arXiv subjects

Li-Cai Deng

Publications and source records attributed to Li-Cai Deng.

At least 19 recordsLinked to original sources

arXiv2023

Age Determination of LAMOST Red Giant Branch stars based on the Gradient Boosting Decision Tree method

In this study we estimate the stellar ages of LAMOST DR8 Red Giant Branch (RGB) stars based on the Gradient Boosting Decision Tree algorithm (GBDT). We used 2,643 RGB stars extracted from the APOKASC-2 astero-seismological catalog as training data-set. After selecting the parameterses ([$\alpha$/Fe], [C/Fe], T$_{eff}$, [N/Fe], [C/H], log g) highly correlated with age using GBDT, we apply the same GBDT method to the new catalog of more than 590,000 stars classified as RGB stars. The test data-set shows that the median relative error is around 11.6$\%$ for the method. We also compare the predicted ages of RGB stars with other studies (e.g., based on APOGEE), and find systematic differences. The final uncertainty is about 15 to 30$\%$ compared to open clusters' ages. Then we present the spatial distribution of the RGB sample having an age determination, which could recreate the expected result, and discuss systematic biases. All these diagnostics show that one can apply the GBDT method to other stellar samples to estimate atmospheric parameters and age.

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arXiv2022

Mass and Age determination of the LAMOST data with different Machine Learning methods

We present a catalog of 948,216 stars with mass label and a catalog of 163,105 red clump (RC) stars with mass and age labels simultaneously. The training dataset is cross matched from the LAMOST (The Large Sky Area Multi-Object Fiber Spectroscopic Telescope) DR5 and high resolution asteroseismology data, mass and age are predicted by random forest method or convex hull algorithm. The stellar parameters with high correlation with mass and age are extracted and the test dataset shows that the median relative error of the prediction model for the mass of large sample is 3\% and meanwhile, the mass and age of red clump stars are 4\% and 7\%. We also compare the predicted age of red clump stars with the recent works and find that the final uncertainty of the RC sample could reach 18\% for age and 9\% for mass, in the meantime, final precision of the mass for large sample with different type of stars could reach 13\% without considering systematics, all these are implying that this method could be widely used in the future. Moreover, we explore the performance of different machine learning methods for our sample, including bayesian linear regression (BYS), gradient boosting decision Tree (GBDT), multilayer perceptron (MLP), multiple linear regression (MLR), random forest (RF) and support vector regression (SVR). Finally we find that the performance of nonlinear model is generally better than that of linear model, and the GBDT and RF methods are relatively better.

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arXiv2020

Detecting shock waves in non-fundamental mode RR Lyrae using large sample of spectra in SDSS and LAMOST

Steps toward the nature inside RR Lyrae variables can not only improve our understanding of variable stars but also innovate the precision when we use them as tracers to map the structure of the universe. In this work, we develop a hand-crafted one-dimensional pattern recognition pipeline to fetch out the "first apparitions", the most prominent observational characteristic of shock. We report the first detection of hydrogen emission lines in the first-overtone and multi-mode RR Lyrae variables. We find that there is an anti-correlation between the intensity and the radial velocity of the emission signal, which is possibly caused by opacity changing in the helium ionization zone. Moreover, we find one RRd star with hydrogen emission that possibly shows Blazhko-type modulations. According to our discoveries, with an enormous volume of upcoming data releases of variable stars and spectra, it may become possible to build up the bridge between shock waves and big problems like the Blazhko effect in non-fundamental mode RR Lyrae stars.

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arXiv2020

Possible evidence of hydrogen emission in the first-overtone and multi-mode RR Lyrae variables

The nature of shock waves in non-fundamental mode RR Lyrae stars remains a mystery because of limited spectroscopic observations. We apply a pattern recognition algorithm on spectroscopic data from SDSS and LAMOST and report the first evidence of hydrogen emission in first-overtone and multi-mode RR Lyrae stars showing the "first apparition", which is the most prominent observational characteristic of shock in RR Lyrae variables. We find ten RRc stars in SDSS, ten RRc stars in LAMOST, and three RRd stars in LAMOST that show blueshifted Balmer emissions. The emission features possibly indicate the existence of shock waves. We calculate the radial velocities of the emission lines, which are related to the physical conditions occurring in the radiative zone of shock waves. Using photometric observations from ZTF, we present a detailed light curve analysis for the frequency components in one of our RRd stars with hydrogen emission, RRdl3, for possible modulations. With the enormous volume of upcoming spectral observations of variable stars, our study raises the possibility of connecting the unexplained Blazhko effect to shock waves in non-fundamental mode RR Lyrae stars.

