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Jie Zheng

Publications and source records attributed to Jie Zheng.

At least 73 records · Page 4Linked to original sources
arXiv2024

Candidate Members of the VMP/EMP Disk System of the Galaxy from the SkyMapper and SAGES Surveys

Photometric stellar surveys now cover a large fraction of the sky, probe to fainter magnitudes than large-scale spectroscopic surveys, and are relatively free from the target-selection biases often associated with such studies. Photometric-metallicity estimates that include narrow/medium-band filters can achieve comparable accuracy and precision to existing low-resolution spectroscopic surveys such as SDSS/SEGUE and LAMOST. Here we report on an effort to identify likely members of the Galactic disk system among the very metal-poor (VMP; [Fe/H] $\leq$ --2) and extremely metal-poor (EMP; [Fe/H] $\leq$ --3) stars. Our analysis is based on an initial sample of $\sim11.5$ million stars with full space motions selected from the SkyMapper Southern Survey (SMSS) and Stellar Abundance and Galactic Evolution Survey (SAGES). After applying a number of quality cuts to obtain the best available metallicity and dynamical estimates, we analyze a total of $\sim$5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1,476 VMP stars (6.9%-11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%-18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits (v$_ϕ > 150$ km/s). The total number of candidate VMP/EMP disk-like stars is 1,496, the majority of which have low orbital eccentricities, ecc $\le 0.4$; many have ecc $\le 0.2$. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early forming ``primordial" disk.

astro-ph.GA↗
arXiv2024

Large Language Models for Automated Open-domain Scientific Hypotheses Discovery

Hypothetical induction is recognized as the main reasoning type when scientists make observations about the world and try to propose hypotheses to explain those observations. Past research on hypothetical induction is under a constrained setting: (1) the observation annotations in the dataset are carefully manually handpicked sentences (resulting in a close-domain setting); and (2) the ground truth hypotheses are mostly commonsense knowledge, making the task less challenging. In this work, we tackle these problems by proposing the first dataset for social science academic hypotheses discovery, with the final goal to create systems that automatically generate valid, novel, and helpful scientific hypotheses, given only a pile of raw web corpus. Unlike previous settings, the new dataset requires (1) using open-domain data (raw web corpus) as observations; and (2) proposing hypotheses even new to humanity. A multi-module framework is developed for the task, including three different feedback mechanisms to boost performance, which exhibits superior performance in terms of both GPT-4 based and expert-based evaluation. To the best of our knowledge, this is the first work showing that LLMs are able to generate novel (''not existing in literature'') and valid (''reflecting reality'') scientific hypotheses.

cs.CL↗
arXiv2024

Credentials in the Occupation Ontology

The term credential encompasses educational certificates, degrees, certifications, and government-issued licenses. An occupational credential is a verification of an individuals qualification or competence issued by a third party with relevant authority. Job seekers often leverage such credentials as evidence that desired qualifications are satisfied by their holders. Many U.S. education and workforce development organizations have recognized the importance of credentials for employment and the challenges of understanding the value of credentials. In this study, we identified and ontologically defined credential and credential-related terms at the textual and semantic levels based on the Occupation Ontology (OccO), a BFO-based ontology. Different credential types and their authorization logic are modeled. We additionally defined a high-level hierarchy of credential related terms and relations among many terms, which were initiated in concert with the Alabama Talent Triad (ATT) program, which aims to connect learners, earners, employers and education/training providers through credentials and skills. To our knowledge, our research provides for the first time systematic ontological modeling of the important domain of credentials and related contents, supporting enhanced credential data and knowledge integration in the future.

cs.AI↗
arXiv2024

A fast photometric image alignment algorithm with row and column means

This paper introduces an astronomical image alignment algorithm. This algorithm uses the means of the rows and columns of the original image for alignment, and finds the optimal offset corresponding to the maximum similarity by comparing different offsets between images. The similarity is evaluated by the standard deviation of the quotient divided by the means. This paper also discusses the theoretical feasibility of this algorithm. Through practical testing, it has been confirmed that the algorithm is fast and robust.

