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Ying Li

Publications and source records attributed to Ying Li.

At least 289 records · Page 16Linked to original sources

Online/Offline Learning to Enable Robust Beamforming: Limited Feedback Meets Deep Generative Models

Robust beamforming is a pivotal technique in massive multiple-input multiple-output (MIMO) systems as it mitigates interference among user equipment (UE). One current risk-neutral approach to robust beamforming is the stochastic weighted minimum mean square error method (WMMSE). However, this method necessitates statistical channel information, which is typically inaccessible, particularly in fifth-generation new radio frequency division duplex cellular systems with limited feedback. To tackle this challenge, we propose a novel approach that leverages a channel variational auto-encoder (CVAE) to simulate channel behaviors using limited feedback, eliminating the need for specific distribution assumptions present in existing methods. To seamlessly integrate model learning into practical wireless communication systems, this paper introduces two learning strategies to prepare the CVAE model for practical deployment. Firstly, motivated by the digital twin technology, we advocate employing a high-performance channel simulator to generate training data, enabling pretraining of the proposed CVAE while ensuring non-disruption to the practical wireless communication system. Moreover, we present an alternative online method for CVAE learning, where online training data is sourced based on channel estimations using Type II codebook. Numerical results demonstrate the effectiveness of these strategies, highlighting their exceptional performance in channel generation and robust beamforming applications.

stat.AP↗

Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution

Artifact-free super-resolution (SR) aims to translate low-resolution images into their high-resolution counterparts with a strict integrity of the original content, eliminating any distortions or synthetic details. While traditional diffusion-based SR techniques have demonstrated remarkable abilities to enhance image detail, they are prone to artifact introduction during iterative procedures. Such artifacts, ranging from trivial noise to unauthentic textures, deviate from the true structure of the source image, thus challenging the integrity of the super-resolution process. In this work, we propose Self-Adaptive Reality-Guided Diffusion (SARGD), a training-free method that delves into the latent space to effectively identify and mitigate the propagation of artifacts. Our SARGD begins by using an artifact detector to identify implausible pixels, creating a binary mask that highlights artifacts. Following this, the Reality Guidance Refinement (RGR) process refines artifacts by integrating this mask with realistic latent representations, improving alignment with the original image. Nonetheless, initial realistic-latent representations from lower-quality images result in over-smoothing in the final output. To address this, we introduce a Self-Adaptive Guidance (SAG) mechanism. It dynamically computes a reality score, enhancing the sharpness of the realistic latent. These alternating mechanisms collectively achieve artifact-free super-resolution. Extensive experiments demonstrate the superiority of our method, delivering detailed artifact-free high-resolution images while reducing sampling steps by 2X. We release our code at https://github.com/ProAirVerse/Self-Adaptive-Guidance-Diffusion.git.

eess.IV↗

TARN-VIST: Topic Aware Reinforcement Network for Visual Storytelling

As a cross-modal task, visual storytelling aims to generate a story for an ordered image sequence automatically. Different from the image captioning task, visual storytelling requires not only modeling the relationships between objects in the image but also mining the connections between adjacent images. Recent approaches primarily utilize either end-to-end frameworks or multi-stage frameworks to generate relevant stories, but they usually overlook latent topic information. In this paper, in order to generate a more coherent and relevant story, we propose a novel method, Topic Aware Reinforcement Network for VIsual StoryTelling (TARN-VIST). In particular, we pre-extracted the topic information of stories from both visual and linguistic perspectives. Then we apply two topic-consistent reinforcement learning rewards to identify the discrepancy between the generated story and the human-labeled story so as to refine the whole generation process. Extensive experimental results on the VIST dataset and human evaluation demonstrate that our proposed model outperforms most of the competitive models across multiple evaluation metrics.

cs.CV↗

Optical wood with switchable solar transmittance for all-round thermal management