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arXiv2020

The local and global properties of different types of supernova host galaxies

By using Data Analysis Pipeline (DAP) products of Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), which are publicly available from the SDSS Data Release 15, we analyze the local properties at the SN explosion sites and global properties of different types of SN host galaxies to explore the explosion environments of different types of SNe. In our sample, there are 67 SN host galaxies in the field of view of MaNGA, including 32 Type Ia, 29 CCSNe, 1 super-luminous SN (SLSN), 1 Type I and 4 unclassified type of SNe, with which we can perform the K-S test for analysis and derive statistically robust results. Due to the limited sample size, we couldn't remove the mass dependence in this work, which is likely the true driver of the trends for the properties presented in this work. The global star formation rate (SFR) and EW(H$\alpha$) for SN Ia hosts is slightly lower than that for CCSN hosts on average. SN Ia host galaxies are $\sim$ 0.3 dex more massive than CCSN hosts, which implies that the number ratio of CCSNe to Type Ia SNe will decrease with the increasing of stellar mass of host galaxies. The stellar population age of SN Ia host galaxies is older than that of CCSN hosts on average. There is no significant difference between different types of SN hosts for some properties, including local SFR density ($\Sigma \rm SFR$), local and global gas-phase oxygen abundance. For most galaxies in our sample, the global gas-phase oxygen abundance estimated from the integrated spectra of SN hosts can represent the local gas-phase oxygen abundance at the SN explosion sites with small bias.

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arXiv2019

Exploring the spectral \textit{information content} in the LAMOST medium-resolution survey (MRS)

Low-resolution spectra are proved competitive to high-resolution spectra in determining many stellar labels at comparable precision. It is useful to consider the spectral information content when assessing the capability of a stellar spectrum in deriving precise stellar labels. In this work, we quantify the information content brought by the LAMOST-II medium-resolution spectroscopic survey (MRS) using the gradient spectra and the coefficients-of-dependence (CODs). In general, the wavelength coverage of the MRS well constrains the stellar labels but the sensitivities of different stellar labels vary with spectral types and metallicity of the stars of interest and, therefore, affect the performance of the stellar label determination from the MRS spectra. Applying the SLAM to the synthetic spectra which mimic the MRS data, we find the precision of the fundamental stellar parameters Teff, logg and [M/H] are better when combining both the blue and red bands of the MRS. This is especially important for warm stars since the H$\alpha$ line located in the red part plays a more important role in determining the effective temperature for warm stars. With blue and red parts together, we are able to reach similar performance to the low-resolution spectra except for warm stars. However, at [M/H]$\sim-2.0$ dex, the uncertainties of fundamental stellar labels estimated from MRS are substantially larger than those from low-resolution spectra. We also tested the uncertainties of Teff, logg and [M/H] of from MRS data induced from the radial velocity mismatch and find that a mismatch of about 1 km s$^{-1}$, which is typical for LAMOST MRS data, would not significantly affect the stellar label estimates. At last, reference precision limits are calculated using synthetic gradient spectra, according to which we expect abundances of at least 17 elements to be measured precisely from MRS spectra.

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arXiv2019

Deriving the stellar labels of LAMOST spectra with Stellar LAbel Machine (SLAM)

The LAMOST survey has provided 9 million spectra in its Data Release 5 (DR5) at R$\sim$1800. Extracting precise stellar labels is crucial for such a large sample. In this paper, we report the implementation of the Stellar LAbel Machine (SLAM), which is a data-driven method based on Support Vector Regression (SVR), a robust non-linear regression technique. Thanks to the capability to model highly non-linear problems with SVR, SLAM generally can derive stellar labels over a wide range of spectral types. This gives it a unique capability compared to other popular data-driven methods. To illustrate this capability, we test the performance of SLAM on stars ranging from Teff$\sim$4000 to $\sim$8000 K trained on LAMOST spectra and stellar labels. At g-band signal-to-noise ratio (SNRg) higher than 100, the random uncertainties of Teff, logg and [Fe/H] are 50 K, 0.09 dex, and 0.07 dex, respectively. We then set up another SLAM model trained by APOGEE and LAMOST common stars to demonstrate its capability of dealing with high dimensional problems. The spectra are from LAMOST DR5 and the stellar labels of the training set are from APOGEE DR15, including Teff, logg, [M/H],[$\alpha$/M], [C/M], and [N/M]. The cross-validated scatters at SNRg$\sim$100 are 49 K, 0.10 dex, 0.037 dex,0.026 dex, 0.058 dex, and 0.106 dex for these parameters, respectively. This performance is at the same level as other up-to-date data-driven models. As a byproduct, we also provide the latest catalog of $\sim$1 million LAMOST DR5 K giant stars with SLAM-predicted stellar labels in this work.