astro-ph.IM↗
arXiv2024

Tianyu: search for the second solar system and explore the dynamic universe

Giant planets like Jupiter and Saturn, play important roles in the formation and habitability of Earth-like planets. The detection of solar system analogs that have multiple cold giant planets is essential for our understanding of planet habitability and planet formation. Although transit surveys such as Kepler and TESS have discovered thousands of exoplanets, these missions are not sensitive to long period planets due to their limited observation baseline. The Tianyu project, comprising two 1-meter telescopes (Tianyu-I and II), is designed to detect transiting cold giant planets in order to find solar system analogs. Featuring a large field of view and equipped with a high-speed CMOS camera, Tianyu-I will perform a high-precision photometric survey of about 100 million stars, measuring light curves at hour-long cadence. The candidates found by Tianyu-I will be confirmed by Tianyu-II and other surveys and follow-up facilities through multi-band photometry, spectroscopy, and high resolution imaging. Tianyu telescopes will be situated at an elevation about 4000 meters in Lenghu, China. With a photometric precision of 1% for stars with V < 18 mag, Tianyu is expected to find more than 300 transiting exoplanets, including about 12 cold giant planets, over five years. A five-year survey of Tianyu would discover 1-2 solar system analogs. Moreover, Tianyu is also designed for non-exoplanetary exploration, incorporating multiple survey modes covering timescales from sub-seconds to months, with a particular emphasis on events occurring within the sub-second to hour range. It excels in observing areas such as infant supernovae, rare variable stars and binaries, tidal disruption events, Be stars, cometary activities, and interstellar objects. These discoveries not only enhance our comprehension of the universe but also offer compelling opportunities for public engagement in scientific exploration.

astro-ph.IM↗
arXiv2024

A spectral data release for 104 Type II Supernovae from the Tsinghua Supernova Group

We present 206 unpublished optical spectra of 104 type II supernovae obtained by the Xinglong 2.16m telescope and Lijiang 2.4m telescope during the period from 2011 to 2018, spanning the phases from about 1 to 200 days after the SN explosion. The spectral line identifications, evolution of line velocities and pseudo equivalent widths, as well as correlations between some important spectral parameters are presented. Our sample displays a large range in expansion velocities. For instance, the Fe~{\sc ii} $5169$ velocities measured from spectra at $t\sim 50$ days after the explosion vary from ${\rm 2000\ km\ s^{-1}}$ to ${\rm 5500\ km\ s^{-1}}$, with an average value of ${\rm 3872 \pm 949\ km\ s^{-1}}$. Power-law functions can be used to fit the velocity evolution, with the power-law exponent quantifying the velocity decline rate. We found an anticorrelation existing between H$β$ velocity at mid-plateau phase and its velocity decay exponent, SNe II with higher velocities tending to have smaller velocity decay rate. Moreover, we noticed that the velocity decay rate inferred from the Balmer lines (i.e., H$α$ and H$β$) have moderate correlations with the ratio of absorption to emission for H$α$ (a/e). In our sample, two objects show possibly flash-ionized features at early phases. Besides, we noticed that multiple high-velocity components may exist on the blue side of hydrogen lines of SN 2013ab, possibly suggesting that these features arise from complex line forming region. All our spectra can be found in WISeREP and Zenodo.

astro-ph.HE↗
arXiv2023

Evaluation of GPT and BERT-based models on identifying protein-protein interactions in biomedical text

