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Yue Zhao

Publications and source records attributed to Yue Zhao.

At least 307 records · Page 17Linked to original sources
arXiv2023

Probing the pulsar explanation of the Galactic-Center GeV excess using continuous gravitational-wave searches

Over ten years ago, Fermi observed an excess of GeV gamma rays from the Galactic Center whose origin is still under debate. One explanation for this excess involves annihilating dark matter; another requires an unresolved population of millisecond pulsars concentrated at the Galactic Center. In this work, we use the results from LIGO/Virgo's most recent all-sky search for quasi-monochromatic, persistent gravitational-wave signals from isolated neutron stars, which is estimated to be about 20-50\% of the population, to determine whether unresolved millisecond pulsars could actually explain this excess. First, we choose a luminosity function that determines the number of millisecond pulsars required to explain the observed excess. Then, we consider two models for deformations on millisecond pulsars to determine their ellipticity distributions, which are directly related to their gravitational-wave radiation. Lastly, based on null results from the O3 Frequency-Hough all-sky search for continuous gravitational waves, we find that a large set of the parameter space in the pulsar luminosity function can be excluded. We also evaluate how these exclusion regions may change with respect to various model choices. Our results are the first of their kind and represent a bridge between gamma-ray astrophysics, gravitational-wave astronomy, and dark-matter physics.

astro-ph.HE↗
arXiv2023

DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection

Self-supervised learning (SSL) has proven effective in solving various problems by generating internal supervisory signals. Unsupervised anomaly detection, which faces the high cost of obtaining true labels, is an area that can greatly benefit from SSL. However, recent literature suggests that tuning the hyperparameters (HP) of data augmentation functions is crucial to the success of SSL-based anomaly detection (SSAD), yet a systematic method for doing so remains unknown. In this work, we propose DSV (Discordance and Separability Validation), an unsupervised validation loss to select high-performing detection models with effective augmentation HPs. DSV captures the alignment between an augmentation function and the anomaly-generating mechanism with surrogate losses, which approximate the discordance and separability of test data, respectively. As a result, the evaluation via DSV leads to selecting an effective SSAD model exhibiting better alignment, which results in high detection accuracy. We theoretically derive the degree of approximation conducted by the surrogate losses and empirically show that DSV outperforms a wide range of baselines on 21 real-world tasks.

cs.LG↗
arXiv2023

Earth Shielding and Daily Modulation from Electrophilic Boosted Dark Particles

Boosted dark particles of astrophysical origin can lead to nonstandard nuclear or electron recoil signals in direct detection experiments. %It has been shown that this interpretation successfully explains the excess of keV electron recoil events recently observed by the XENON1T experiment, and that a daily modulation of the signal in the detector is expected. We conduct an investigation of the daily modulation feature of a potential future signal of this type. In particular, we perform simulations of the dark particle interactions with electrons in atoms building up the Earth on its path to the detector, and provide in-depth predictions for the expected daily changes in the signal for various direct detection experiments, including XENONnT, PandaX, and LUX-ZEPLIN.

hep-ph↗
arXiv2023

Evidence for mass-dependent peculiar velocities in compact object binaries: Towards better constraints on natal kicks

We compile a catalogue of low-mass and high-mass X-ray binaries, some recently reported binaries that likely host a neutron star (NS) or a black hole (BH), and binary pulsars (a pulsar and a non-degenerated companion) that have measured systemic radial velocities ($γ$). Using Gaia and radio proper motions together with $γ$, we integrate their Galactic orbits and infer their post-supernova (post-SN) 3D peculiar velocities ($v_\mathrm{pec}^{z=0}$ at Galactic plane crossing); these velocities bear imprint of natal kicks that compact objects received at birth. With the sample totalling 85 objects, we model the overall distribution of $v_\mathrm{pec}^{z=0}$ and find a two-component Maxwellian distribution with a low- ($σ_v \approx 21\,\mathrm{km~s^{-1}}$) and a high-velocity ($σ_v \approx 107\,\mathrm{km~s^{-1}}$) component. A further comparison between distributions of binary subgroups suggests that binaries hosting high-mass donors/luminous companions mostly have $v_\mathrm{pec}^{z=0}\lesssim 100\,\mathrm{km~s^{-1}}$, while binaries with low-mass companions exhibit a broader distribution that extends up to $\sim 400\,\mathrm{km~s^{-1}}$. We also find significant anti-correlations of $v_\mathrm{pec}^{z=0}$ with binary total mass ($M_\mathrm{tot}$) and orbital period ($P_\mathrm{orb}$), at over 99% confidence. Specifically, our fit suggests $v_\mathrm{pec}^{z=0}\propto M_\mathrm{tot}^{-0.5}$ and $v_\mathrm{pec}^{z=0}\propto P_\mathrm{orb}^{-0.2}$. Discussions are presented on possible interpretation of the correlations in the context of kinematics and possible biases. The sample should enable a range of follow-up studies on compact object binary kinematics and evolution.

