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Xue Lu

Publications and source records attributed to Xue Lu.

5 recordsLinked to original sources

Photometric Metallicities for 367,324 stars of Omega Centauri

Omega Centauri is the most massive and chemically complex multi-population globular cluster with a wide metallicity range that has been extensively studied photometrically and spectroscopically. Using the wide metallicity range of omega Cen, HST photometry (F275W, F336W, F435W, F625W), and MUSE spectroscopy ([M/H]), we derive [M/H]- and M_{F625W}-dependent stellar loci to estimate photometric metallicities from HST colors. Our tests yield metallicity precisions of 0.10\,dex for giants and 0.22\,dex for fainter dwarfs. We construct a photometric metallicity catalog from simultaneous F336W, F435W, and F625W observations (plus F275W where available), containing 20,778 giants and 346,546 dwarfs. A subsample of 20,533 giants is used to study the spatial metallicity distribution and gradient. We find no significant metallicity gradient within the half-light radius, consistent with previous work. Moreover, the previously reported ring-like structure is less pronounced in our data, and no physically significant, irregular two-dimensional metallicity pattern is detected, indicating that the stellar subpopulations are well mixed within the half-light radius. Our catalog significantly extends the metallicity sample of omega Cen, and this approach can be applied to other HST data to estimate photometric metallicities.

astro-ph.SR

Stellar Loci. IX. Estimation of Stellar Parameters from CSST-like Photometry

The China Space Station Telescope (CSST) will conduct a deep and wide imaging survey in the NUV-, u-, g-, r-, i-, z-, and y-bands. In this work, using theoretical data synthesized from the BOSZ spectra of Bohlin et al. (2017), along with observational data constructed from different sources, we present two methods for estimating stellar parameters from CSST-like photometry. One approach is to estimate metallicity [M/H] and surface gravity log g simultaneously by using the metallicity- and log g-dependent stellar loci. Tests with theoretical data (without photometric errors) result in precisions of 0.088 dex and 0.083 dex for [M/H] and log g, respectively. With 0.01 mag photometric errors, precision is degraded by about a factor of two, due to degeneracy in [M/H] and log g. Tests with observational data, although with larger photometric errors, result in precisions of 0.10 dex and 0.39 dex for [Fe/H] and log g, respectively, thanks to the strong correlation between stellar colors and log g in real data. The other approach is the giant-dwarf loci method to obtain classifications and metallicity estimates. With the same observational data, it achieves a better [Fe/H] precision of 0.084 dex, due to the stronger constraints imposed on log g. The method also performs well in distinguishing giants from dwarfs, particularly for red or metal-poor giants. This work demonstrates the clear potential of the CSST data, paving the way for stellar-parameter estimates for many billions of stars.

astro-ph.SR

Filter Design for Estimation of Stellar Metallicity: Insights from Experiments with Gaia XP Spectra

We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright ($G \sim 11.5$) stars is excellent, $\sigma_{\rm [Fe/H]} = 0.034$\,dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper\,$v$). By selecting hundreds of high-probabability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036\,dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters.

astro-ph.SR

Stellar Loci. VII. Photometric Metallicities of 5 Million FGK Stars Based on GALEX GR6+7 AIS and Gaia EDR3

We combine photometric data from GALEX GR6+7 AIS and Gaia EDR3 with stellar parameters from the SAGA and PASTEL catalogs to construct high-quality training samples for dwarfs ($\rm 0.4< BP-RP<1.6$) and giants ($\rm 0.6< BP-RP <1.6$). We apply careful reddening corrections using empirical temperature- and extinction-dependent extinction coefficients. Using the two samples, we establish a relationship between stellar loci (NUV$-$BP vs. BP$-$RP colors), metallicity, and $\rm M_G$. For a given BP$-$RP color, a 1 dex change in [Fe/H] corresponds to an approximately 1 magnitude change in NUV$-$BP color for solar-type stars. These relationships are employed to estimate metallicities based on NUV$-$BP, BP$-$RP, and $\rm M_G$. Thanks to the strong metallicity dependence in the GALEX NUV-band, our models enable a typical photometric-metallicity precision of approximately $\sigma_{\rm [Fe/H]}$ = 0.11 dex for dwarfs and $\sigma_{\rm [Fe/H]}$ = 0.17 dex for giants, with an effective metallicity range extending down to [Fe/H] $= -3.0$ for dwarfs and [Fe/H] $= -4.0$ for giants. We also find that the NUV-band based photometric-metallicity estimate is not as strongly affected by carbon enhancement as previous photometric techniques. With the Gaia and GALEX data, we have estimated metallicities for about 5 million stars across almost the entire sky, including approximately 4.5 million dwarfs and 0.5 million giants. This work demonstrates the potential of the NUV-band for estimating photometric metallicities, and sets the groundwork for utilizing the NUV data from space telescopes such as the upcoming Chinese Space Station Telescope.

astro-ph.SR

On Adaptive Estimation for Dynamic Bernoulli Bandits

The multi-armed bandit (MAB) problem is a classic example of the exploration-exploitation dilemma. It is concerned with maximising the total rewards for a gambler by sequentially pulling an arm from a multi-armed slot machine where each arm is associated with a reward distribution. In static MABs, the reward distributions do not change over time, while in dynamic MABs, each arm's reward distribution can change, and the optimal arm can switch over time. Motivated by many real applications where rewards are binary, we focus on dynamic Bernoulli bandits. Standard methods like $ε$-Greedy and Upper Confidence Bound (UCB), which rely on the sample mean estimator, often fail to track changes in the underlying reward for dynamic problems. In this paper, we overcome the shortcoming of slow response to change by deploying adaptive estimation in the standard methods and propose a new family of algorithms, which are adaptive versions of $ε$-Greedy, UCB, and Thompson sampling. These new methods are simple and easy to implement. Moreover, they do not require any prior knowledge about the dynamic reward process, which is important for real applications. We examine the new algorithms numerically in different scenarios and the results show solid improvements of our algorithms in dynamic environments.

stat.ML