Search arXiv⌕ Search

arXiv subjects

Gang Li

Publications and source records attributed to Gang Li.

At least 289 records · Page 16Linked to original sources

Rich Human Feedback for Text-to-Image Generation

Recent Text-to-Image (T2I) generation models such as Stable Diffusion and Imagen have made significant progress in generating high-resolution images based on text descriptions. However, many generated images still suffer from issues such as artifacts/implausibility, misalignment with text descriptions, and low aesthetic quality. Inspired by the success of Reinforcement Learning with Human Feedback (RLHF) for large language models, prior works collected human-provided scores as feedback on generated images and trained a reward model to improve the T2I generation. In this paper, we enrich the feedback signal by (i) marking image regions that are implausible or misaligned with the text, and (ii) annotating which words in the text prompt are misrepresented or missing on the image. We collect such rich human feedback on 18K generated images (RichHF-18K) and train a multimodal transformer to predict the rich feedback automatically. We show that the predicted rich human feedback can be leveraged to improve image generation, for example, by selecting high-quality training data to finetune and improve the generative models, or by creating masks with predicted heatmaps to inpaint the problematic regions. Notably, the improvements generalize to models (Muse) beyond those used to generate the images on which human feedback data were collected (Stable Diffusion variants). The RichHF-18K data set will be released in our GitHub repository: https://github.com/google-research/google-research/tree/master/richhf_18k.

cs.CV↗

The Physics potential of the CEPC. Prepared for the US Snowmass Community Planning Exercise (Snowmass 2021)

The Circular Electron Positron Collider (CEPC) is a large-scale collider facility that can serve as a factory of the Higgs, Z, and W bosons and is upgradable to run at the ttbar threshold. This document describes the latest CEPC nominal operation scenario and particle yields and updates the corresponding physics potential. A new detector concept is also briefly described. This submission is for consideration by the Snowmass process.

hep-ph↗

Terraced Compression Method with Automated Threshold Selection for Multidimensional Image Clustering of Heterogeneous Bodies

Multispectral transmission imaging provides strong benefits for early breast cancer screening. The frame accumulation method addresses the challenge of low grayscale and signal-to-noise ratio resulting from the strong absorption and scattering of light by breast tissue. This method introduces redundancy in data while improving the grayscale and signal-to-noise ratio of the image. Existing terraced compression algorithms effectively eliminate the data redundancy introduced by frame accumulation but necessitate significant time for manual debugging of threshold values. Hence, this paper proposes an improved terrace compression algorithm. The algorithm necessitates solely the input of the desired heterogeneous body size and autonomously calculates the optimal area threshold and gradient threshold by counting the grayscale and combining its distribution. Experimental acquisition involved multi-wavelength images of heterogeneous bodies exhibiting diverse textures, depths, and thicknesses. Subsequently, the method was applied after pre-processing to determine the thresholds for terraced compression at each wavelength, coupled with a window function for multi-dimensional image clustering. The results illustrate the method's efficacy in detecting and identifying various heterogeneous body types, depths, and thicknesses. This approach is expected to accurately identify the locations and types of breast tumors in the future, thus providing a more dependable tool for early breast cancer screening.

eess.IV↗

CME Deflection and East-West Asymmetry of ESP Intensity in Solar Cycles 23 and 24

We investigate the East-West asymmetry in energetic storm particle (ESP) heavy ion intensities at interplanetary shocks driven by coronal mass ejections (CMEs) during solar cycles (SCs) 23 and 24. We use observations from NASA's ACE and STEREO missions of helium (He), oxygen (O), and iron (Fe) intensities from ~0.13 to 3 MeV/nucleon. We examine the longitudinal distribution of ESP intensities and the correlation of ESP intensities with the near-Sun CME speed and the average transit CME speed for eastern and western events. We observed an East-West asymmetry reversal of ESP heavy ion intensities from SC 23 to 24. We have determined that this change in asymmetry is caused by a shift in the heliolongitude distribution of the CME speed ratio (the ratio of CME near-Sun speed to CME average transit speed) from west to east.

