arXiv subjects

Guangwei Li

Publications and source records attributed to Guangwei Li.

18 recordsLinked to original sources

arXiv2026

Overview of Ground-based Wide-Angle Cameras array

As one of the key ground-based facilities of the Chinese-French SVOM mission, the main scientific objectives of the Ground-based Wide Angle Camera array (GWAC) are to detect prompt optical emission of gamma-ray bursts or other short duration astronomical transients on a second-scale temporal resolution. GWAC is located at Xinglong observatory, China, and consists of 10 mounts and 40 cameras, providing a joint field of view of about 3600 square degrees.The detection ability is 16 magnitude in 10 seconds of exposure time in the visual band under the condition of the new moon phase. Here, we give an overview of GWAC and introduce the science motivation of the project, as well as the performance of the hardware and the software. The observation strategies and the data processing are briefly presented. The early sciences in the last 5 years since the first light are summarized.

astro-ph.IM↗

arXiv2025

PRIV-QA: Privacy-Preserving Question Answering for Cloud Large Language Models

The rapid development of large language models (LLMs) is redefining the landscape of human-computer interaction, and their integration into various user-service applications is becoming increasingly prevalent. However, transmitting user data to cloud-based LLMs presents significant risks of data breaches and unauthorized access to personal identification information. In this paper, we propose a privacy preservation pipeline for protecting privacy and sensitive information during interactions between users and LLMs in practical LLM usage scenarios. We construct SensitiveQA, the first privacy open-ended question-answering dataset. It comprises 57k interactions in Chinese and English, encompassing a diverse range of user-sensitive information within the conversations. Our proposed solution employs a multi-stage strategy aimed at preemptively securing user information while simultaneously preserving the response quality of cloud-based LLMs. Experimental validation underscores our method's efficacy in balancing privacy protection with maintaining robust interaction quality. The code and dataset are available at https://github.com/ligw1998/PRIV-QA.

cs.CL↗

arXiv2024

A photometric and spectroscopic study of eight semi-detached eclipsing binaries

By cross-matching the eclipsing binary catalog from TESS with that from LAMOST MRS, semi-detached eclipsing binaries with radial velocities coverage spanning more than 0.3 phases were authenticated. The absolute parameters for these systems were determined by simultaneous modeling of light curves and radial velocities using the Wilson-Devinney program. Additionally, the secular orbital variations were further analyzed using O-C curves. Eight semi-detached eclipsing binaries have been identified. Among them, seven feature primary stars situated within the main-sequence band, while their secondaries are all in evolved stages. This suggests that these systems likely originated as detached binaries and have undergone a reversal of the mass ratio. However, TIC 428257299 is an exception where the primary is Roche lobe-filling, and its secondary has experienced mass loss events. Additionally, TIC 8677671 and TIC 318217844 demonstrate secular cyclical changes of orbital periods. Specifically, for TIC 8677671, the cyclical change could result from magnetic activity or a third body which is likely to be compact, with a mass of at least 2.97 M$_{\odot}$.

astro-ph.SR↗

arXiv2023

Diverse and Vivid Sound Generation from Text Descriptions

Previous audio generation mainly focuses on specified sound classes such as speech or music, whose form and content are greatly restricted. In this paper, we go beyond specific audio generation by using natural language description as a clue to generate broad sounds. Unlike visual information, a text description is concise by its nature but has rich hidden meanings beneath, which poses a higher possibility and complexity on the audio to be generated. A Variation-Quantized GAN is used to train a codebook learning discrete representations of spectrograms. For a given text description, its pre-trained embedding is fed to a Transformer to sample codebook indices to decode a spectrogram to be further transformed into waveform by a melgan vocoder. The generated waveform has high quality and fidelity while excellently corresponding to the given text. Experiments show that our proposed method is capable of generating natural, vivid audios, achieving superb quantitative and qualitative results.