astro-ph.HE↗
arXiv2023

Mathematical and numerical study of an inverse source problem for the biharmonic wave equation

In this paper, we study the inverse source problem for the biharmonic wave equation. Mathematically, we characterize the radiating sources and non-radiating sources at a fixed wavenumber. We show that a general source can be decomposed into a radiating source and a non-radiating source. The radiating source can be uniquely determined by Dirichlet boundary measurements at a fixed wavenumber. Moreover, we derive a Lipschitz stability estimate for determining the radiating source. On the other hand, the non-radiating source does not produce any scattered fields outside the support of the source function. Numerically, we propose a novel source reconstruction method based on Fourier series expansion by multi-wavenumber boundary measurements. Numerical experiments are presented to verify the accuracy and efficiency of the proposed method.

math.NA↗
arXiv2023

High-speed scanless entire bandwidth mid-infrared chemical imaging

Mid-infrared spectroscopy probes molecular vibrations to identify chemical species and functional groups. Therefore, mid-infrared hyperspectral imaging is one of the most powerful and promising candidates for chemical imaging using optical methods. Yet high-speed and entire bandwidth mid-infrared hyperspectral imaging has not been realized. Here we report a mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane. This technique offers a lateral resolution of 15 $μ$m, and the field of view is adjustable between 800 $μ$m $\times$ 600 $μ$m to 12 mm $\times$ 9 mm. The hyperspectral imaging produces a 640 $\times$ 480 pixel image in 8 s, which covers a spectral range of 640-3015 cm$^{-1}$, comprising 1069 wavelength points and offering a wavenumber resolution of 2.6-3.7 cm$^{-1}$. For discrete frequency mid-infrared imaging, the measurement speed reaches a frame rate of 5 kHz, the repetition rate of the laser. As a demonstration, we effectively identified and mapped different components in a microfluidic device, plant cell, and mouse embryo section. The great capacity and latent force of this technique in chemical imaging promise to be applied to many fields such as chemical analysis, biology, and medicine.

physics.optics↗
arXiv2023

Regularized Multivariate Functional Principal Component Analysis

Multivariate Functional Principal Component Analysis (MFPCA) is a valuable tool for exploring relationships and identifying shared patterns of variation in multivariate functional data. However, controlling the roughness of the extracted Principal Components (PCs) can be challenging. This paper introduces a novel approach called regularized MFPCA (ReMFPCA) to address this issue and enhance the smoothness and interpretability of the multivariate functional PCs. ReMFPCA incorporates a roughness penalty within a penalized framework, using a parameter vector to regulate the smoothness of each functional variable. The proposed method generates smoothed multivariate functional PCs, providing a concise and interpretable representation of the data. Extensive simulations and real data examples demonstrate the effectiveness of ReMFPCA and its superiority over alternative methods. The proposed approach opens new avenues for analyzing and uncovering relationships in complex multivariate functional datasets.

stat.ME↗
arXiv2023

Exotica in the Globular Cluster M4, Studied with Chandra, HST, and the VLA

Using the Hubble Ultraviolet Globular Cluster Survey (HUGS) and additional HST archival data, we have carried out a search for optical counterparts to the low-luminosity Chandra X-ray sources in the globular cluster M4 (NGC 6121). We have also searched for optical or X-ray counterparts to radio sources detected by the VLA. We find 24 new confident optical counterparts to Chandra sources for a total of 40, including the 16 previously identified. Of the 24 new identifications, 18 are stellar coronal X-ray sources (active binaries, ABs), the majority located along the binary sequence in a V-I colour-magnitude diagram and generally showing an H-alpha excess. In addition to confirming the previously detected cataclysmic variable (CV, CX4), we identify one confident new CV (CX76), and two candidates (CX81 and CX101). One MSP is known in M4 (CX12), and another strong candidate has been suggested (CX1); we identify some possible MSP candidates among optical and radio sources, such as VLA20, which appears to have a white dwarf counterpart. One X-ray source with a sub-subgiant optical counterpart and a flat radio spectrum (CX8, VLA31) is particularly mysterious. The radial distribution of X-ray sources suggests a relaxed population of average mass ~ 1.2 - 1.5 Msun. Comparing the numbers of ABs, MSPs, and CVs in M4 with other clusters indicates that AB numbers are proportional to cluster mass (primordial population), MSPs to stellar encounter rate (dynamically formed population), while CVs seem to be produced both primordially and dynamically.