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arXiv2019

The local properties of supernova explosions and their host galaxies

We aim to understand the properties at the locations of supernova (SN) explosion in their host galaxies and compare with the global properties of the host galaxies. We use the integral field spectrograph (IFS) of Mapping Nearby Galaxies (MaNGA) at Apache Point Observatory (APO) to get the 2D maps of the parameter properties for eleven SN host galaxies. The sample galaxies are analyzed one by one in details on their properties of velocity field, star formation rate, oxygen abundance and stellar mass etc. This sample of SN host galaxies have redshifts around $z$ $\sim$ 0.03, which is higher than those of the previous related works. The higher redshift distribution allows us to obtain the properties of more distant SN host galaxies. Metallicity (gas-phase oxygen abundance) estimated from integrated spectra could represent the local metallicity at SN explosion sites with small bias. All the host galaxies in our sample are metal-rich galaxies (12+log(O/H) $>$ 8.5) except for NGC 6387, which means supernovae (SNe) may be more inclined to explode in rich-metallicity galaxies. There is a positive relation between global gas-phase oxygen abundance and the stellar mass of host galaxies. We also try to compare the differences of the host galaxies between SN Ia and SN II. In our sample, both SNe Ia and SNe II could explode in normal galaxies, while SNe II also could explode in an interactive or merger system, which has star formation in the galaxy.

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arXiv2017

Mapping the Milky Way with LAMOST II: the stellar halo

The radial number density and flattening of the Milky Way's stellar halo is measured with $\mathrm{5351}$ metal-poor ([Fe/H]$<-1$) K giants from LAMOST DR3, using a nonparametric method which is model independent and largely avoids the influence of halo substucture. The number density profile is well described by a single power law with index $5.03^{+0.64}_{-0.64}$, and flattening that varies with radius. The stellar halo traced by LAMOST K giants is more flattened at smaller radii, and becomes nearly spherical at larger radii. The flattening, $q$, is about 0.64, 0.8, 0.96 at $r=15$, 20 and 30 kpc (where $r=\sqrt{R^2+\left[Z/q\left(r\right)\right]^2}$), respectively. Moreover, the leading arm of the Sagittarius dwarf galaxy tidal stream in the north, and the trailing arm in the south, are significant in the residual map of density distribution. In addition, an unknown overdensity is identified in the residual map at (R,Z)=(30,15) kpc.

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arXiv2017

Mapping the Milky Way with LAMOST I: Method and overview

We present a statistical method to derive the stellar density profiles of the Milky Way from spectroscopic survey data, taking into account selection effects. We assume that the selection function of the spectroscopic survey is based on photometric colors and magnitudes and possibly altered during observations and data reductions. Then the underlying selection function for a line-of-sight can be well recovered by comparing the distribution of the spectroscopic stars in a color-magnitude plane with that of the photometric dataset. Subsequently, the stellar density profile along a line-of-sight can be derived from the spectroscopically measured stellar density profile multiplied by the selection function. The method is validated using Galaxia mock data with two different selection functions. We demonstrate that the derived stellar density profiles well reconstruct the true ones not only for the full targets, but also for the sub-populations selected from the full dataset. Finally, the method is applied to map the density profiles for the Galactic disk and halo, respectively, using the LAMOST RGB stars. The Galactic disk extends to about R=19 kpc, where the disk still contributes about 10% to the total stellar surface density. Beyond this radius, the disk smoothly transitions to the halo without any truncation, bending, or broken. Moreover, no over-density corresponding to the Monoceros ring is found in the Galactic anti-center direction. The disk shows moderate north-south asymmetry at radii larger than 12 kpc. On the other hand, the R-Z tomographic map directly shows that the stellar halo is substantially oblate within a Galactocentric radius of 20 kpc and gradually becomes nearly spherical beyond 30 kpc.