cs.SD↗

arXiv2021

Enriching Ontology with Temporal Commonsense for Low-Resource Audio Tagging

Audio tagging aims at predicting sound events occurred in a recording. Traditional models require enormous laborious annotations, otherwise performance degeneration will be the norm. Therefore, we investigate robust audio tagging models in low-resource scenarios with the enhancement of knowledge graphs. Besides existing ontological knowledge, we further propose a semi-automatic approach that can construct temporal knowledge graphs on diverse domain-specific label sets. Moreover, we leverage a variant of relation-aware graph neural network, D-GCN, to combine the strength of the two knowledge types. Experiments on AudioSet and SONYC urban sound tagging datasets suggest the effectiveness of the introduced temporal knowledge, and the advantage of the combined KGs with D-GCN over single knowledge source.

cs.SD↗

arXiv2020

The GWAC Data Processing and Management System

GWAC will have been built an integrated FOV of 5,000 $degree^2$ and have already built 1,800 square $degree^2$. The limit magnitude of a 10-second exposure image in the moonless night is 16R. In each observation night, GWAC produces about 0.7TB of raw data, and the data processing pipeline generates millions of single frame alerts. We describe the GWAC Data Processing and Management System (GPMS), including hardware architecture, database, detection-filtering-validation of transient candidates, data archiving, and user interfaces for the check of transient and the monitor of the system. GPMS combines general technology and software in astronomy and computer field, and use some advanced technologies such as deep learning. Practical results show that GPMS can fully meet the scientific data processing requirement of GWAC. It can online accomplish the detection, filtering and validation of millions of transient candidates, and feedback the final results to the astronomer in real-time. During the observation from October of 2018 to December of 2019, we have already found 102 transients.

astro-ph.IM↗

arXiv2019

The Richardson-Lucy Deconvolution method to Extract LAMOST 1D Spectra

We use the Richardson-Lucy deconvolution algorithm to extract one dimensional (1D) spectra from LAMOST spectrum images. Compared with other deconvolution algorithms, this algorithm is much more fast. The practice on a real LAMOST image illustrates that the 1D resulting spectrum of this method has a higher SNR and resolution than those extracted by the LAMOST pipeline. Furthermore, our algorithm can effectively depress the ringings that are often shown in the 1D resulting spectra of other deconvolution methods.

astro-ph.IM↗

arXiv2017

Cosmic Ray Removal in Fiber Spectroscopic Image

Single-exposure spectra in large spectral surveys are valuable for time domain studies such as stellar variability, but there is no available method to eliminate cosmic rays for single-exposure, multi-fiber spectral images. In this paper, we describe a new method to detect and remove cosmic rays in multi-fiber spectroscopic single exposures. Through the use of two-dimensional profile fitting and a noise model that considers the position-dependent errors, we successfully detect as many as 80% of the cosmic rays and correct the cosmic ray polluted pixels to an average accuracy of 97.8%. Multiple tests and comparisons with both simulated data and real LAMOST data show that the method works properly in detection rate, false detection rate, and validity of cosmic ray correction.

astro-ph.IM↗

arXiv2017

LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC): the second release of value-added catalogues

We present the second release of value-added catalogues of the LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC DR2). The catalogues present values of radial velocity $V_{\rm r}$, atmospheric parameters --- effective temperature $T_{\rm eff}$, surface gravity log$g$, metallicity [Fe/H], $α$-element to iron (metal) abundance ratio [$α$/Fe] ([$α$/M]), elemental abundances [C/H] and [N/H], and absolute magnitudes ${\rm M}_V$ and ${\rm M}_{K_{\rm s}}$ deduced from 1.8 million spectra of 1.4 million unique stars targeted by the LSS-GAC since September 2011 until June 2014. The catalogues also give values of interstellar reddening, distance and orbital parameters determined with a variety of techniques, as well as proper motions and multi-band photometry from the far-UV to the mid-IR collected from the literature and various surveys. Accuracies of radial velocities reach 5kms$^{-1}$ for late-type stars, and those of distance estimates range between 10 -- 30 per cent, depending on the spectral signal-to-noise ratios. Precisions of [Fe/H], [C/H] and [N/H] estimates reach 0.1dex, and those of [$α$/Fe] and [$α$/M] reach 0.05dex. The large number of stars, the contiguous sky coverage, the simple yet non-trivial target selection function and the robust estimates of stellar radial velocities and atmospheric parameters, distances and elemental abundances, make the catalogues a valuable data set to study the structure and evolution of the Galaxy, especially the solar-neighbourhood and the outer disk.

