arXiv subjects

Luca Tonietti

Publications and source records attributed to Luca Tonietti.

3 recordsLinked to original sources

arXiv2026

Phosphorus abundances and multi-element co-enrichment in nearby FGK stars

The distribution of bio-essential elements is key to assessing the chemical fertility of galactic environments. We analyse phosphorus abundances for 233 nearby FGK stars from the Hypatia Catalog, separating thin- and thick-disk populations. We study [P/Fe] as a function of [Fe/H] and other elemental abundances using non-parametric tests and bootstrap resampling, and we examine residual correlations at fixed [Fe/H] together with molar ratios involving P. We find a [P/Fe]-[Fe/H] trend broadly similar to that of alpha elements, supporting a dominant origin in core-collapse supernovae, while deviations point to additional nucleosynthetic channels. Phosphorus shows strong positive correlations with several CHNOPS, alpha, and Fe-peak elements, especially in the thin disk. These co-enrichment patterns remain significant at fixed [Fe/H], indicating that they are not a trivial consequence of global metallicity. Thin-disk stars are also more enriched than thick-disk stars in many elements. The solar P/Mg and P/Si ratios are representative of the local stellar population, whereas solar P/O is relatively elevated. Overall, phosphorus emerges as a tracer of genuine multi-element co-enrichment and of the chemical fertility of the solar neighbourhood.

astro-ph.SR↗

arXiv2025

DART-Vetter: A Deep LeARning Tool for automatic triage of exoplanet candidates

In the identification of new planetary candidates in transit surveys, the employment of Deep Learning models proved to be essential to efficiently analyse a continuously growing volume of photometric observations. To further improve the robustness of these models, it is necessary to exploit the complementarity of data collected from different transit surveys such as NASA's Kepler, Transiting Exoplanet Survey Satellite (TESS), and, in the near future, the ESA PLAnetary Transits and Oscillation of stars (PLATO) mission. In this work, we present a Deep Learning model, named DART-Vetter, able to distinguish planetary candidates (PC) from false positives signals (NPC) detected by any potential transiting survey. DART-Vetter is a Convolutional Neural Network that processes only the light curves folded on the period of the relative signal, featuring a simpler and more compact architecture with respect to other triaging and/or vetting models available in the literature. We trained and tested DART-Vetter on several dataset of publicly available and homogeneously labelled TESS and Kepler light curves in order to prove the effectiveness of our model. Despite its simplicity, DART-Vetter achieves highly competitive triaging performance, with a recall rate of 91% on an ensemble of TESS and Kepler data, when compared to Exominer and Astronet-Triage. Its compact, open source and easy to replicate architecture makes DART-Vetter a particularly useful tool for automatizing triaging procedures or assisting human vetters, showing a discrete generalization on TCEs with Multiple Event Statistic (MES) > 20 and orbital period < 50 days.

astro-ph.EP↗

arXiv2022

A systematic validation of hot Neptunes in TESS data

We statistically validated a sample of hot Neptune candidates applying a two-step vetting technique using DAVE and TRICERATOPS. We performed a systematic validation of 250 transit-like events in the Transiting Exoplanet Survey Satellite (TESS) archive in the parameter region defined by $P\leq 4$ d and $3R_\oplus\leq R\leq 5R_\oplus$. Through our analysis, we identified 18 hot Neptune-sized candidates, with a false positive probability $<50\%$. Nine of these planet candidates still need to be confirmed. For each of the nine targets we retrieved the stellar parameters using ARIADNE and derived constraints on the planetary parameters by fitting the lightcurves with the juliet package. Within this sample of nine candidates, we statistically validated (i.e, with false positive probability < $0.3\%$) two systems (TOI-277 b and TOI-1288 b) by re-processing the candidates with TRICERATOPS along with follow-up observations. These new validated exoplanets expand the known hot Neptunes population and are high-priority targets for future radial velocities follow-up.

astro-ph.EP↗