astro-ph.SR↗

Beam test of a baseline vertex detector prototype for CEPC

The Circular Electron Positron Collider (CEPC) has been proposed to enable more thorough and precise measurements of the properties of Higgs, W, and Z bosons, as well as to search for new physics. In response to the stringent performance requirements of the vertex detector for the CEPC, a baseline vertex detector prototype was tested and characterized for the first time using a 6 GeV electron beam at DESY II Test Beam Line 21. The baseline vertex detector prototype is designed with a cylindrical barrel structure that contains six double-sided detector modules (ladders). Each side of the ladder includes TaichuPix-3 sensors based on Monolithic Active Pixel Sensor (MAPS) technology, a flexible printed circuit, and a carbon fiber support structure. Additionally, the readout electronics and the Data Acquisition system were also examined during this beam test. The performance of the prototype was evaluated using an electron beam that passed through six ladders in a perpendicular direction. The offline data analysis indicates a spatial resolution of about 5 um, with detection efficiency exceeding 99 % and an impact parameter resolution of about 5.1 um. These promising results from this baseline vertex detector prototype mark a significant step toward realizing the optimal vertex detector for the CEPC.

physics.ins-det↗

Charge order induced Dirac pockets in the nonsymmorphic crystal TaTe$_4$

The interplay between charge order (CO) and nontrivial band topology has spurred tremendous interest in understanding topological excitations beyond the single-particle description. In a quasi-one-dimensional nonsymmorphic crystal TaTe$_4$, the (2a$\times$2b$\times$3c) charge ordered ground state drives the system into a space group where the symmetry indicator features the emergence of Dirac fermions and unconventional double Dirac fermions. Using angle-resolved photoemission spectroscopy and first-principles calculations, we provide evidence of the CO induced Dirac fermion-related bands near the Fermi level. Furthermore, the band folding at the Fermi level is compatible with the new periodicity dictated by the CO, indicating that the electrons near the Fermi level follow the crystalline symmetries needed to host double Dirac fermions in this system.

cond-mat.str-el↗

Asteroseismology of the young open cluster NGC 2516 I: Photometric and spectroscopic observations

Asteroseismic modelling of isolated star presents significant challenges due to the difficulty in accurately determining stellar parameters, particularly the stellar age. These challenges can be overcomed by observing stars in open clusters, whose coeval members share an initial chemical composition. The light curves by TESS allow us to investigate and analyse stellar variations in clusters with an unprecedented level. We aim to detect gravity-mode oscillations in the early-type main-sequence members of the young open cluster NGC 2516. We selected the 301 member stars as our sample and analysed the TESS FFI light curves. We also collected high-resolution spectra using the FEROS for the g-mode pulsators. By fitting the theoretical isochrones to the colour-magnitude diagram (CMD) of a cluster, we determined an age of 102 $\pm$ 15 Myr and inferred the extinction at 550 nm ($A_0$) is 0.53 $\pm$ 0.04 mag. We identified 147 stars with surface brightness modulations, 24 with g-mode pulsations ($γ$ Doradus or Slowly Pulsating B stars), and 35 with p-mode pulsations ($δ$ Sct stars). When sorted by colour index, the amplitude spectra of the $δ$ Sct stars show a distinct ordering and reveal a discernible frequency-temperature relationship. The near-core rotation rates, measured from period spacing patterns in two SPB and nine $γ$ Dor stars, reach up to 3/d . This is at the high end of the values found from Kepler data of field stars of similar variability type. The $γ$ Dor stars have internal rotation rates as high as 50% of their critical value, whereas the SPB stars exhibit rotation rates close to their critical rate. We did not find long-term brightness and colour variations in the mid-infrared, which suggests that there are no disk or shell formation events in our sample. We also discussed the results of our spectroscopic observations for the g-mode pulsators.

astro-ph.SR↗

Microwave-to-optics conversion using magnetostatic modes and a tunable optical cavity

