogen-vacancy centers in silicon carbide nanopillars

The development of efficient quantum communication technologies depends on the innovation in multiple layers of its implementation, a challenge we address from the fundamental properties of the physical system at the nano-scale to the instrumentation level at the macro-scale. We select a promising near infrared quantum emitter, the nitrogen-vacancy (NV) center in 4H-SiC, and integrate it, at an ensemble level, with nanopillar structures that enhance photon collection efficiency into an objective lens. Moreover, changes in collection efficiency in pillars compared to bulk can serve as indicators of color center orientation in the lattice. To characterize NV center properties at the unprecedented sub-2 Kelvin temperatures, we incorporate compatible superconducting nanowire single photon detectors inside the chamber of an optical cryostat and create the ICECAP, the Integrated Cryogenic system for Emission, Collection And Photon-detection. ICECAP measurements show no significant linewidth broadening of NV ensemble emission and up to 14-fold enhancement in collected emission. With additional filtering, we measure emitter lifetimes of NV centers in a basal ($hk$) and an axial ($kk$) orientation unveiling their cryogenic values of 2.2 ns and 2.8 ns.

quant-ph↗

arXiv2025

Elastic properties of Cu-6wt\%Ag alloy wires for pulsed magnets investigated by ultrasonic techniques

Conductor materials with good mechanical performance as well as high electrical- and thermal-conductivities are particularly important to break through the current bottle-neck limit ($\sim 100$ T) of pulsed magnets. Here we perform systematic studies on the elastic properties of the Cu-6wt\%Ag alloy wires, a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques - resonant ultrasound spectroscopy (RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu-6wt\%Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this chance to test the availability of our newly-built ultrasound pulse-echo facility at Wuhan National High Magnetic Field Center (WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu-6wt\%Ag alloy wire remains excellent without anomalous softening under extreme conditions, e.g., ultra-high magnetic field up to 50 T, nitrogen / helium cryogenic liquids.

cond-mat.mtrl-sci↗

arXiv2025

GRB 190114C: Fireball Energy Budget and Radiative Efficiency Revisited

The jet composition of gamma-ray bursts (GRBs), as well as how efficiently the jet converts its energy to radiation, are long-standing problems in GRB physics. Here, we reported a comprehensive temporal and spectral analysis of the TeV-emitting bright GRB 190114C. Its high fluence ($\sim$ 4.4$\times$10$^{-4}$ erg cm$^{-2}$) allows us to conduct the time-resolved spectral analysis in great detail and study their variations down to a very short time-scale ($\sim$0.1 s) while preserving a high significance. Its prompt emission consists of three well-separated pulses. The first two main pulses ($P_1$ and $P_2$) exhibit independently strong thermal components, starting from the third pulse ($P_3$) and extending to the entire afterglow, the spectra are all nonthermal, the synchrotron plus Compton upscattering model well interprets the observation. By combining the thermal ($P_1$ and $P_2$) and the nonthermal ($P_3$) observations based on two different scenarios (global and pulse properties) and following the method described in Zhang et al., we measure the fireball parameters and GRB radiative efficiency with little uncertainties for this GRB. A relevantly high GRB radiative efficiency is obtained based on both the global and pulse properties, suggesting that if GRBs are powered by fireballs, the efficiency can sometimes be high. More interestingly, though the observed parameters are individually different (e.g., the amount of mass loading $M$), the radiative efficiency obtained from $P_1$ ($η_γ=36.0\pm6.5\%$) and $P_2$ ($η_γ=41.1\pm1.9\%$) is roughly the same, which implies that the central engine of the same GRB has some common properties.