astro-ph.GA↗

arXiv2016

FGK 22 $μ$m Excess Stars in LAMOST DR2 Stellar Catalog

Since the release of LAMOST (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope) catalog, we have the opportunity to use the LAMOST DR2 stellar catalog and \emph{WISE All-sky catalog} to search for 22 $μ$m excess candidates. In this paper, we present 10 FGK candidates which show an excess in the infrared (IR) at 22 $μ$m. The ten sources are all the newly identified 22 $μ$m excess candidates. Of these 10 stars, 5 stars are F type and 5 stars are G type. The criterion for selecting candidates is $K_s-[22]_{μm}\geq0.387$. In addition, we present the spectral energy distributions (SEDs) covering wavelength from optical to mid-infrared band. Most of them show an obvious excess from 12 $μ$m band and three candidates even show excess from 3.4 $μ$m. To characterize the amount of dust, we also estimate the fractional luminosity of ten 22 $μ$m excess candidates.

astro-ph.SR↗

arXiv2015

Validation of LAMOST Stellar Parameters with the PASTEL Catalog

Recently the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) published its first data release (DR1), which is ranked as the largest stellar spectra dataset in the world so far. We combine the PASTEL catalog and SIMBAD radial velocities as a testing standard to validate the DR1 stellar parameters (effective temperature $T_{\mathrm{eff}}$, surface gravity $\log g$, metallicity $\mathrm{[Fe/H]}$ and radial velocity $V_{\mathrm{r}}$). Through cross-identification of the DR1 catalogs and the PASTEL catalog, we obtain a preliminary sample of 422 stars. After removal of stellar parameter measurements from problematic spectra and applying effective temperature constraints to the sample, we compare the stellar parameters from DR1 with those from PASTEL and SIMBAD to prove that the DR1 results are reliable in restricted $T_{\mathrm{eff}}$ ranges. We derive standard deviations of 110 K, 0.19 dex, 0.11 dex and 4.91 $\mathrm{km\,s^{-1}}$ , for $T_{\mathrm{eff}}$, $\log g$, $[\mathrm{Fe/H}]$ when $T_{\mathrm{eff}}<8000\,\mathrm{K}$, and for $V_{\mathrm{r}}$ when $T_{\mathrm{eff}}<10000\,\mathrm{K}$, respectively. Systematic errors are negligible except for that of $V_{\mathrm{r}}$. Besides, metallicities in DR1 are systematically higher than those in PASTEL, in the range of PASTEL $[\mathrm{Fe/H}]<-1.5$.

astro-ph.SR↗

arXiv2015

A Practical Deconvolution Computation Algorithm to Extract 1D Spectra from 2D Images of Optical Fiber Spectroscopy

Bolton and Schlegel presented a promising deconvolution method to extract 1D spectra from a 2D optical fiber spectral CCD image. The method could eliminate the PSF difference between fibers, extract spectra to the photo noise level, as well as improve the resolution. But the method is limited by its huge computation requirement and thus cannot be implemented in actual data reduction. In this article, we develop a practical computation method to solve the computation problem. The new computation method can deconvolve a 2D fiber spectral image of any size with actual PSFs, which may vary with positions. Our method does not require large amounts of memory and can extract a 4k multi 4k noise-free CCD image with 250 fibers in 2 hr. To make our method more practical, we further consider the influence of noise, which is thought to be an intrinsic illposed problem in deconvolution algorithms. We modify our method with a Tikhonov regularization item to depress the method induced noise. Compared with the results of traditional extraction methods, our method has the least residual and influence by cross talk and noise, even for extreme situation. Our method can convergent in 2 to 4 iterations, and the computation times are about 3.5 hr for the extreme fiber distance and about 2 hr for nonextreme cases. Finally, we apply our method to real LAMOST (Large sky Area Multi-Object fiber Spectroscopic Telescope, a.k.a. Guo Shou Jing Telescope) data. We find that the 1D spectra extracted by our method have both higher signal-to-noise ratio and resolution than the traditional methods.