Quantum computing, quantum communication and quantum networks rely on hybrid quantum systems operating in different frequency ranges. For instance, the superconducting qubits work in the gigahertz range, while the optical photons used in communication are in the range of hundreds of terahertz. Due to the large frequency mismatch, achieving the direct coupling and information exchange between different information carriers is generally difficult. Accordingly, a quantum interface is demanded, which serves as a bridge to establish information linkage between different quantum systems operating at distinct frequencies. Recently, the magnon mode in ferromagnetic spin systems has received significant attention. While the inherent weak optomagnonic coupling strength restricts the microwave-to-optical photon conversion efficiency using magnons, the versatility of the magnon modes, together with their readily achievable strong coupling with other quantum systems, endow them with many distinct advantages. Here, we realize the magnon-based microwave-light interface by adopting an optical cavity with adjustable free spectrum range and different kinds of magnetostatic modes in two microwave cavity configurations. By optimizing the parameters, an internal conversion efficiency of $1.28 \times 10^{-7}$ is achieved. We analyze the impact of various parameters on the microwave-to-optics conversion. The study provides useful guidance and insights to further enhancing the microwave-to-optics conversion efficiency using magnons.

quant-ph↗

Modelling ion acceleration and transport in corotating interaction regions: the mass-to-charge ratio dependence of the particle spectrum

We investigate the role of perpendicular diffusion in shaping energetic ion spectrum in corotating interaction regions (CIRs), focusing on its mass-to-charge ($A/Q$) dependence. We simulate a synthetic CIR using the EUropean Heliospheric FORcasting Information Asset (EUHFORIA) and model the subsequent ion acceleration and transport by solving the focused transport equation incorporating both parallel and perpendicular diffusion. Our results reveal distinct differences in ion spectra between scenarios with and without perpendicular diffusion. In the absence of perpendicular diffusion, ion spectra near CIRs show a strong $(A/Q)^ε$ dependence with $ε$ depending on the turbulence spectral index, agreeing with theoretical predictions. In contrast, the incorporation of perpendicular diffusion, characterized by a weak $A/Q$ dependence, leading to similar spectra for different ion species. This qualitatively agrees with observations of energetic particles in CIRs.

astro-ph.SR↗

Complementary LHC searches for UV resonances of the $0νββ$ decay operators

We investigate the quark-level effective operators related to the neutrinoless double beta $(0νββ)$ decay process, and their ultraviolet completions relevant to chiral enhancement effects at the hadronic level. We have classified several kinds of leptoquark models, matching to different standard model effective operators. Assuming weakly-coupled new physics, we find the ongoing $0νββ$-decay experiments are sensitive to new physics scale at around $2\sim 4$ TeV, which is in the reach of LHC searches. We discuss the discovery potential of such resonances in the same-sign dilepton channels at the LHC. Therefore, the direct LHC searches and indirect $0νββ$-decay searches are complementary to each other in testing the UV completions of the effective operators for $0νββ$ decay.

hep-ph↗

Hunting for $X_b$ via hidden bottomonium decays $X_b\to ππχ_{bJ}$

In this work, we investigate the isospin breaking decay $X_b \to π^0χ_{bJ}$ and the isospin conserved decay $X_b \to ππχ_{bJ}$, where $X_b$ is taken to be the heavy quark flavor symmetry counterpart of $X(3872)$ in the bottomonium sector as a $B^*\bar B$ molecule candidate. Since the mass of this state may be far below the $B {\bar B}^*$ threshold and the mass difference between the neutral and charged bottom meson is small compared to the binding energy of the $X_b$, the isospin-violating decay channel $X_b \to π^0 χ_{bJ}$ would be highly suppressed. The calculated partial width of $X_b \to ππχ_{b1}$ is found to be about tens of $\rm{keVs}$, $1\sim 2$ order(s) of magnitude larger than those of $X_b \to ππχ_{b2}$ and $X_b \to ππχ_{b0}$. Taking into account the fact that the total width of $X_b$ may be smaller than a few MeV like $X(3872)$, the calculated branching ratios $X_b\to ππχ_{b1}$ may reach to orders of $10^{-2}$, which makes it a possible channel for the experimental searching of the $X_b$.