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arXiv2016

Numerical simulations of downward convective overshooting in giants

An attempt at understanding downward overshooting in the convective envelopes of post-main-sequence stars has been made on the basis of three-dimensional large-eddy simulations, using artificially modified OPAL opacity and taking into account radiation and ionization in the equation of state. Two types of star, an intermediate-mass star and a massive star, were considered. To avoid a long thermal relaxation time of the intermediate-mass star, we increased the stellar energy flux artificially while trying to maintain a structure close to the one given by a 1D stellar model. A parametric study of the flux factor was performed. For the massive star, no such process was necessary. Numerical results were analysed when the system reached the statistical steady state. It was shown that the penetration distance in pressure scaleheights is of the order of unity. The scaling relations between penetration distance, input flux and vertical velocity fluctuations studied by Singh et al. were checked. The anisotropy of the turbulent convection and the diffusion models of the third-order moments representing the non-local transport were also investigated. These models are dramatically affected by the velocity fields and no universal constant parameters seem to exist. The limitations of the numerical results were also discussed.

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arXiv2015

The K giant stars from the LAMOST survey data II: the Hercules stream in radial migration

We estimate the age for the individual stars located at the lower part of the red giant branch from the LAMOST DR2 K giant sample. Taking into account the selection effects and the volume completeness, the age--metallicity map for the stars located between 0.3 and 1.5 kpc from the Sun is obtained. A significant substructure (denoted as the \it{narrow stripe}) located from (age, [Fe/H])$\sim$(5, 0.4) to (10 Gyr, -0.4 dex) in the age--metallicity map is clearly identified. Moreover, the \it{narrow stripe} stars are found the dominate contributors to several velocity substructures, including the well-known Hercules stream. The substantially large difference between the observed guiding-center radii and the birth radii inferred from the age--metallicity relation is evident that the \it{narrow stripe} stars have been radially migrated from about R$\sim4$ kpc to the solar neighborhood. This implies that the Hercules stream may not be owe to the resonance associated with the bar, but may be the kinematic imprint of the inner disk and later moved out due to radial migration. We estimate that the traveling speed of the radial migration are roughly 1.1$\pm0.1$ kpc Gyr$^{-1}$, equivalent with about $1.1\pm0.1$ km s$^{-1}$. This is in agreement with the median $v_R$ of $2.6^{+1.8}_{-1.9}$ km s$^{-1}$ of the \it{narrow stripe}. We also obtain that about one third stars in the solar neighborhood are radially migrated from around 4 kpc. Finally, we find that the radial migration does not lead to additional disk thickening according to the distribution of $z_{max}$.

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arXiv2015

The stellar kinematics in the solar neighborhood from LAMOST data

We use about 200,000 FGK type main-sequence stars from the LAMOST DR1 data to map the local stellar kinematics. With the velocity de-projection technique, we are able to derive the averaged 3 dimensional velocity and velocity ellipsoids using only the line-of-sight velocity for the stars with various effective temperatures within $100 < |z| < 500$ pc. Using the mean velocities of the cool stars, we derive the solar motion of ($U_{\!\odot}$, $V_{\!\odot}$, $W_{\!\odot}$)=(9.58$\pm2.39$, 10.52$\pm1.96$, 7.01$\pm1.67$)$km\,s^{-1}$ with respect to the local standard of rest. Moreover, we find that the stars with ${T}_{\rm eff}>6000$K show a net asymmetric motion of $\sim3 km\,s^{-1}$ in $\langle W\rangle$ compared to the stars with ${T}_{\rm eff}<6000$K. And their azimuthal velocity increases when $|z|$ increases. This peculiar motion in the warmer stars is likely because they are young and not completely relaxed, although other reasons, such as the resonance induced by the central rotating bar or the spiral structures, and the perturbation of the merging dwarf galaxies, can not be ruled out. The derived velocity dispersions and cross terms for the data are approximately consistent with previous studies. We also find that the vertical gradients of $\sigma_{U}$ and $\sigma_V$ are larger than that of $\sigma_W$ . And the vertical gradient of $\sigma_U$ shows clear correlation with ${T}_{\rm eff}$, while the other two do not. Finally, our sample shows vertex deviation of about 11$^\circ$, at $300 < |z| < 500$pc, but roughly zero at $100 < |z| < 300$pc.