Detecting protein-protein interactions (PPIs) is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. However, with the fast-paced growth of biomedical literature, there is a growing need for automated and accurate extraction of PPIs to facilitate scientific knowledge discovery. Pre-trained language models, such as generative pre-trained transformers (GPT) and bidirectional encoder representations from transformers (BERT), have shown promising results in natural language processing (NLP) tasks. We evaluated the performance of PPI identification of multiple GPT and BERT models using three manually curated gold-standard corpora: Learning Language in Logic (LLL) with 164 PPIs in 77 sentences, Human Protein Reference Database with 163 PPIs in 145 sentences, and Interaction Extraction Performance Assessment with 335 PPIs in 486 sentences. BERT-based models achieved the best overall performance, with BioBERT achieving the highest recall (91.95%) and F1-score (86.84%) and PubMedBERT achieving the highest precision (85.25%). Interestingly, despite not being explicitly trained for biomedical texts, GPT-4 achieved commendable performance, comparable to the top-performing BERT models. It achieved a precision of 88.37%, a recall of 85.14%, and an F1-score of 86.49% on the LLL dataset. These results suggest that GPT models can effectively detect PPIs from text data, offering promising avenues for application in biomedical literature mining. Further research could explore how these models might be fine-tuned for even more specialized tasks within the biomedical domain.

cs.CL↗
arXiv2023

Confirmation of a Sub-Saturn-size transiting exoplanet orbiting a G dwarf: TOI-1194 b and a very low mass companion star: TOI-1251 B from TESS

We report the confirmation of a sub-Saturn-size exoplanet, TOI-1194 b with a mass about $0.456_{-0.051}^{+0.055}$ $M_{J}$, and a very low mass companion star with a mass of about $96.5\pm1.5$ $M_J$, TOI-1251 B. Exoplanet candidates provided by the Transiting Exoplanet Survey Satellite (TESS) are suitable for further follow-up observations by ground-based telescopes with small and medium apertures. The analysis is performed based on data from several telescopes worldwide, including telescopes in the Sino-German multiband photometric campaign, which aimed at confirming TESS Objects of Interest (TOIs) using ground-based small-aperture and medium-aperture telescopes, especially for long-period targets. TOI-1194 b is confirmed based on the consistent periodic transits depths from the multiband photometric data. We measure an orbital period of $2.310644\pm0.000001$ d, and radius is $0.767_{-0.041}^{+0.045}$ $R_J$, and amplitude of RV curve is $69.4_{-7.3}^{+7.9}$ m/s. TOI-1251 B is confirmed based on the multiband photometric and high-resolution spectroscopic data, whose orbiting period is $5.963054_{-0.000001}^{+0.000002}$ d, the radius is $0.947_{-0.033}^{+0.035}$ $R_J$, and amplitude of RV curve is $9849_{-40}^{+42}$ m/s.

astro-ph.EP↗
arXiv2023

Weakly supervised learning for pattern classification in serial femtosecond crystallography

Serial femtosecond crystallography at X-ray free electron laser facilities opens a new era for the determination of crystal structure. However, the data processing of those experiments is facing unprecedented challenge, because the total number of diffraction patterns needed to determinate a high-resolution structure is huge. Machine learning methods are very likely to play important roles in dealing with such a large volume of data. Convolutional neural networks have made a great success in the field of pattern classification, however, training of the networks need very large datasets with labels. Th is heavy dependence on labeled datasets will seriously restrict the application of networks, because it is very costly to annotate a large number of diffraction patterns. In this article we present our job on the classification of diffraction pattern by weakly supervised algorithms, with the aim of reducing as much as possible the size of the labeled dataset required for training. Our result shows that weakly supervised methods can significantly reduce the need for the number of labeled patterns while achieving comparable accuracy to fully supervised methods.

cond-mat.mtrl-sci↗
arXiv2023

Photometric calibration of the Stellar Abundance and Galactic Evolution Survey (SAGES): Nanshan One-meter Wide-field Telescope g, r, and i band imaging data