astro-ph.HE↗
arXiv2023

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

Neural architecture search (NAS) for Graph neural networks (GNNs), called NAS-GNNs, has achieved significant performance over manually designed GNN architectures. However, these methods inherit issues from the conventional NAS methods, such as high computational cost and optimization difficulty. More importantly, previous NAS methods have ignored the uniqueness of GNNs, where GNNs possess expressive power without training. With the randomly-initialized weights, we can then seek the optimal architecture parameters via the sparse coding objective and derive a novel NAS-GNNs method, namely neural architecture coding (NAC). Consequently, our NAC holds a no-update scheme on GNNs and can efficiently compute in linear time. Empirical evaluations on multiple GNN benchmark datasets demonstrate that our approach leads to state-of-the-art performance, which is up to $200\times$ faster and $18.8\%$ more accurate than the strong baselines.

cs.LG↗
arXiv2023

Increasing stability estimates for the inverse potential scattering problems

This paper is mainly concerned with the inverse scattering problem of determining the unknown potential for the classical Schrödinger equation in two and three dimensions. We establish the increasing stability of the inverse scattering problem from either multi-frequency near-field data or multi-frequency far-field pattern. The stability estimate consists of the Lipschitz type data discrepancy and the logarithmic high frequency tail of the potential function, where the latter decreases as the upper bound of the frequency increases. A novel method is proposed for the proof, which is based on choosing appropriate incident plane waves and an application of the quantitative analytic continuation. A key ingredient in the analysis is employing scattering theory to obtain an analytic region and resolvent estimates in this region for the resolvent in two and three dimensions. We further apply this method to study the inverse scattering problem of determining both the magnetic potential and electric potential for the three-dimensional magnetic Schrödinger equation.

math.AP↗
arXiv2023

Phonon promoted charge density wave in topological kagome metal ScV$_{6}$Sn$_{6}$

Charge density wave (CDW) orders in vanadium-based kagome metals have recently received tremendous attention due to their unique properties and intricate interplay with exotic correlated phenomena, topological and symmetry-breaking states. However, the origin of the CDW order remains a topic of debate. The discovery of ScV$_{6}$Sn$_{6}$, a vanadium-based bilayer kagome metal exhibiting an in-plane $\sqrt{3}$ x $\sqrt{3} $ $\textit{R}$30$°$ CDW order with time-reversal symmetry breaking, provides a novel platform to explore the underlying mechanism behind the unconventional CDW. Here, we combine high-resolution angle-resolved photoemission spectroscopy, Raman scattering measurements and density functional theory to investigate the electronic structures and phonon modes of ScV$_{6}$Sn$_{6}$ and their evolution with temperature. We identify topologically nontrivial Dirac surface states and multiple van Hove singularities (VHSs) in the vicinity of the Fermi level, with one VHS near the K point exhibiting nesting wave vectors in proximity to the $\sqrt{3}$ x $\sqrt{3}$ $\textit{R}$30$°$ CDW wave vector. Additionally, Raman measurements indicate a strong intrinsic electron-phonon coupling in ScV$_{6}$Sn$_{6}$, as evidenced by the presence of a two-phonon mode and a large frequency amplitude mode. Our findings highlight the fundamental role of lattice degrees of freedom in promoting the CDW in ScV$_{6}$Sn$_{6}$ and provide important insights into the fascinating correlation phenomena observed in kagome metals.

cond-mat.str-el↗
arXiv2023

Construction of unbiased dental template and parametric dental model for precision digital dentistry

Dental template and parametric dental models are important tools for various applications in digital dentistry. However, constructing an unbiased dental template and accurate parametric dental models remains a challenging task due to the complex anatomical and morphological dental structures and also low volume ratio of the teeth. In this study, we develop an unbiased dental template by constructing an accurate dental atlas from CBCT images with guidance of teeth segmentation. First, to address the challenges, we propose to enhance the CBCT images and their segmentation images, including image cropping, image masking and segmentation intensity reassigning. Then, we further use the segmentation images to perform co-registration with the CBCT images to generate an accurate dental atlas, from which an unbiased dental template can be generated. By leveraging the unbiased dental template, we construct parametric dental models by estimating point-to-point correspondences between the dental models and employing Principal Component Analysis to determine shape subspaces of the parametric dental models. A total of 159 CBCT images of real subjects are collected to perform the constructions. Experimental results demonstrate effectiveness of our proposed method in constructing unbiased dental template and parametric dental model. The developed dental template and parametric dental models are available at https://github.com/Marvin0724/Teeth_template.