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arXiv2015

Member candidates of the star clusters from LAMOST DR2 data

In this work, we provide 2189 photometric- and kinematic-selected member candidates of 24 star clusters from the LAMOST DR2 catalog. We perform two-step membership identification: selection along the stellar track in the color-magnitude diagram, i.e., photometric identification, and the selection from the distribution of radial velocities, i.e. the kinematic identification. We find that the radial velocity from the LAMOST data are very helpful in the membership identification. The mean probability of membership is 40\% for the radial velocity selected sample. With these 24 star clusters, we investigate the performance of the radial velocity and metallicity estimated in the LAMOST pipeline. We find that the systematic offset in radial velocity and metallicity are $0.85\pm1.26$\,\kms\ and $-0.08\pm0.04$\,dex, with dispersions of $5.47_{-0.71}^{+1.16}$\,\kms\ and $0.13_{-0.02}^{+0.04}$\,dex, respectively. Finally, we propose that the photometric member candidates of the clusters covered by the LAMOST footprints should be assigned higher priority so that more member stars can be observed.

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arXiv2015

Spectral classification of stars based on LAMOST spectra

In this work, we select the high signal-to-noise ratio spectra of stars from the LAMOST data andmap theirMK classes to the spectral features. The equivalentwidths of the prominent spectral lines, playing the similar role as the multi-color photometry, form a clean stellar locus well ordered by MK classes. The advantage of the stellar locus in line indices is that it gives a natural and continuous classification of stars consistent with either the broadly used MK classes or the stellar astrophysical parameters. We also employ a SVM-based classification algorithm to assignMK classes to the LAMOST stellar spectra. We find that the completenesses of the classification are up to 90% for A and G type stars, while it is down to about 50% for OB and K type stars. About 40% of the OB and K type stars are mis-classified as A and G type stars, respectively. This is likely owe to the difference of the spectral features between the late B type and early A type stars or between the late G and early K type stars are very weak. The relative poor performance of the automatic MK classification with SVM suggests that the directly use of the line indices to classify stars is likely a more preferable choice.

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arXiv2014

Asteroseismic based estimation of the surface gravity for the LAMOST giant stars

Asteroseismology is one of the most accurate approaches to estimate the surface gravity of a star. However, most of the data from the current spectroscopic surveys do not have asteroseismic measurements, which is very expensive and time consuming. In order to improve the spectroscopic surface gravity estimates for a large amount of survey data with the help of the small subset of the data with seismic measurements, we set up a support vector regression model for the estimation of the surface gravity supervised by 1,374 LAMOST giant stars with Kepler seismic surface gravity. The new approach can reduce the uncertainty of the estimates down to about 0.1 dex, which is better than the LAMOST pipeline by at least a factor of 2, for the spectra with signal-to-noise ratio higher than 20. Compared with the logg estimated from the LAMOST pipeline, the revised logg values provide a significantly improved match to the expected distribution of red clump and RGB stars from stellar isochrones. Moreover, even the red bump stars, which extend to only about 0.1 dex in logg, can be discriminated from the new estimated surface gravity. The method is then applied to about 350,000 LAMOST metal-rich giant stars to provide improved surface gravity estimates. In general, the uncertainty of the distance estimate based on the SVR surface gravity can be reduced to about 12% for the LAMOST data.

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arXiv2014

The K giant stars from the LAMOST survey data I: identification, metallicity, and distance

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about 2 million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with uncertainty of $0.13\sim0.29$\,dex based on the equivalent widths of Mg$_{\rm b}$ and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at $K=11$\,mag, which is the median brightness of the K giant sample, is about 0.6\,mag, corresponding to $\sim30$% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample. Moreover, at about 80\,kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.

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arXiv2013

DA white dwarfs observed in LAMOST pilot survey

A total of $\sim640,000$ objects from LAMOST pilot survey have been publicly released. In this work, we present a catalog of DA white dwarfs from the entire pilot survey. We outline a new algorithm for the selection of white dwarfs by fitting S\'ersic profiles to the Balmer H$\beta$, H$\gamma$ and H$\delta$ lines of the spectra, and calculating the equivalent width of the CaII K line. 2964 candidates are selected by constraining the fitting parameters and the equivalent width of CaII K line. All the spectra of candidates are visually inspected. We identify 230 (59 of them are already in Villanova and SDSS WD catalog) DA white dwarfs, 20 of which are DA white dwarfs with non-degenerate companions. In addition, 128 candidates are classified as DA white dwarf/subdwarfs, which means the classifications are ambiguous. The result is consistent with the expected DA white dwarf number estimated based on the LEGUE target selection algorithm.

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