In this paper, a total of approximately 2.6 million dwarfs were constructed as standard stars, with an accuracy of about 0.01-0.02 mag for each band, by combining spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope Data Release 7, photometric data from the corrected Gaia Early Data Release 3, and photometric metallicities. Using the spectroscopy based stellar color regression method (SCR method) and the photometric-based SCR method (SCR' method), we performed the relative calibration of the Nanshan One-meter Wide-field Telescope imaging data. Based on the corrected Pan-STARRS DR1 photometry, the absolute calibration was also performed. In the photometric calibration process, we analyzed the dependence of the calibration zero points on different images (observation time), different gates of the CCD detector, and different CCD positions. We found that the stellar flat and the relative gain between different gates depend on time. The amplitude of gain variation in three channels is approximately 0.5%-0.7% relative to the other channel, with a maximum value of 4%. In addition, significant spatial variations of the stellar flat fitting residual are found and corrected. Using repeated sources in the adjacent images, we checked and discovered internal consistency of about 1-2 mmag in all the filters. Using the PS1 magnitudes synthesized by Gaia DR3 BP/RP spectra by the synthetic photometry method, we found that the photometric calibration uniformity is about 1-2 mmag for all the bands, at a spatial resolution of 1.3 degree. A detailed comparison between the spectroscopy-based SCR and photometric-based SCR method magnitude offsets was performed, and we achieved an internal consistency precision of about 2 mmag or better with resolutions of 1.3 degree for all the filters. Which is mainly from the position-dependent errors of the E(B-V) used in SCR' method.

astro-ph.SR↗
arXiv2023

Beyond spectroscopy. II. Stellar parameters for over twenty million stars in the northern sky from SAGES DR1 and Gaia DR3

We present precise photometric estimates of stellar parameters, including effective temperature, metallicity, luminosity classification, distance, and stellar age, for nearly 26 million stars using the methodology developed in the first paper of this series, based on the stellar colors from the Stellar Abundances and Galactic Evolution Survey (SAGES) DR1 and Gaia EDR3. The optimal design of stellar-parameter sensitive $uv$ filters by SAGES has enabled us to determine photometric-metallicity estimates down to $-3.5$, similar to our previous results with the SkyMapper Southern Survey (SMSS), yielding a large sample of over five million metal-poor (MP; [Fe/H]$\le -1.0$) stars and nearly one million very metal-poor (VMP; [Fe/H]$\le -2.0$) stars. The typical precision is around $0.1$ dex for both dwarf and giant stars with [Fe/H]$>-1.0$, and 0.15-0.25/0.3-0.4 dex for dwarf/giant stars with [Fe/H]$<-1.0$. Using the precise parallax measurements and stellar colors from Gaia, effective temperature, luminosity classification, distance and stellar age are further derived for our sample stars. This huge data set in the Northern sky from SAGES, together with similar data in the Southern sky from SMSS, will greatly advance our understanding of the Milky Way, in particular its formation and evolution.

astro-ph.GA↗
arXiv2023

The Stellar Abundances and Galactic Evolution Survey (SAGES) -- -- I. General Description and the First Data Release (DR1)

The Stellar Abundances and Galactic Evolution Survey (SAGES) of the northern sky is a specifically-designed multi-band photometric survey aiming to provide reliable stellar parameters with accuracy comparable to those from low-resolution optical spectra. It was carried out with the 2.3-m Bok telescope of Steward Observatory and three other telescopes. The observations in the $u_s$ and $v_s$ passband produced over 36,092 frames of images in total, covering a sky area of $\sim9960$ degree$^2$. The median survey completeness of all observing fields for the two bands are of $u_{\rm s}=20.4$ mag and $v_s=20.3$ mag, respectively, while the limiting magnitudes with signal-to-noise ratio (S/N) of 100 are $u_s\sim17$ mag and $v_s\sim18$ mag, correspondingly. We combined our catalog with the data release 1 (DR1) of the first of Panoramic Survey Telescope And Rapid Response System (Pan-STARRS1, PS1) catalog, and obtained a total of 48,553,987 sources which have at least one photometric measurement in each of the SAGES $u_s$ and $v_s$ and PS1 $grizy$ passbands, which is the DR1 of SAGES and it will be released in our paper. We compare our $gri$ point-source photometry with those of PS1 and found an RMS scatter of $\sim2$% in difference of PS1 and SAGES for the same band. We estimated an internal photometric precision of SAGES to be on the order of $\sim1$%. Astrometric precision is better than $0^{\prime\prime}.2$ based on comparison with the DR1 of Gaia mission. In this paper, we also describe the final end-user database, and provide some science applications.