cs.CV↗
arXiv2023

Spectroscopic signature of obstructed surface states in SrIn$_2$P$_2$

The century-long development of surface sciences has witnessed the discoveries of a variety of quantum states. In the recently proposed "obstructed atomic insulators", insulators with symmetric charges pinned at virtual sites where no real atoms reside, the cleavage through these sites could lead to a set of obstructed surface states with partial occupation. Here, utilizing scanning tunneling microscopy, angle-resolved photoemission spectroscopy and first-principles calculations, we observe spectroscopic signature of obstructed surface states in SrIn$_2$P$_2$. We find a pair of surface states originated from the pristine obstructed surface states split by a unique surface reconstruction. The upper branch is marked with a striking differential conductance peak followed by negative differential conductance, signaling its localized nature, while the lower branch is found to be highly dispersive. This pair of surface states is in consistency with our calculational results. Our finding not only demonstrates a surface quantum state induced by a new type of bulk-boundary correspondence, but also provides a platform for exploring efficient catalysts and related surface engineering.

cond-mat.mtrl-sci↗
arXiv2023

Inverse source scattering problem for a nonlinear Schrödinger equation

We study an inverse source scattering problem for the Schrödinger equation with a quadratic nonlinearity. In general, uniqueness of inverse source problems can not be guaranteed at a fixed energy. Therefore, additional information is required for the source in order to obtain a unique solution. By adding reference point sources, we show that a general source function could be uniquely determined from boundary measurements at a fixed wavenumber. This method does not apply to inverse source problems of linear equations since it uses the nonlinearity as a tool. The proof utilizes the method of linearization to reduce the nonlinear inverse source scattering problem to the inverse potential scattering problem of the linear Schrödinger equation.

math.AP↗
arXiv2023

Inverse moving source problems for parabolic equations

This paper is concerned with the inverse moving source problems for parabolic equations. Given the temporal function, we prove the uniqueness of the nonlinear inverse problem of determining the orbit function by final data measured in a bounded domain. On the other hand, given the orbit function we also show that the profile function can be uniquely determined by final data measured in a bounded domain away from the domain enclosing the moving orbit. The proofs adopt the Fourier approach and results from complex analysis.

math.AP↗
arXiv2023

Stabilization with Prescribed Instant via Lyapunov Method

This letter investigates the prescribed-instant stabilization problem for high-order integrator systems. In anothor word, the settling time under the presented controller is independent of the initial conditions and equals the prescribed time instant. The controller is designed with the concept of backstepping. A strict proof based on the Lyapunov method is presented to clamp the settling time to the prescribed time instant from both the left and right sides. This proof serves as an example to present a general framework to verify the designed stabilization property. It should be emphasized that the prescribed-time stability (PSTS) [1] can only prescribe the upper bound of the settling time and is different from this work. The detailed argumentation will be presented after a brief review of the existing important research.

eess.SY↗
arXiv2023

Weakly Supervised Anomaly Detection: A Survey

Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news. However, obtaining complete, accurate, and precise labels for AD tasks can be expensive and challenging due to the cost and difficulties in data annotation. To address this issue, researchers have developed AD methods that can work with incomplete, inexact, and inaccurate supervision, collectively summarized as weakly supervised anomaly detection (WSAD) methods. In this study, we present the first comprehensive survey of WSAD methods by categorizing them into the above three weak supervision settings across four data modalities (i.e., tabular, graph, time-series, and image/video data). For each setting, we provide formal definitions, key algorithms, and potential future directions. To support future research, we conduct experiments on a selected setting and release the source code, along with a collection of WSAD methods and data.

cs.LG↗
arXiv2023

Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression

Federated learning has become a popular tool in the big data era nowadays. It trains a centralized model based on data from different clients while keeping data decentralized. In this paper, we propose a federated sparse sliced inverse regression algorithm for the first time. Our method can simultaneously estimate the central dimension reduction subspace and perform variable selection in a federated setting. We transform this federated high-dimensional sparse sliced inverse regression problem into a convex optimization problem by constructing the covariance matrix safely and losslessly. We then use a linearized alternating direction method of multipliers algorithm to estimate the central subspace. We also give approaches of Bayesian information criterion and hold-out validation to ascertain the dimension of the central subspace and the hyper-parameter of the algorithm. We establish an upper bound of the statistical error rate of our estimator under the heterogeneous setting. We demonstrate the effectiveness of our method through simulations and real world applications.

stat.ML↗