hep-ph↗

COMIC: An Unsupervised Change Detection Method for Heterogeneous Remote Sensing Images Based on Copula Mixtures and Cycle-Consistent Adversarial Networks

In this paper, we consider the problem of change detection (CD) with two heterogeneous remote sensing (RS) images. For this problem, an unsupervised change detection method has been proposed recently based on the image translation technique of Cycle-Consistent Adversarial Networks (CycleGANs), where one image is translated from its original modality to the modality of the other image so that the difference map can be obtained by performing arithmetical subtraction. However, the difference map derived from subtraction is susceptible to image translation errors, in which case the changed area and the unchanged area are less distinguishable. To overcome the above shortcoming, we propose a new unsupervised copula mixture and CycleGAN-based CD method (COMIC), which combines the advantages of copula mixtures on statistical modeling and the advantages of CycleGANs on data mining. In COMIC, the pre-event image is first translated from its original modality to the post-event image modality. After that, by constructing a copula mixture, the joint distribution of the features from the heterogeneous images can be learnt according to quantitive analysis of the dependence structure based on the translated image and the original pre-event image, which are of the same modality and contain totally the same objects. Then, we model the CD problem as a binary hypothesis testing problem and derive its test statistics based on the constructed copula mixture. Finally, the difference map can be obtained from the test statistics and the binary change map (BCM) is generated by K-means clustering. We perform experiments on real RS datasets, which demonstrate the superiority of COMIC over the state-of-the-art methods.

eess.IV↗

Optimal Control of Malware Propagation in IoT Networks

The rapid proliferation of Internet of Things (IoT) devices in recent years has resulted in a significant surge in the number of cyber-attacks targeting these devices. Recent data indicates that the number of such attacks has increased by over 100 percent, highlighting the urgent need for robust cybersecurity measures to mitigate these threats. In addition, a cyber-attack will begin to spread malware across the network once it has successfully compromised an IoT network. However, to mitigate this attack, a new patch must be applied immediately. In reality, the time required to prepare and apply the new patch can vary significantly depending on the nature of the cyber-attack. In this paper, we address the issue of how to mitigate cyber-attacks before the new patch is applied by formulating an optimal control strategy that reduces the impact of malware propagation and minimise the number of infected devices across IoT networks in the smart home. A novel node-based epidemiological model susceptible, infected high, infected low, recover first, and recover complete(SI_HI_LR_FR_C) is established with immediate response state for the restricted environment. After that, the impact of malware on IoT devices using both high and low infected rates will be analyzed. Finally, to illustrate the main results, several numerical analyses are carried out in addition to simulate the real-world scenario of IoT networks in the smart home, we built a dataset to be used in the experiments.

cs.CR↗

Performance studies of jet flavor tagging and measurement of $R_b(R_c)$ using ParticleNet at CEPC

Jet flavor tagging plays a crucial role in the measurement of relative partial decay widths of $Z$ boson, denoted as $R_b$($R_c$), which is considered as a fundamental test of the Standard Model and sensitive probe to new physics. In this study, a Deep Learning algorithm, ParticleNet, is employed to enhance the performance of jet flavor tagging. The combined efficiency and purity of $c$-tagging is improved by more than 50\% compared to the Circular Electron Positron Collider (CEPC) baseline software. In order to measure $R_b$($R_c$) with this new flavor tagging approach, we have adopted the double-tagging method. The precision of $R_b$($R_c$) is improved significantly, in particular to $R_c$, which has seen a reduction in statistical uncertainty by 40\%.