astro-ph.IM↗

arXiv2015

The M-giant star candidates identified in the LAMOST data release 1

We perform a discrimination procedure with the spectral index diagram of TiO5 and CaH2+CaH3 to separate M giants from M dwarfs. Using the M giant spectra identified from the LAMOST DR1 with high signal-to-noise ratio (SNR), we have successfully assembled a set of M giant templates, which show more reliable spectral features. Combining with the M dwarf/subdwarf templates in Zhong et al. (2015), we present an extended M-type templates library which includes not only M dwarfs with well-defined temperature and metallicity grid but also M giants with subtype from M0 to M6. Then, the template-fit algorithm were used to automatically identify and classify M giant stars from the LAMOST DR1. The result of M giant stars catalog is cross-matched with 2MASS JHKs and WISE W1/W2 infrared photometry. In addition, we calculated the heliocentric radial velocity of all M giant stars by using the cross-correlation method with the template spectrum in a zero-velocity restframe. Using the relationship between the absolute infrared magnitude MJ and our classified spectroscopic subtype, we derived the spectroscopic distance of M giants with uncertainties of about 40%. A catalog of 8639 M giants is provided. As an additional search result, we also present 101690 M dwarfs/subdwarfs catalog which were classified by our classification pipeline.

astro-ph.GA↗

arXiv2015

Estimation of distances to stars with stellar parameters from LAMOST

We present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star's absolute magnitude. This technique is tailored specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ~5-degree diameter "plate" that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and target selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ~20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ~40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.

astro-ph.GA↗

arXiv2014

Relative Flux Calibration of the LAMOST Spectroscopic Survey of the Galactic Anti-center

We have developed and implemented an iterative algorithm of flux calibration for the LAMOST Spectroscopic Survey of the Galactic anti-center (LSS-GAC). For a given LSS-GAC plate, the spectra are first processed with a set of nominal spectral response curves (SRCs) and used to derive initial stellar atmospheric parameters (effective temperature $T_{\rm eff}$, surface gravity log\,$g$ and metallicity [Fe/H]) as well as dust reddening $E(B-V)$ of all targeted stars. For each of the sixteen spectrographs, several F-type stars of good signal-to-noise ratios (SNRs) are then selected as flux standard stars for further, iterative spectral flux calibration. Comparison of spectrophotometric colours, deduced from the flux-calibrated spectra, with the photometric measurements yields average differences of 0.02$\pm$0.07 and $-$0.04$\pm$0.09\,mag for the $(g-r)$ and $(g-i)$, respectively. The relatively large negative offset in $(g-i)$ is due to the fact that we have opted not to correct for the telluric bands, most notably the atmospheric A-band in the wavelength range of $i$-band. Comparison of LSS-GAC multi-epoch observations of duplicate targets indicates that the algorithm has achieved an accuracy of about 10 per cent in relative flux calibration for the wavelength range 4000 -- 9000\,Å. The shapes of SRC deduced for the individual LAMOST spectrographs are found to vary by up to 30 per cent for a given night, and larger for different nights, indicating that the derivation of SRCs for the individual plates is essential in order to achieve accurate flux calibration for the LAMOST spectra.

