Daily Papers

We present a novel approach for identifying members of open star clusters using Gaia DR3 data by combining Minimum Spanning Tree (MST) and Gaussian Mixture Model (GMM) techniques. Our method employs a three-step process: initial filtering based on astrometric parameters, MST analysis for spatial distribution filtering, and GMM for final membership probability determination. We tested this methodology on 12+1 open clusters of varying ages, distances, and richness. The method demonstrates superior performance in distinguishing cluster members from field stars, particularly in regions with overlapping populations, as evidenced by its application to clusters like NGC 7790. By effectively reducing the number of probable field stars through MST analysis before applying GMM, our approach enhances both computational efficiency and membership determination accuracy. The results show strong agreement with previous studies while offering improved precision in member identification. This method provides a robust framework for analyzing the extensive datasets provided by Gaia DR3, addressing the challenges of processing large-scale astronomical data while maintaining high accuracy in cluster membership determination.

Axion-like particles (ALPs) are hypothetical pseudoscalar bosons, natural in extensions of the Standard Model. Their interactions with ordinary matter and radiation are suppressed, making it challenging to detect them in laboratory experiments. However, these particles, produced within stellar interiors, can provide an additional mechanism for energy loss, potentially influencing stellar evolution. Prominent methods for searching for such effects involve measuring the properties of red giants and helium-burning stars in globular clusters (GCs). Here we use published catalogs of stars selected as members of seven GCs on the basis of parallaxes and proper motions measured by Gaia (Data Realease 3). Making use of previously derived theoretical relations and the new data, we find the upper limit on the ALP-electron coupling, g_{ae}<5.2*10^{-14} (95% CL), and an indication (3.3 sigma) to nonzero ALP-photon coupling, g_{a\gamma}=(6.5+1.1-1.3)*10^{-11} GeV^{-1}. Given the precision of contemporary observational data, it is imperative to refine ALP constraints through more sophisticated analyses, which will be explored in detail elsewhere.

The Pleiades is the most prominent open star cluster visible from Earth and an important benchmark for simple stellar populations, unified by common origin, age, and distance. Binary stars are its essential ingredient, yet their contribution remains uncertain due to heavy observational biases. A resolved multiplicity survey was conducted for a magnitude-limited G < 15mag sample of 423 potential cluster members, including sources with poorly fitted astrometric solutions in Gaia DR3. Speckle interferometric observations at the 2.5 meter telescope of SAI MSU observatory were combined with Gaia data, enabling the identification of 61 resolved binary or multiple systems within the 0.04 - 10 arcsec (5 - 1350 au) separation range. With speckle observations, we discovered 21 components in 20 systems. The existence of a Merope (23 Tau) companion is confirmed after several previous unsuccessful attempts. We show that the Gaia multipeak fraction is a strong predictor of subarcsecond multiplicity, as all sources with ipd_frac_multi_peak > 4% are successfully resolved. We found that 10% of Pleiades stars have a companion with a mass ratio q > 0.5 within projected separation of 27 < s < 1350 au, and confirm a deficit of wide binaries with s > 300 au. An observed dearth of wide pairs with large mass ratio (q > 0.55) may imprint the transition from hard to soft binaries regime at the early stages of cluster evolution. The total binary fraction for q > 0.5 systems is extrapolated to be around 25%.

Most of the stars in the Universe are M spectral class dwarfs, which are known to be the source of bright and frequent stellar flares. In this paper, we propose new approaches to discover M-dwarf flares in ground-based photometric surveys. We employ two approaches: a modification of a traditional method of parametric fit search and a machine learning algorithm based on active anomaly detection. The algorithms are applied to Zwicky Transient Facility (ZTF) data release 8, which includes the data from the ZTF high-cadence survey, allowing us to reveal flares lasting from minutes to hours. We analyze over 35 million ZTF light curves and visually scrutinize 1168 candidates suggested by the algorithms to filter out artifacts, occultations of a star by an asteroid, and other types of known variable objects. The result of this analysis is the largest catalogue of ZTF flaring stars to date, representing 134 flares with amplitudes ranging from -0.2 to -4.6 magnitudes, including repeated flares. Using Pan-STARRS DR2 colors, we assign a spectral subclass to each object in the sample. For 13 flares with well-sampled light curves and available geometric distances from Gaia DR3, we estimate the bolometric energy. This research shows that the proposed methods combined with the ZTF's cadence strategy are suitable for identifying M-dwarf flares and other fast transients, allowing for the extraction of significant astrophysical information from their light curves.

We estimate ([M/H], [alpha/M]) for 48 million giants and dwarfs in low-dust extinction regions from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 and metal-poor star sample from Li et al. The root mean square error of our estimation is 0.0890 dex for [M/H] and 0.0436 dex for [alpha/M], when we evaluate our models on the test data that are not used in training the models. Because the training data is dominated by giants, our estimation is most reliable for giants. The high-[alpha/M] stars and low-[alpha/M] stars selected by our ([M/H], [alpha/M]) show different kinematical properties for giants and low-temperature dwarfs. We further investigate how our machine-learning models extract information on ([M/H], [alpha/M]). Intriguingly, we find that our models seem to extract information on [alpha/M] from Na D lines (589 nm) and Mg I line (516 nm). This result is understandable given the observed correlation between Na and Mg abundances in the literature. The catalog of ([M/H], [alpha/M]) as well as their associated uncertainties are publicly available online.

In this work, we aim to estimate the stellar parameters of the primary (Aa) by performing asteroseismic analysis on its period-spacing pattern. We use the C-3PO neural network to perform asteroseismic modelling of the g-mode period-spacing pattern of Aa, discussing the interplay of this information with external constraints from spectroscopy (T_{rm eff} and log(g)) and eclipse modelling (R). To estimate the level of uncertainty due to different frequency extraction and pattern identification processes, we consider four different variations on the period-spacing patterns. To better understand the correlations between and the uncertainty structure of our parameter estimates, we also employed a classical, parameter-based MCMC grid search on four different stellar grids. The best-fitting, externally constrained model to the period-spacing pattern arrives at estimates of the stellar properties for Aa of: M=1.51 pm 0.05 M_odot, X_c =0.43 pm 0.04, R=1.66 pm 0.1 R_odot, f_{rm ov}=0.010, Omega_c=1.58 pm 0.01 d^{-1} with rigid rotation to within the measurement errors, log(T_{rm eff})=3.856 pm 0.008 dex, log(g)=4.18 pm 0.04 dex, and log(L)=0.809 pm 0.005 dex, which agree well with previous measurements from eclipse modelling, spectroscopy, and the Gaia DR3 luminosity. We find that the near-core properties of the best-fitting asteroseismic models are consistent with external constraints from eclipse modelling and spectroscopy. Aa appears to be a typical example of a gamma Dor star, fitting well within existing populations. We find that Aa is quasi-rigidly rotating to within the uncertainties, and note that the asteroseismic age estimate for Aa (1100 pm 100 Myr) is considerably older than the young (35 Myr) age implied by previous isochrone fits to the B binary in the literature. Our MCMC parameter-based grid-search agrees well with our pattern-modelling approach.