arXiv subjects

E. Reggiani

Publications and source records attributed to E. Reggiani.

4 recordsLinked to original sources

arXiv2026

Survey of Surveys Data Release 3. Homogenised stellar parameters across nine spectroscopic surveys

Large spectroscopic surveys have measured atmospheric parameters for millions of Milky Way stars, but differences in instruments, wavelength ranges, analysis methods, and assumptions introduce survey-dependent systematics that complicate their joint use. We aim to place effective temperature, surface gravity, and metallicity estimates from major spectroscopic surveys onto a common, externally validated scale, and to provide a homogenised catalogue for large-scale Galactic studies. We construct the calibration hierarchically. We first define an internal reference scale from the best-populated and best-overlapped surveys (APOGEE, GALAH, and LAMOST LRS), and model survey-to-reference corrections and their uncertainties with machine-learning regression. The scale is then extended to LAMOST MRS, Gaia RVS, RAVE, DESI, Gaia-ESO, and SEGUE, and anchored to high-quality measurements from the PASTEL database. The calibration reduces survey-to-survey offsets and improves consistency in independent overlap samples: independent calibration of GALAH and LAMOST LRS temperatures onto the APOGEE scale reduces their median offset from 44.5 K to 6.2 K. The final catalogue contains about 10.13 million stars, including 6.10 million in the recommended high-quality subset and 3.69 million in the metallicity-optimised subset. For the high-quality subset, Gaia benchmark stars give median residuals of 30 K in $T_{\rm eff}$, 0.03 dex in $\log g$, and $-0.02$ dex in [Fe/H]. The [Fe/H]-optimised subset gives median residuals of 0.003 dex against Gaia benchmark stars, 0.05 dex for globular clusters, and $-0.02$ dex for open clusters. As an example application, we confirm the presence of metal-poor stars on thin-disc-like orbits, including stars with [Fe/H] $< -2$, showing that the catalogue can be used to study rare Galactic populations on a consistent multi-survey scale.

astro-ph.SR↗

arXiv2026

Detailed chemo-dynamical characterization of four elusive Milky Way star clusters

A variety of faint and observationally challenging stellar systems has been discovered in the Milky Way in the last decades. Unveiling their kinematic and chemical properties is crucial to understand their nature and to assess their role in the history of our Galaxy. In this paper, we present a chemo-dynamical analysis of four elusive stellar systems (BH 140, Garro 01, BLISS 1, and Kim 3) using spectra collected with the X-shooter medium-resolution spectrograph at the VLT. We derived precise line-of-sight velocities and chemical abundances for all targets. Specifically, we provide the first spectroscopic characterization of metallicity and α-element content for BH 140, the first comprehensive chemical characterization for BLISS 1 and Garro 01, and the first spectroscopic metallicity determination for Kim 3. BH 140, Garro 01 and BLISS 1 are relatively metal-rich systems with [Fe/H] ~ -0.7 dex and have enhanced α-element abundances, whereas Kim 3 is notably metal-poor with [Fe/H] ~ -1.8 dex. We also performed an orbital analysis to investigate their origin as accreted or in situ systems. We found that Garro 01 and BH 140 have orbits confined within < 1.5 kpc from the Galactic plane, the former having also a remarkably circular orbit. They were likely born in situ, although the high orbital eccentricity of BH 140 and its mild deficiency in α-elements leave other possibilities open. Although undoubtedly accreted, BLISS 1 does not exhibit a clear dynamical association with any known progenitor, lying in a high energy (E) - high vertical angular momentum (LZ ) prograde orbit reaching a maximum height from the Galactic plane of zmax ~ 8 kpc. Its chemical properties seem to favor an in situ origin, which might be connected with the Aleph sub-structure. Finally, we tentatively link the high energy and low LZ orbit of Kim 3 to the Elqui stream.

astro-ph.GA↗

arXiv2026

The role of mass transfer efficiency in stability criteria: Implementation in SEVN and a test on blue stragglers and binary compact objects

Context: The stability of mass transfer through Roche-lobe overflow plays a key role in shaping the outcome of binary interactions. However, the criterion for mass transfer stability remains one of the main open questions in the theory of binary evolution. Aims: We develop a mass transfer stability prescription that accounts for mass and angular momentum loss, and implement it in the population synthesis code SEVN. We assess its impact relative to the standard formalism used in SEVN, using blue stragglers and binary compact objects as illustrative cases. Methods: We derive an expression for the response of the Roche-lobe radius to mass loss in the general case where the mass and angular momentum of the system are not conserved. On the basis of this formulation, we construct a new mass transfer stability criterion that modifies the standard approach only through the Roche-lobe response term. Results: Population synthesis simulations with SEVN show that the new criterion allows stable mass transfer in binaries with higher donor-to-accretor mass ratios, leading to an overall increase in the predicted number of blue stragglers and promoting their formation in wider orbits. This contributes to reconciling the differences between theory and observations. For binary compact objects, the impact of the new stability criterion varies across system types, with the strongest effects occurring in binaries containing at least one neutron star. In particular, for low mass transfer efficiency, the new criterion enhances the contribution of channels involving stable mass transfer and leads to a larger number of systems, including gravitational wave progenitors. Conclusion: The inclusion of a new, simple, yet more consistent prescription for mass transfer stability has proven that refining this criterion can significantly improve our understanding of the formation channels of specific stellar populations.

astro-ph.SR↗

arXiv2025

Survey of Surveys. II. Stellar parameters for 23 millions of stars

In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a project to critically compile survey results in a single catalogue, facilitating the scientific use of the available information. In this second release, we present two new catalogs of stellar parameters (Teff, logg, and [Fe/H]). To build the first catalog, SoS-Spectro, we calibrated internally and externally stellar parameters from five spectroscopic surveys (APOGEE, GALAH, Gaia-ESO, RAVE, and LAMOST) and externally on the PASTEL database. The second catalog, SoS-ML catalog, is obtained by using SoS-Spectro as a reference to train a multi-layer perceptron, which predicts stellar parameters based on two photometric surveys, SDSS and SkyMapper. As a novel approach, we build on previous parameters sets, from Gaia DR3 and Andrae et al. (2023), aiming to improve their precision and accuracy. We obtain a catalog of stellar parameters for around 23 millions of stars, which we make publicly available. We validate our results with several comparisons with other machine learning catalogs, stellar clusters, and astroseismic samples. We find substantial improvements in the parameters estimates compared to other Machine Learning methods in terms of precision and accuracy, especially in the metal-poor range, as shown in particular when validating our results with globular clusters. We believe that there are two reasons behind our improved results at the low-metallicity end: first, our use of a reference catalog, the SoS-Spectro, which is calibrated using high-resolution spectroscopic data; and second, our choice to build on pre-existing parameter estimates from em Gaia and Andrae et al., rather than attempting to obtain our predictions from survey data alone.

astro-ph.SR↗