Technologies enabling passive daytime radiative cooling and daylight harvesting are highly relevant for energy-efficient buildings. Despite recent progress demonstrated with passively cooling polymer coatings, however, it remains challenging to combine also a passive heat gain mechanism into a single substrate for all-round thermal management. Herein, we developed an optical wood (OW) with switchable transmittance of solar irradiation enabled by the hierarchically porous structure, ultralow absorption in solar spectrum and high infrared absorption of cellulose nanofibers. After delignification, the OW shows a high solar reflectance (94.9%) in the visible and high broadband emissivity (0.93) in the infrared region (2.5-25 $μ$m). Owing to the exceptional mass transport of its aligned cellulose nanofibers, OW can quickly switch to a new highly transparent state following phenylethanol impregnation. The solar transmittance of optical wood (OW-II state) can reach 68.4% from 250 to 2500 nm. The switchable OW exhibits efficient radiative cooling to 4.5 °C below ambient temperature in summer (81.4 W m$^{-2}$ cooling power), and daylight heating to 5.6 °C above the temperature of natural wood in winter (heating power 229.5 W m$^{-2}$), suggesting its promising role as a low-cost and sustainable solution to all-season thermal management applications.

physics.optics↗

Federated Domain Generalization: A Survey

Machine learning typically relies on the assumption that training and testing distributions are identical and that data is centrally stored for training and testing. However, in real-world scenarios, distributions may differ significantly and data is often distributed across different devices, organizations, or edge nodes. Consequently, it is imperative to develop models that can effectively generalize to unseen distributions where data is distributed across different domains. In response to this challenge, there has been a surge of interest in federated domain generalization (FDG) in recent years. FDG combines the strengths of federated learning (FL) and domain generalization (DG) techniques to enable multiple source domains to collaboratively learn a model capable of directly generalizing to unseen domains while preserving data privacy. However, generalizing the federated model under domain shifts is a technically challenging problem that has received scant attention in the research area so far. This paper presents the first survey of recent advances in this area. Initially, we discuss the development process from traditional machine learning to domain adaptation and domain generalization, leading to FDG as well as provide the corresponding formal definition. Then, we categorize recent methodologies into four classes: federated domain alignment, data manipulation, learning strategies, and aggregation optimization, and present suitable algorithms in detail for each category. Next, we introduce commonly used datasets, applications, evaluations, and benchmarks. Finally, we conclude this survey by providing some potential research topics for the future.

cs.LG↗

Surveying the Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese

In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese. Humans have produced texts in various languages for thousands of years; however, most of the computational literature is focused on contemporary languages and corpora. The emerging field of historical psychology relies on computational techniques to extract aspects of psychology from historical corpora using new methods developed in natural language processing (NLP). The present pipeline, called Contextualized Construct Representations (CCR), combines expert knowledge in psychometrics (i.e., psychological surveys) with text representations generated via transformer-based language models to measure psychological constructs such as traditionalism, norm strength, and collectivism in classical Chinese corpora. Considering the scarcity of available data, we propose an indirect supervised contrastive learning approach and build the first Chinese historical psychology corpus (C-HI-PSY) to fine-tune pre-trained models. We evaluate the pipeline to demonstrate its superior performance compared with other approaches. The CCR method outperforms word-embedding-based approaches across all of our tasks and exceeds prompting with GPT-4 in most tasks. Finally, we benchmark the pipeline against objective, external data to further verify its validity.

cs.CL↗

The $B^0 \to J/ψf_0(1370,1500,1710)$ decays: an opportunity for scalar glueball hunting

The scalars $f_0$ closest to 1.5 GeV contain the mesons $f_0(1370)$, $f_0(1500)$ and $f_0(1710)$, and the latter two ones are usually viewed as the potential candidates for the scalar glueballs. In this work, by including the important contributions from the vertex corrections, we study the decays $B^0 \to J/ψf_0$ within the improved perturbative QCD approach and analyze the possible scalar glueball hunting. Together with the two mixing models, namely, $f_0(1500) (f_0(1710))$ being the primary scalar glueball in model I (II), and two classification scenarios, namely, $f_0$ being the $q\bar q$ excited (ground) states in scenario 1 (2), the branching fractions associated with their ratios for $B^0 \to J/ψf_0$ are evaluated comprehensively. The predictions with still large uncertainties in the considered two mixing models are roughly consistent with currently limited data, which indicates that both more rich data and more precise predictions are urgently demanded to figure out the scalar glueball clearly in the future. Moreover, several interesting ratios between the branching fractions of $B^0 \to J/ψf_0(\to π^+ π^-/K^+ K^-)$ and $B^0 \to J/ψρ^0/ϕ(\to π^+ π^-/ K^+ K^-)$ that could help us to understand the nature of scalar $f_0$ are defined and predicted theoretically. These ratios should be examined in future experiments.