astro-ph.HE↗

arXiv2024

Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts

The composition and radiation mechanism of gamma-ray bursts (GRBs) within jets continue to be hotly debated. Investigating the joint polarimetric and spectral properties is crucial for understanding GRB composition and radiation mechanism. Various jet properties, such as ``kinetic-energy-dominated" (KED), ``Poynting-flux-dominated" (PFD), and ``hybrid-dominated" (HD) relativistic outflows, have been inferred from observed GRB spectra, with expectations of differing polarization levels among them. In this study, we analyzed a sample of 27 GRBs detected by the Gamma-ray Burst Monitor on board the NASA Fermi Gamma-ray Space Telescope, focusing on 26 bursts with significant polarization measurements. Our analysis revealed that 16 bursts (62\%) were predominantly associated with the ``PFD'' jet type, while 10 bursts (38\%) were classified as HD, implying that photosphere emission may also be a possible mechanism powering the high levels of polarization. Notably, no bursts were identified as KED-type. We found distinct polarization properties, with HD-type bursts exhibiting consistently higher polarization levels than PFD-type bursts. We proposed models incorporating ordered and random magnetic field configurations specific to hybrid jets.

astro-ph.HE↗

arXiv2024

High-purity valley-polarized currents induced by bichromatic optical fields in two-dimensional materials

Producing currents predominantly from a single valley, namely valley-polarized currents, at optical-cycle timescales is an important aspect of the petahertz valleytronics, yet it remains less developed. This work exhibits the feasibility of achieving this goal using bichromatic optical fields, which allow for the precise control of sub-cycle electron dynamics. The combined effect of the helical and asymmetric waveforms of the optical fields leads to highly asymmetric excitation at different valleys and displacement of the excited electrons concurrently, thereby inducing valley-polarized currents with high valley purity, on the sub-optical-cycle timescale. Inherently, the purity of the currents built up from the optical approach remains high even for materials with short decoherence time. Moreover, the direction of the currents can be precisely controlled by adjusting the relative phase of the bichromatic components. Our work offers a promising avenue for generating and modulating high-purity valley-polarized currents at the femtosecond timescale, facilitating the development of petahertz valleytronics.

physics.optics↗

arXiv2024

EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation

Recently, Text-to-Image (T2I) generation models have achieved significant advancements. Correspondingly, many automated metrics have emerged to evaluate the image-text alignment capabilities of generative models. However, the performance comparison among these automated metrics is limited by existing small datasets. Additionally, these datasets lack the capacity to assess the performance of automated metrics at a fine-grained level. In this study, we contribute an EvalMuse-40K benchmark, gathering 40K image-text pairs with fine-grained human annotations for image-text alignment-related tasks. In the construction process, we employ various strategies such as balanced prompt sampling and data re-annotation to ensure the diversity and reliability of our benchmark. This allows us to comprehensively evaluate the effectiveness of image-text alignment metrics for T2I models. Meanwhile, we introduce two new methods to evaluate the image-text alignment capabilities of T2I models: FGA-BLIP2 which involves end-to-end fine-tuning of a vision-language model to produce fine-grained image-text alignment scores and PN-VQA which adopts a novel positive-negative VQA manner in VQA models for zero-shot fine-grained evaluation. Both methods achieve impressive performance in image-text alignment evaluations. We also use our methods to rank current AIGC models, in which the results can serve as a reference source for future study and promote the development of T2I generation. The data and code will be made publicly available.

cs.CV↗

arXiv2024

Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning

Video has emerged as a favored multimedia format on the internet. To better gain video contents, a new topic HIREST is presented, including video retrieval, moment retrieval, moment segmentation, and step-captioning. The pioneering work chooses the pre-trained CLIP-based model for video retrieval, and leverages it as a feature extractor for other three challenging tasks solved in a multi-task learning paradigm. Nevertheless, this work struggles to learn the comprehensive cognition of user-preferred content, due to disregarding the hierarchies and association relations across modalities. In this paper, guided by the shallow-to-deep principle, we propose a query-centric audio-visual cognition (QUAG) network to construct a reliable multi-modal representation for moment retrieval, segmentation and step-captioning. Specifically, we first design the modality-synergistic perception to obtain rich audio-visual content, by modeling global contrastive alignment and local fine-grained interaction between visual and audio modalities. Then, we devise the query-centric cognition that uses the deep-level query to perform the temporal-channel filtration on the shallow-level audio-visual representation. This can cognize user-preferred content and thus attain a query-centric audio-visual representation for three tasks. Extensive experiments show QUAG achieves the SOTA results on HIREST. Further, we test QUAG on the query-based video summarization task and verify its good generalization.