hep-ex↗

Detecting Change Intervals with Isolation Distributional Kernel

Detecting abrupt changes in data distribution is one of the most significant tasks in streaming data analysis. Although many unsupervised Change-Point Detection (CPD) methods have been proposed recently to identify those changes, they still suffer from missing subtle changes, poor scalability, or/and sensitivity to outliers. To meet these challenges, we are the first to generalise the CPD problem as a special case of the Change-Interval Detection (CID) problem. Then we propose a CID method, named iCID, based on a recent Isolation Distributional Kernel (IDK). iCID identifies the change interval if there is a high dissimilarity score between two non-homogeneous temporal adjacent intervals. The data-dependent property and finite feature map of IDK enabled iCID to efficiently identify various types of change-points in data streams with the tolerance of outliers. Moreover, the proposed online and offline versions of iCID have the ability to optimise key parameter settings. The effectiveness and efficiency of iCID have been systematically verified on both synthetic and real-world datasets.

cs.LG↗

Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data

The understanding of the convoluted evolution of infant brain networks during the first postnatal year is pivotal for identifying the dynamics of early brain connectivity development. Existing deep learning solutions suffer from three major limitations. First, they cannot generalize to multi-trajectory prediction tasks, where each graph trajectory corresponds to a particular imaging modality or connectivity type (e.g., T1-w MRI). Second, existing models require extensive training datasets to achieve satisfactory performance which are often challenging to obtain. Third, they do not efficiently utilize incomplete time series data. To address these limitations, we introduce FedGmTE-Net++, a federated graph-based multi-trajectory evolution network. Using the power of federation, we aggregate local learnings among diverse hospitals with limited datasets. As a result, we enhance the performance of each hospital's local generative model, while preserving data privacy. The three key innovations of FedGmTE-Net++ are: (i) presenting the first federated learning framework specifically designed for brain multi-trajectory evolution prediction in a data-scarce environment, (ii) incorporating an auxiliary regularizer in the local objective function to exploit all the longitudinal brain connectivity within the evolution trajectory and maximize data utilization, (iii) introducing a two-step imputation process, comprising a preliminary KNN-based precompletion followed by an imputation refinement step that employs regressors to improve similarity scores and refine imputations. Our comprehensive experimental results showed the outperformance of FedGmTE-Net++ in brain multi-trajectory prediction from a single baseline graph in comparison with benchmark methods.

q-bio.NC↗

Hidden charmonium decays of 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} $. Assuming the $X_2$ as a pure molecule of the $D^*\bar{D}^*$, we calculated in detail the hidden charmonium decays of the $X_2 \to J/ψV$ and $X_2\toη_cP$ via the intermediate meson loops, where $V = ρ^0\,,ω$ and $P= π^0\,,η\,,η'$. The results indicate that the decay widths are strongly dependent on the $X_2$ mass. At present center value of the mass $4014.3~\mathrm{MeV}$, the width for the $X_2\to J/ψρ^0$ is predicted to be a few tens of keV, while it is on the order of $10^{2\text{-}3}~\mathrm{keV}$ for the $X_2\to J/ ψω$; the predicted width for the $X_2\to η_c π^0$ is about a few keV, while the widths for $X_2\toη_cη$ and $η_cη'$ are around a few tens and tenths of keV, respectively. We also investigated the dependence of the ratios between these widths on the $X_2$ mass and on the $η$-$η'$ mixing angle, which may be good quantities for experiments. We hope that the present calculations would be checked experimentally in the future.

hep-ph↗

Resolved Raman sideband cooling of a single optically trapped cesium atom

We developed a resolved Raman sideband cooling scheme that can efficiently prepare a single optically trapped cesium (Cs) atom in its motional ground states. A two-photon Raman process between two outermost Zeeman sublevels in a single hyperfine state is applied to reduce the phonon number. Our scheme is less sensitive to the variation in the magnetic field than the commonly used scheme where the two outermost Zeeman sublevels belonging to the two separate ground hyperfine states are taken. Fast optical pumping with less spontaneous emission guarantees the efficiency of the cooling process. After cooling for 50 ms, 82% of the Cs atoms populate their three-dimensional ground states. Our scheme improves the long-term stability of Raman sideband cooling in the presence of magnetic field drift and is thus suitable for cooling other trapped atoms or ions with abundant magnetic sublevels.

quant-ph↗