hep-ph↗

CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models

Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models such as Codex, CodeGen, and PanGu-Coder. To evaluate the effectiveness of these models, multiple existing benchmarks are proposed, including only cases of generating a standalone function, i.e., a function that may invoke or access only built-in functions and standard libraries. However, non-standalone functions, which typically are not included in the existing benchmarks, constitute more than 70% of the functions in popular open-source projects, and evaluating models' effectiveness on standalone functions cannot reflect these models' effectiveness on pragmatic code generation scenarios. To help bridge the preceding gap, in this paper, we propose a benchmark named CoderEval, consisting of 230 Python and 230 Java code generation tasks carefully curated from popular real-world open-source projects and a self-contained execution platform to automatically assess the functional correctness of generated code. CoderEval supports code generation tasks from six levels of context dependency, where context refers to code elements such as types, APIs, variables, and consts defined outside the function under generation but within the dependent third-party libraries, current class, file, or project. CoderEval can be used to evaluate the effectiveness of models in generating code beyond only standalone functions. By evaluating three code generation models on CoderEval, we find that the effectiveness of these models in generating standalone functions is substantially higher than that in generating non-standalone functions. Our analysis highlights the current progress and pinpoints future directions to further improve a model's effectiveness by leveraging contextual information for pragmatic code generation.

cs.SE↗

Study of $B_s \to ϕ(ρ^0, ω)$ Decays in Standard Model and Family Non-universal $Z^\prime$ Model

Within QCD factorization approach, we employ the new results of form factors of $B_s \to ϕ$ and calculate the branching fractions, CP asymmetries (CPAs) and polarization fractions of the decay modes $B_s \to ϕ(ρ^0, ω)$ in both the standard model (SM) and the family non-universal $Z^\prime$ model. We find that in SM the above observables are relate to two parameters $ρ_H$ and $ϕ_H$, which characterize the end-point divergence in the hard spectator-scattering amplitudes. When setting $ρ_H=0.5$ and $ϕ_H\in [-180,180]^\circ$, the theoretical uncertainties are large. By combining the experimental data, our results can be used to constrain these two parameters. Supposing $ρ_H=0$, we study the effects of $Z^\prime$ boson on the concerned observables. With the available branching fraction of $B_s \to ϕρ^0$, the possible ranges of parameter spaces are obtained. Within the allowed parameter spaces, the branching fraction of $B_s \to ϕω$ can be enlarged remarkably. Furthermore, the new introduced weak phase plays important roles in significantly affecting the CPAs and polarization fractions, which are important observables for probing the effects of NP. If these decay modes were measured in the on-going LHC-b and Belle-II experiments in future, the peculiar deviation from SM could provide a signal of the family non-universal $Z^\prime$ model, which can also be used to constrain the mass of $Z^\prime$ boson in turn.

hep-ph↗

Leveraging junk information to enhance the quantum error mitigation

Noise in quantum information processing poses a significant obstacle to achieving precise results. Quantum error mitigation techniques are crucial for improving the accuracy of experimental expectation values in this process. In the experiments, it is commonly observed that some measured events violate certain principles, such as symmetry constraints. These events can be considered junk information and should be discarded in a post-selection process. In this work, we introduce a quantum error mitigation method named Self-Trained Quantum Noise Filter (SQNF), which leverages the junk information to differentiate errors from the experimental population distributions, thereby aiming to approximate the error-free distribution. Our numerical results demonstrate that the proposed method can significantly reduce the infidelity of population distributions compared to the traditional post-selection method. Notably, the infidelity reduction is achieved without additional experimental resource consumption. Our method is scalable and applicable to multi-qubit computing systems.

quant-ph↗

The White-light Emissions in Two X-class Flares Observed by ASO-S and CHASE

The white-light continuum emissions in solar flares (i.e., white-light flares) are usually observed on the solar disk but, in a few cases, off the limb. Here we present on-disk as well as off-limb continuum emissions at 3600 Å (in the Balmer continuum) in an X2.1 flare (SOL2023-03-03T17:52) and an X1.5 flare (SOL2023-08-07T20:46), respectively, observed by the White-light Solar Telescope (WST) on the Advanced Space-based Solar Observatory (ASO-S). These continuum emissions are seen at the ribbons for the X2.1 flare and on loops during the X1.5 event, in which the latter also appears in the decay phase. These emissions also show up in the pseudo-continuum images at Fe I λ6173 from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO). In addition, the ribbon sources in the X2.1 flare exhibit significant enhancements in the Fe I line at 6569.2 Å and the nearby continuum observed by the Chinese Hα Solar Explorer (CHASE). It is found that the on-disk continuum emissions in the X2.1 flare are related to a nonthermal electron-beam heating either directly or indirectly, while the off-limb emissions in the X1.5 flare are associated with thermal plasma cooling or due to Thomson scattering. These comprehensive continuum observations can provide good constraints on flare energy deposition models, which helps well understand the physical mechanism of white-light flares.

