Related papers: Confidence limits of evolutionary synthesis models…
Mass changes due to strong stellar winds and binary mass transfer have a dramatic impact on the consequent evolution of stars. This is generally not accounted for in population synthesis codes which are built using single star evolution…
Evolutionary population synthesis models for a wide range of metallicities, ages, star formation histories, and Horizontal Branch morphologies, including blue morphologies at high metallicity, are computed. The energetics of the post Main…
We discuss the systematic uncertainties inherent to analyses of observed (broad-band) Spectral Energy Distributions (SEDs) of star clusters with evolutionary synthesis models. We investigate the effects caused by restricting oneself to a…
A version of the STARS stellar evolution code has been developed that uses a non-simultaneous solution of the equations of stellar structure and evolution. In all other respects it is identical to the normal, fully simultaneous version. It…
We describe a method for removing the numerical errors in the modeling of linear evolution equations that are caused by approximating the time derivative by a finite difference operator. The method is based on integral transforms realized…
Since the early 1970s, stellar population modelling has been one of the basic tools for understanding the physics of unresolved systems from observation of their integrated light. Models allow us to relate the integrated spectra (or…
Context: Internal chemical mixing in intermediate- and high-mass stars represents an immense uncertainty in stellar evolution models.In addition to extending the main-sequence lifetime, chemical mixing also appreciably increases the mass of…
Integrated light from distant galaxies is often compared to stellar population models via the equivalent widths of spectral features--spectral indices--whose strengths rely on the abundances of one or more elements. Such comparisons hinge…
Context. The emergence of mixed modes during the subgiant phase, whose frequencies are characterized by a fast evolution with age, can potentially enable a precise determination of stellar properties, a key goal for future missions like…
Machine learning models are increasingly trained or fine-tuned on synthetic data. Recursively training on such data has been observed to significantly degrade performance in a wide range of tasks, often characterized by a progressive drift…
Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and…
One-zone Galactic Chemical Evolution (GCE) models have provided useful insights on a great wealth of average abundance patterns in many environments, especially for the Milky Way and its satellites. However, the scatter of such abundance…
We present a large and updated stellar evolution database for low-, intermediate- and high-mass stars in a wide metallicity range, suitable for studying Galactic and extragalactic simple and composite stellar populations using population…
Evolved stars dominate galactic spectra, enrich the galactic medium, expand to change their planetary systems, eject winds of a complex nature, produce spectacular nebulae and illuminate them, and transfer material between binary…
Synthesis models predict the integrated properties of stellar populations. Several problems exist in this field, mostly related to the fact that integrated properties are distributed. To date, this aspect has been either ignored (as in…
Mass loss and variability are two linked, fundamental properties of evolved stars. In this paper I review our current understanding of these processes, with a particular focus on how observations and models are used to constrain reliable…
We briefly review some constraints (Owing to the limited number of pages of present review, only a sub-sample of the topics discussed during the talk are briefly summarized. For the interested readers we are pleased to send them upon…
In terms of statistical fluctuations, stellar population synthesis models are only asymptotically correct in the limit of a large number of stars, where sampling errors become asymptotically small. When dealing with stellar clusters,…
The predictability problem for systems with different characteristic time scales is investigated. It is shown that even in simple chaotic dynamical systems, the leading Lyapunov exponent is not sufficient to estimate the predictability…
The stochastic interpolant framework offers a powerful approach for constructing generative models based on ordinary differential equations (ODEs) or stochastic differential equations (SDEs) to transform arbitrary data distributions.…