cs.CV↗

arXiv2024

A Decade of Deep Learning: A Survey on The Magnificent Seven

Deep learning has fundamentally reshaped the landscape of artificial intelligence over the past decade, enabling remarkable achievements across diverse domains. At the heart of these developments lie multi-layered neural network architectures that excel at automatic feature extraction, leading to significant improvements in machine learning tasks. To demystify these advances and offer accessible guidance, we present a comprehensive overview of the most influential deep learning algorithms selected through a broad-based survey of the field. Our discussion centers on pivotal architectures, including Residual Networks, Transformers, Generative Adversarial Networks, Variational Autoencoders, Graph Neural Networks, Contrastive Language-Image Pre-training, and Diffusion models. We detail their historical context, highlight their mathematical foundations and algorithmic principles, and examine subsequent variants, extensions, and practical considerations such as training methodologies, normalization techniques, and learning rate schedules. Beyond historical and technical insights, we also address their applications, challenges, and potential research directions. This survey aims to serve as a practical manual for both newcomers seeking an entry point into cutting-edge deep learning methods and experienced researchers transitioning into this rapidly evolving domain.

cs.LG↗

arXiv2024

A Novel Method of Estimating GRB Peak Energies Beyond the \emph{Swift}/BAT Limit

The \emph{Swift} Burst Alert Telescope (BAT), operating in the 15--150 keV energy band, struggles to detect the peak energy ($E_{\rm p}$) of gamma-ray bursts (GRBs), as most GRBs have $E_{\rm p}$ values typically distributed between 200-300 keV, exceeding BAT's upper limit. To address this, we develop an innovative method to robustly estimate the lower limit of $E_{\rm p}$ for GRBs with $E_{\rm p}>150$ keV. This approach relies on the intrinsic curvature of GRB spectra, which is already evident within the BAT energy range for such GRBs. By fitting BAT spectra with a cutoff power-law model and extrapolating the spectral curvature beyond BAT's range, we, therefore, can estimate the cutoff energy ($E^{'}_{\rm c}$) beyond 150 keV and the corresponding peak energy ($E^{'}_{\rm p}$). We applied this method to 17 GRBs, categorizing them into two main groups. Group I (10 bursts) maintains $α$ within a typical range (from $\sim$ -0.8 to $\sim$ -1.20) with increasing $E_{\rm c}$; Group II (2 bursts) maintains $E_{\rm c}$ within a typical range (300-500 keV) but with varying $α$. Our results show that for $E_{\rm c}\lesssim $1000 keV, the estimated $E^{'}_{\rm c}$ aligns well with observed values. Moreover, the reliability of $E^{'}_{\rm c}$ also depends on $α$: bursts with harder $α$ (e.g., $α\gtrsim -2/3$) show reduced accuracy, while bursts with softer $α$ (e.g., $α\lesssim -2/3$) yield more precise estimates. In conclusion, this method is well-suited for GRB spectra with moderately observed $E_{\rm c}$ ($E_{\rm p}$) values and $α$ indices that are not too hard.

astro-ph.HE↗

arXiv2024

DarkSHINE Baseline Design Report: Physics Prospects and Detector Technologies

DarkSHINE is a newly proposed fixed-target experiment initiative to search for the invisible decay of Dark Photon via missing energy/momentum signatures, based on the high repetition rate electron beam to be deployed/delivered by the Shanghai High repetition rate XFEL and Extreme light facility (SHINE). This report elaborates the baseline design of DarkSHINE experiment by introducing the physics goals, experimental setups, details of each sub-detector system technical designs, signal and backgground modelings, expected search sensitivities and future prospects, which mark an important step towards the further prototyping and technical demonstrations.