astro-ph.SR↗

The Metallicity Distribution in the LMC and the SMC based on the Tip-RGB Colors

The color index $(J-K)_0$ of tip-red giant branch (TRGB) is used to study the metallicity distribution in the Large and Small Magellanic Cloud. With the most complete and pure sample of red member stars so far, the areas are divided into 154 and 70 bins for the LMC and SMC respectively with similar number of stars by the Voronoi binning. For each bin, the position of TRGB on the near-infrared color-magnitude diagram, specifically $(J-K)_0/K_0$, is determined by the Poison-Noise weighted method. Converting the color index of TRGB into metallicity, the metallicity gradients in the LMC and the SMC are obtained in four major directions. For the LMC, the gradient to the north is $-0.006 \pm 0.004$ dex kpc$^{-1}$, to the south $-0.010 \pm 0.005$ dex kpc$^{-1}$, to the east $-0.006 \pm 0.003$ dex kpc$^{-1}$, and to the west $-0.010 \pm 0.003$ dex kpc$^{-1}$. The farthest distance extends to 16 kpc. For the SMC, the gradients to the north, south, east, and west are $-0.017 \pm 0.031$ dex kpc$^{-1}$, $-0.016 \pm 0.007$ dex kpc$^{-1}$, $-0.003 \pm 0.002$ dex kpc$^{-1}$, and $-0.004 \pm 0.003$ dex kpc$^{-1}$, respectively. The farthest distance for the SMC extends to 27 kpc. The gradient is large from the center to 1 kpc.

astro-ph.GA↗

Chiral and non-chiral swift mode conversion near an exception point with dynamic adiabaticity engineering

The eigenvalue of a non-Hermitian Hamiltonian often forms a self-intersecting Riemann surface, leading to a unique mode conversion phenomenon when the Hamiltonian evolves along certain loop paths around an exceptional point (EP). However, two fundamental problems exist with the conventional scheme of EP encircling: the speed of mode conversion is restricted by the adiabatic requirement, and the chirality cannot be freely controlled. Here, we introduce a method which dynamically engineers the adiabaticity in the evolution of non-Hermitian Hamiltonians that allows for both chiral and non-chiral mode conversion on the same path. Our method is based on quantifying and controlling the instantaneous adiabaticity, allowing for non-uniform evolution throughout the entire path. We apply our method into the microwave waveguide system and by optimizing the distributed adiabaticity along the evolution loop, we achieve the same quality of mode conversion as conventional quasi-adiabatic evolution in only one-fourth of the time. Our approach provides a comprehensive and universal solution to address the speed and chirality challenges associated with EP encircling. It also facilitates the dynamic manipulation and regulation of non-adiabatic processes, thereby accelerating the operation and allowing for a selection among various mode conversion patterns.

quant-ph↗

Shadow-based quantum subspace algorithm for the nuclear shell model

In recent years, researchers have been exploring the applications of noisy intermediate-scale quantum (NISQ) computation in various fields. One important area in which quantum computation can outperform classical computers is the ground state problem of a many-body system, e.g., the nucleus. However, using a quantum computer in the NISQ era to solve a meaningful-scale system remains a challenge. To calculate the ground energy of nuclear systems, we propose a new algorithm that combines classical shadow and subspace diagonalization techniques. Our subspace is composed of matrices, with the basis of the subspace being the classical shadow of the quantum state. We test our algorithm on nuclei described by Cohen-Kurath shell model and USD shell model. We find that the accuracy of the results improves as the number of shots increases, following the Heisenberg scaling.

quant-ph↗

A Statistical Study of Solar White-Light Flares Observed by the White-light Solar Telescope of the Lyman-alpha Solar Telescope on the Advanced Space-based Solar Observatory (ASO-S/LST/WST) at 360 nm