astro-ph.GA↗
arXiv2023

Micromechanical measurements of local plastic events in granular materials

Understanding the relationship between micromechanics and macroscopic plastic deformation is vital for elucidating the deformation mechanism of amorphous solids, such as granular materials. In this study, we directly measure T1 events, which are topological rearrangements of particles, and the associated microscopic stresses in dense packings of photoelastic disks under pure shear. We observe a remarkable similarity between the evolution of the total number of T1 events and the global stress-strain curve. The competition between the birth and death of T1 events establishes a dynamic equilibrium after the yield strain, contributing to the overall plastic behavior. Despite the erratic stress fluctuations of individual T1 events, the local stresses decrease on average once T1 events occur, indicating their soft characteristics. Furthermore, we demonstrate that the microscopic stress fluctuations exhibit a long-range anisotropic spatial correlation similar to the Eschelby character, but with a distinct scaling of $r^{-1.5}$. Interestingly, we also find a striking similarity in the correlation functions of T1 and non-T1 regions. These findings establish a significant connection between macroscopic mechanical behavior and the elementary deformation of T1 events, shedding light on the fundamental understanding of granular materials as amorphous solids with contact-scale plastic deformation.

cond-mat.soft↗
arXiv2023

Biological Factor Regulatory Neural Network

Genes are fundamental for analyzing biological systems and many recent works proposed to utilize gene expression for various biological tasks by deep learning models. Despite their promising performance, it is hard for deep neural networks to provide biological insights for humans due to their black-box nature. Recently, some works integrated biological knowledge with neural networks to improve the transparency and performance of their models. However, these methods can only incorporate partial biological knowledge, leading to suboptimal performance. In this paper, we propose the Biological Factor Regulatory Neural Network (BFReg-NN), a generic framework to model relations among biological factors in cell systems. BFReg-NN starts from gene expression data and is capable of merging most existing biological knowledge into the model, including the regulatory relations among genes or proteins (e.g., gene regulatory networks (GRN), protein-protein interaction networks (PPI)) and the hierarchical relations among genes, proteins and pathways (e.g., several genes/proteins are contained in a pathway). Moreover, BFReg-NN also has the ability to provide new biologically meaningful insights because of its white-box characteristics. Experimental results on different gene expression-based tasks verify the superiority of BFReg-NN compared with baselines. Our case studies also show that the key insights found by BFReg-NN are consistent with the biological literature.

cs.LG↗
arXiv2022

Revisiting Chaplygin gas cosmologies with the recent observations of high-redshfit quasars

In this paper, we use the latest observations of quasars covering the redshift range of $0.04<z<5.1$ to investigate a series of Chaplygin gas models as candidates for unified dark matter and dark energy. Based on different combinations of available standard candle and standard ruler data, we put constraints on the generalized Chaplygin gas (GCG), modified Chaplygin gas (MCG), new generalized Chaplygin gas (NGCG) and viscous generalized Chaplygin gas (VGCG) models. Moreover, we apply Jensen-Shannon divergence (JSD), statefinder diagnostics, and the deviance information criterion (DIC) to distinguish these CG models, based on the statistical results derived from Markov chain Monte Carlo method. The results show that (1) The standard ruler data could provide more stringent constraints on the cosmological parameters of different CG models considered in this analysis. Interestingly, the matter density parameter $Ω_{m}$ and Hubble constant $H_{0}$ derived from the available data are well consistent with those from the Planck 2018 results; (2) Based on the statistical criteria JSD, our findings demonstrate the well consistency between Chaplygin gas and the concordance $Λ$CDM model. However, in the framework of statefinder diagnostics, the GCG and NGCG models cannot be distinguished from $Λ$CDM, while MCG and VGCG models show significant deviation from $Λ$CDM in the present epoch; (3) According to the the statistical criteria DIC, we show that the MCG and VGCG models have substantial observational support from high-redshfit quasars, whereas the GCG and NGCG models miss out on the less observational support category but can not be ruled out.

astro-ph.CO↗
arXiv2022

Finding Quasars behind the Galactic Plane. II. Spectroscopic Identifications of 204 Quasars at $|b|< 20°$

