skip to main content


Title: Modelling stars with Gaussian Process Regression: augmenting stellar model grid
ABSTRACT

Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian Process (GP) Regression that turns a sparse model grid on to a continuous function. We train GP models to map five fundamental inputs (mass, equivalent evolutionary phase, initial metallicity, initial helium fraction, and the mixing-length parameter) to observable outputs (effective temperature, surface gravity, radius, surface metallicity, and stellar age). We test the GP predictions for the five outputs using off-grid stellar models and find no obvious systematic offsets, indicating good accuracy in predictions. As a further validation, we apply these GP models to characterize 1000 fake stars. Inferred masses and ages determined with GP models well recover true values within one standard deviation. An important consequence of using GP-based interpolation is that stellar ages are more precise than those estimated with the original sparse grid because of the full sampling of fundamental inputs.

 
more » « less
NSF-PAR ID:
10363770
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
Volume:
511
Issue:
4
ISSN:
0035-8711
Page Range / eLocation ID:
p. 5597-5610
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    Context. Magnetic fields influence the formation and evolution of stars and impact the observed stellar properties. magnetic A-type stars (Ap stars) are a prime example of this. Access to precise and accurate determinations of their stellar fundamental properties, such as masses and ages, is crucial to understand the origin and evolution of fossil magnetic fields. Aims. We propose using the radii and luminosities determined from interferometric measurements, in addition to seismic constraints when available, to infer fundamental properties of 14 Ap stars préviously characterised. Methods. We used a grid-based modelling approach, employing stellar models computed with the CESTAM stellar evolution code, and the parameter search performed with the AIMS optimisation method. The stellar model grid was built using a wide range of initial helium abundances and metallicities in order to avoid any bias originating from the initial chemical composition. The large frequency separations (Δ ν ) of HR 1217 (HD 24712) and α Cir (HD 128898), two rapidly oscillating Ap stars of the sample, were used as seismic constraints. Results. We inferred the fundamental properties of the 14 stars in the sample. The overall results are consistent within 1 σ with previous studies, however, the stellar masses inferred in this study are higher. This trend likely originates from the broader range of chemical compositions considered in this work. We show that the use of Δ ν in the modelling significantly improves our inferences, allowing us to set reasonable constraints on the initial metallicity which is, otherwise, unconstrained. This gives an indication of the efficiency of atomic diffusion in the atmospheres of roAp stars and opens the possibility of characterising the transport of chemical elements in their interiors. 
    more » « less
  2. ABSTRACT

    Magnetic fields can drastically change predictions of evolutionary models of massive stars via mass-loss quenching, magnetic braking, and efficient angular momentum transport, which we aim to quantify in this work. We use the mesa software instrument to compute an extensive main-sequence grid of stellar structure and evolution models, as well as isochrones, accounting for the effects attributed to a surface fossil magnetic field. The grid is densely populated in initial mass (3–60 M⊙), surface equatorial magnetic field strength (0–50 kG), and metallicity (representative of the Solar neighbourhood and the Magellanic Clouds). We use two magnetic braking and two chemical mixing schemes and compare the model predictions for slowly rotating, nitrogen-enriched (‘Group 2’) stars with observations in the Large Magellanic Cloud. We quantify a range of initial field strengths that allow for producing Group 2 stars and find that typical values (up to a few kG) lead to solutions. Between the subgrids, we find notable departures in surface abundances and evolutionary paths. In our magnetic models, chemical mixing is always less efficient compared to non-magnetic models due to the rapid spin-down. We identify that quasi-chemically homogeneous main sequence evolution by efficient mixing could be prevented by fossil magnetic fields. We recommend comparing this grid of evolutionary models with spectropolarimetric and spectroscopic observations with the goals of (i) revisiting the derived stellar parameters of known magnetic stars, and (ii) observationally constraining the uncertain magnetic braking and chemical mixing schemes.

     
    more » « less
  3. Context. Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process ( s -process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. Aims. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the F RUITY and Monash stellar models. Methods. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s -process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. Results. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = −0.21 and −0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns. 
    more » « less
  4. ABSTRACT

    Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

     
    more » « less
  5. ABSTRACT

    Using early-release data from the JWST, Mowla et al. and Claeyssens et al. recently measured various properties for gravitationally lensed compact sources (‘sparkles’) around the ‘Sparkler’ galaxy at a redshift of 1.378 (a look-back time of 9.1 Gyr). Here, we focus on the Mowla et al. as they were able to break the age-metallicity degeneracy and derive independent ages, metallicities, and extinctions for each source. They identified five metal-rich, old Globular cluster (GC) candidates (with formation ages up to ∼13 Gyr). We examine the age–metallicity relation (AMR) for the GC candidates and other Sparkler compact sources. The Sparkler galaxy, which has a current estimated stellar mass of 109 M⊙, is compared to the Large Magellanic Cloud (LMC), the disrupted dwarf galaxy Gaia–Enceladus and the Milky Way (MW). The Sparkler galaxy appears to have undergone very rapid chemical enrichment in the first few hundred Myr after formation, with its GC candidates similar to those of the MW’s metal-rich subpopulation. We also compare the Sparkler to theoretical AMRs and formation ages from the E-MOSAICS simulation, finding the early formation age of its GCs to be in some tension with these predictions for MW-like galaxies. The metallicity of the Sparkler’s star-forming regions are more akin to a galaxy of stellar mass ≥ 1010.5 M⊙, that is, at the top end of the expected mass growth over 9.1 Gyr of cosmic time. We conclude that the Sparkler galaxy may represent a progenitor of a MW-like galaxy, even including the ongoing accretion of a satellite galaxy.

     
    more » « less