physics.ins-det↗

arXiv2024

On the wave equation with Coulomb potential

Wave/Schrödinger equations with potentials naturally originates from both the quantum physics and the study of nonlinear equations. The distractive Coulomb potential is a quantum mechanical description of distractive Coulomb force between two particles with the same charge. The spectrum of the operator $-Δ+1/|x|$ is well known and there are also a few results on the Strichartz estimates, local and global well-posedness and scattering result about the nonlinear Schrödinger equation with a distractive Coulomb potential. In the contrast, much less is known for the global and asymptotic behaviour of solutions to the corresponding wave equations with a Coulomb potential. In this work we consider the wave equation with a distractive Coulomb potential in dimensions $d\geq 3$. We first describe the asymptotic behaviour of the solutions to the linear homogeneous Coulomb wave equation, especially their energy distribution property and scattering profiles, then show that the radial finite-energy solutions to suitable defocusing Coulomb wave equation are defined for all time and scatter in both two time directions, by establishing a family of radial Strichartz estimates and combining them with the decay of the potential energy.

math.AP↗

arXiv2024

Multi-robot autonomous 3D reconstruction using Gaussian splatting with Semantic guidance

Implicit neural representations and 3D Gaussian splatting (3DGS) have shown great potential for scene reconstruction. Recent studies have expanded their applications in autonomous reconstruction through task assignment methods. However, these methods are mainly limited to single robot, and rapid reconstruction of large-scale scenes remains challenging. Additionally, task-driven planning based on surface uncertainty is prone to being trapped in local optima. To this end, we propose the first 3DGS-based centralized multi-robot autonomous 3D reconstruction framework. To further reduce time cost of task generation and improve reconstruction quality, we integrate online open-vocabulary semantic segmentation with surface uncertainty of 3DGS, focusing view sampling on regions with high instance uncertainty. Finally, we develop a multi-robot collaboration strategy with mode and task assignments improving reconstruction quality while ensuring planning efficiency. Our method demonstrates the highest reconstruction quality among all planning methods and superior planning efficiency compared to existing multi-robot methods. We deploy our method on multiple robots, and results show that it can effectively plan view paths and reconstruct scenes with high quality.

cs.RO↗

arXiv2024

Impact of tensor forces on quasifission product yield distributions

We employ the microscopic time-dependent Hartree-Fock (TDHF) theory to study the 48Ca+249Bk and 48Ti+238U systems, taking into account the dependence on orientation for deformed nuclei and full range of impact parameters. By analyzing fragment distributions of neutron and proton numbers, we assess the influence of different isoscalar and isovector tensor coupling constants of the effective nucleon-nucleon interaction. The quasifission yield distributions of 48Ca + 249Bk collision system utilizing SLy5t and T31 parametrizations exhibit more pronounced spherical shell effects compared to those using SLy5, T44 and T62 sets. Furthermore, within each parametrization group, the distributions for SLy5t and T31 are closely aligned, as are those for SLy5, T44, and T62. Similarly, the yield distributions for the 48Ti + 238U system using SLy5t and T31 also reflect the more pronounced spherical shell effects relative to SLy5 and T62, while the charge distribution shows much better agreement with experimental results for the SLy5t and T62 parametrizations compared to SLy5 and T31. The yield distributions for the 48Ca+249Bk and 48Ti+238U systems, when compared across the SLy5, SLy5t, T31, T44, and T62 parametrizations, indicate that the influence of tensor forces on quasifission fragments is reflected in the prominence of shell effects. This influence appears to be sensitive only in specific regions within the isoscalar and isovector coupling constant parameter space. In the 48Ti + 238U system, the prominence of shell effects is manifested not only through shifts in peak positions but also through narrower yield distributions.

nucl-th↗

arXiv2024

Resurfaced CsPbBr3 Nanocrystals Enable Free Radical Thermal Polymerization of Efficient Ultrafast Polyvinyl Styrene Nanocomposite Scintillators

Lead halide perovskite nanocrystals (LHP-NCs) embedded in a plastic matrix are highly promising for a variety of photonic technologies and are quickly gaining attention as ultrafast, radiation-resistant nanoscintillators for radiation detection. However, advancements in LHP-NC-based photonics are hindered by their well-known thermal instability, which makes them unsuitable for industrial thermally activated mass polymerization processes - crucial for creating polystyrene-based scintillating nanocomposites. In this study, we address this challenge by presenting the first thermal nanocomposite scintillators made from CsPbBr3 NCs passivated with fluorinated ligands that remain attached to the particles surfaces even at high temperatures, enabling their integration into mass-cured polyvinyl toluene without compromising optical properties. Consequently, these nanocomposites demonstrate scintillation light yields reaching 10,400 photons/MeV, sub-nanosecond scintillation kinetics, and remarkable radiation resilience, able to withstand gamma radiation doses of up to 1 MGy. This performance not only meets but also exceeds the scintillation of plastic scintillators, despite the radiation-induced damage to the host matrix.