Quasars behind the Galactic plane (GPQs) are important astrometric references and valuable probes of Galactic gas, yet the search for GPQs is difficult due to severe extinction and source crowding in the Galactic plane. In this paper, we present a sample of 204 spectroscopically confirmed GPQs at |b|<20°, 191 of which are new discoveries. This GPQ sample covers a wide redshift range from 0.069 to 4.487. For the subset of 230 observed GPQ candidates, the lower limit of the purity of quasars is 85.2%, and the lower limit of the fraction of stellar contaminants is 6.1%. Using a multicomponent spectral fitting, we measure the emission line and continuum flux of the GPQs, and estimate their single-epoch virial black hole masses. Due to selection effects raised from Galactic extinction and target magnitude, these GPQs have higher black hole masses and continuum luminosities in comparison to the SDSS DR7 quasar sample. The spectral-fitting results and black hole mass estimates are compiled into a main spectral catalog, and an extended spectral catalog of GPQs. The successful identifications prove the reliability of both our GPQ selection methods and the GPQ candidate catalog, shedding light on the astrometric and astrophysical programs that make use of a large sample of GPQs in the future.

astro-ph.GA↗
arXiv2022

A new way to explore cosmological tensions using gravitational waves and strong gravitational lensing

In recent years, a crisis in the standard cosmology has been caused by inconsistencies in the measurements of some key cosmological parameters, Hubble constant $H_0$ and cosmic curvature parameter $Ω_K$ for example. It is necessary to remeasure them with the cosmological model-independent methods. In this paper, based on the distance sum rule, we present such a way to constrain $H_0$ and $Ω_K$ simultaneously in the late universe from strong gravitational lensing time delay (SGLTD) data and gravitational wave (GW) standard siren data simulated from the future observation of the Einstein Telescope (ET). Based on the currently 6 observed SGLTD data, we find that the constraint precision of $H_0$ from the combined 100 GW events can be comparable with the measurement from SH0ES collaboration. As the number of GW events increases to 700, the constraint precision of $H_0$ will exceed that of the \textit{Planck} 2018 results. Considering 1000 GW events as the conservative estimation of ET in ten-year observation, we obtain $H_0=73.69\pm 0.36 \mathrm{~km~s^{-1}~Mpc^{-1}}$ with a 0.5\% uncertainty and $Ω_K=0.076^{+0.068}_{-0.087}$. In addition, we simulate 55 SGL systems with 6.6\% uncertainty for the measurement of time-delay distance. By combining with 1000 GWs, we infer that $H_0=73.65\pm0.35 \mathrm{~km~s^{-1}~Mpc^{-1}}$ and $Ω_K=0.008\pm0.048$. Our results suggest that this approach can play an important role in exploring cosmological tensions.

astro-ph.CO↗
arXiv2022

Constrained Reinforcement Learning for Short Video Recommendation

The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users provide complex and multi-faceted responses towards recommendations, including watch time and various types of interactions with videos. As a result, established recommendation algorithms that concern a single objective are not adequate to meet this new demand of optimizing comprehensive user experiences. In this paper, we formulate the problem of short video recommendation as a constrained Markov Decision Process (MDP), where platforms want to optimize the main goal of user watch time in long term, with the constraint of accommodating the auxiliary responses of user interactions such as sharing/downloading videos. To solve the constrained MDP, we propose a two-stage reinforcement learning approach based on actor-critic framework. At stage one, we learn individual policies to optimize each auxiliary response. At stage two, we learn a policy to (i) optimize the main response and (ii) stay close to policies learned at the first stage, which effectively guarantees the performance of this main policy on the auxiliaries. Through extensive simulations, we demonstrate effectiveness of our approach over alternatives in both optimizing the main goal as well as balancing the others. We further show the advantage of our approach in live experiments of short video recommendations, where it significantly outperforms other baselines in terms of watch time and interactions from video views. Our approach has been fully launched in the production system to optimize user experiences on the platform.

cs.LG↗