astro-ph.GA↗

arXiv2014

The LAMOST Stellar Parameter Pipeline at Peking University --- LSP3

We introduce the LAMOST Stellar Parameter Pipeline at Peking University --- LSP3, developed and implemented for the determinations of radial velocity $V_{\rm r}$ and stellar atmospheric parameters (effective temperature $T_{\rm eff}$, surface gravity log\,$g$, metallicity [Fe/H]) for the LAMOST Spectroscopic Survey of the Galactic Anti-center (LSS-GAC). We describe the algorithms of LSP3 and examine the accuracy of parameters yielded by it. The precision and accuracy of parameters yielded are investigated by comparing results of multi-epoch observations and of candidate members of open and globular clusters, with photometric calibration, as well as with independent determinations available from a number of external databases, including the PASTEL archive, the APOGEE, SDSS and RAVE surveys, as well as those released in the LAMOST DR1. The uncertainties of LSP3 parameters are characterized and quantified as a function of the spectral signal-to-noise ratio (SNR) and stellar atmospheric parameters. We conclude that the current implementation of LSP3 has achieved an accuracy of 5.0\,km\,s$^{-1}$, 150\,K, 0.25\,dex, 0.15\,dex for the radial velocity, effective temperature, surface gravity and metallicity, respectively, for LSS-GAC spectra of FGK stars of SNRs per pixel higher than 10. The LSP3 has been applied to over a million LSS-GAC spectra collected hitherto. Stellar parameters yielded by the LSP3 will be released to the general public following the data policy of LAMOST, together with estimates of the interstellar extinction $E(B-V)$ and stellar distances, deduced by combining spectroscopic and multi-band photometric measurements using a variety of techniques.

astro-ph.GA↗

arXiv2014

LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC): target selection and the first release of value-added catalogues

As a major component of the LAMOST Galactic surveys, the LAMOST Spectroscopic Survey of the Galactic Anti-centre (LSS-GAC) aims to survey a significant volume of the Galactic thin/thick discs and halo for a contiguous sky area of over 3,400 deg$^2$ centred on the Galactic anti-centre ($|b| \leq 30^{\circ}$, $150 \leq l \leq 210^{\circ}$), and obtain $λλ$3700 -- 9000 low resolution ($R \sim 1,800$) spectra for a statistically complete sample of $\sim 3$\,M stars of all colours down to a limiting magnitued of $r$ $\sim$ 17.8\,mag (to 18.5\,mag for limited fields). Together with Gaia, the LSS-GAC will yield a unique dataset to advance our understanding of the structure and assemblage history of the Galaxy, in particular its disk(s). In addition to the main survey, the LSS-GAC will also target hundreds of thousands objects in the vicinity fields of M\,31 and M\,33 and survey a significant fraction (over a million) of randomly selected very bright stars (VB; $r \le 14$ mag) in the northern hemisphere. During the Pilot and the first year Regular Surveys of LAMOST, a total of 1,042,586 [750,867] spectra of a signal to noise ratio S/N(7450Å) $\ge$ 10 [S/N(4650Å) $\ge$ 10] have been collected. In this paper, we present a detailed description of the target selection algorithm, survey design, observations and the first data release of value-added catalogues (including radial velocities, effective temperatures, surface gravities, metallicities, values of interstellar extinction, distances, proper motions and orbital parameters) of the LSS-GAC.

astro-ph.SR↗

arXiv2013

Effect of clustering on ellipsometric spectra of randomly distributed gold nanoparticles on a substrate

We present a theoretical model for describing light scattering from randomly distributed Au nanoparticles on a substrate, including the clustering effect. By using the finite-element Green function method and spherical harmonic basis functions, we are able to calculate the polarization-dependent reflectivity spectra of the system (modeled by randomly distributed nanoparticles coupled with clusters) efficiently and accurately. The calculated ellipsometric spectra of the system with clusters can adequately describe the experimental data for the whole frequency range. We find that the clustering effect leads to some prominent features in the low frequency range of the ellipsometric spectra, which are attributed to plasmonic resonances associated with the coupling of Au nanoparticles and clusters.

cond-mat.mes-hall↗