Solar white-light flares (WLFs) are those accompanied by brightenings in the optical continuum or integrated light. The White-light Solar Telescope (WST), as an instrument of the Lyman-alpha Solar Telescope (LST) on the Advanced Space-based Solar Observatory (ASO-S), provides continuous solar full-disk images at 360 nm, which can be used to study WLFs. We analyze 205 major flares above M1.0 from October 2022 to May 2023 and identify 49 WLFs at 360 nm from WST observations, i.e. with an occurrence rate of 23.9%. The percentages of WLFs for M1 - M4 (31 out of 180), M5 - M9 (11 out of 18), and above X1 (7 for all) flares are 17.2%, 61.1%, and 100%, respectively, namely the larger the flares, the more likely they are WLFs at 360 nm. We further analyze 39 WLFs among the identified WLFs and investigate their properties such as white-light enhancement, duration, and brightening area. It is found that the relative enhancement of the white-light emission at 360 nm is mostly (>90%) less than 30% and the mean enhancement is 19.4%. The WLFs' duration at 360 nm is mostly (>80%) less than 20 minutes and its mean is 10.3 minutes. The brightening area at 360 nm is mostly (>75%) less than 500 arcsecond2 and the median value is 225. We find that there exist good correlations between the white-light enhancement/duration/area and the peak soft X-ray (SXR) flux of the flare, with correlation coefficients of 0.68, 0.58, and 0.80, respectively. In addition, the white-light emission in most WLFs peaks around the same time as the temporal derivative of SXR flux as well as the hard X-ray emission at 20 - 50 keV, indicative of Neupert effect. It is also found that the limb WLFs are more likely to have a greater enhancement, which is consistent with numerical simulations.

astro-ph.SR↗

Reconfigurable Three-Dimensional Thermal Dome

Thermal metamaterial represents a groundbreaking approach to control heat conduction, and, as a crucial component, thermal invisibility is of utmost importance for heat management. Despite the flourishing development of thermal invisibility schemes, they still face two limitations in practical applications. First, objects are typically completely enclosed in traditional cloaks, making them difficult to use and unsuitable for objects with heat sources. Second, although some theoretical proposals have been put forth to change the thermal conductivity of materials to achieve dynamic invisibility, their designs are complex and rigid, making them unsuitable for large-scale use in real three-dimensional spaces. Here, we propose a concept of a thermal dome to achieve three-dimensional invisibility. Our scheme includes an open functional area, greatly enhancing its usability and applicability. It features a reconfigurable structure, constructed with simple isotropic natural materials, making it suitable for dynamic requirements. The performance of our reconfigurable thermal dome has been confirmed through simulations and experiments, consistent with the theory. The introduction of this concept can greatly advance the development of thermal invisibility technology from theory to engineering and provide inspiration for other physical domains, such as direct current electric fields and magnetic fields.

physics.app-ph↗

Quantum Error Mitigation

For quantum computers to successfully solve real-world problems, it is necessary to tackle the challenge of noise: the errors which occur in elementary physical components due to unwanted or imperfect interactions. The theory of quantum fault tolerance can provide an answer in the long term, but in the coming era of `NISQ' machines we must seek to mitigate errors rather than completely remove them. This review surveys the diverse methods that have been proposed for quantum error mitigation, assesses their in-principle efficacy, and then describes the hardware demonstrations achieved to date. We identify the commonalities and limitations among the methods, noting how mitigation methods can be chosen according to the primary type of noise present, including algorithmic errors. Open problems in the field are identified and we discuss the prospects for realising mitigation-based devices that can deliver quantum advantage with an impact on science and business.

quant-ph↗

TI-DNS: A Trusted and Incentive DNS Resolution Architecture based on Blockchain

Domain Name System (DNS) is a critical component of the Internet infrastructure, responsible for translating domain names into IP addresses. However, DNS is vulnerable to some malicious attacks, including DNS cache poisoning, which redirects users to malicious websites displaying offensive or illegal content. Existing countermeasures often suffer from at least one of the following weakness: weak attack resistance, high overhead, or complex implementation. To address these challenges, this paper presents TI-DNS, a blockchain-based DNS resolution architecture designed to detect and correct the forged DNS records caused by the cache poisoning attacks in the DNS resolution process. TI-DNS leverages a multi-resolver Query Vote mechanism to ensure the credibility of verified records on the blockchain ledger and a stake-based incentive mechanism to promote well-behaved participation. Importantly, TI-DNS is easy to be adopted as it only requires modifications to the resolver side of current DNS infrastructure. Finally, we develop a prototype and evaluate it against alternative solutions. The result demonstrates that TI-DNS effectively and efficiently solves DNS cache poisoning.

cs.CR↗