physics.optics↗

arXiv2024

Chanel-Orderer: A Channel-Ordering Predictor for Tri-Channel Natural Images

This paper shows a proof-of-concept that, given a typical 3-channel images but in a randomly permuted channel order, a model (termed as Chanel-Orderer) with ad-hoc inductive biases in terms of both architecture and loss functions can accurately predict the channel ordering and knows how to make it right. Specifically, Chanel-Orderer learns to score each of the three channels with the priors of object semantics and uses the resulting scores to predict the channel ordering. This brings up benefits into a typical scenario where an \texttt{RGB} image is often mis-displayed in the \texttt{BGR} format and needs to be corrected into the right order. Furthermore, as a byproduct, the resulting model Chanel-Orderer is able to tell whether a given image is a near-gray-scale image (near-monochromatic) or not (polychromatic). Our research suggests that Chanel-Orderer mimics human visual coloring of our physical natural world.

cs.CV↗

arXiv2024

Design of a LYSO Crystal Electromagnetic Calorimeter for DarkSHINE Experiment

This paper presents the design and optimization of a LYSO crystal electromagnetic calorimeter (ECAL) for the DarkSHINE experiment, which aims to search for dark photons as potential mediators of dark forces. The ECAL design was evaluated through comprehensive simulations, focusing on optimizing dimensions, material selection, energy distribution, and energy resolution. The ECAL configuration consists of 21$\times$21$\times$11 LYSO crystals, each measuring 2.5$\times$2.5$\times$4 cm$^3$, arranged in a staggered layout to improve signal detection efficiency. A 4 GeV energy dynamic range was established to ensure accurate energy measurements without saturation, which is essential for background rejection and signal identification. A detailed digitization model was developed to simulate the scintillation, SiPM, and ADC behaviors, providing a more realistic representation of detector performance. Additionally, the study assessed radiation damage in the ECAL region, highlighting the necessity of radiation-resistant scintillators and silicon sensors.

physics.ins-det↗

arXiv2024

A Consistency-Aware Spot-Guided Transformer for Versatile and Hierarchical Point Cloud Registration

Deep learning-based feature matching has shown great superiority for point cloud registration in the absence of pose priors. Although coarse-to-fine matching approaches are prevalent, the coarse matching of existing methods is typically sparse and loose without consideration of geometric consistency, which makes the subsequent fine matching rely on ineffective optimal transport and hypothesis-and-selection methods for consistency. Therefore, these methods are neither efficient nor scalable for real-time applications such as odometry in robotics. To address these issues, we design a consistency-aware spot-guided Transformer (CAST), which incorporates a spot-guided cross-attention module to avoid interfering with irrelevant areas, and a consistency-aware self-attention module to enhance matching capabilities with geometrically consistent correspondences. Furthermore, a lightweight fine matching module for both sparse keypoints and dense features can estimate the transformation accurately. Extensive experiments on both outdoor LiDAR point cloud datasets and indoor RGBD point cloud datasets demonstrate that our method achieves state-of-the-art accuracy, efficiency, and robustness.

cs.CV↗

arXiv2024

CalliffusionV2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control

In this paper, we introduce CalliffusionV2, a novel system designed to produce natural Chinese calligraphy with flexible multi-modal control. Unlike previous approaches that rely solely on image or text inputs and lack fine-grained control, our system leverages both images to guide generations at fine-grained levels and natural language texts to describe the features of generations. CalliffusionV2 excels at creating a broad range of characters and can quickly learn new styles through a few-shot learning approach. It is also capable of generating non-Chinese characters without prior training. Comprehensive tests confirm that our system produces calligraphy that is both stylistically accurate and recognizable by neural network classifiers and human evaluators.

cs.CL↗