Related papers: Data-driven derivation of stellar properties from …
The development of evolutionary stellar population models is central to interpreting observations of galaxies in terms of astrophysical quantities. Stellar population models must therefore be both accurate and compatible with inversion…
The recent UNCOVER survey with the James Webb Space Telescope (JWST) exploits the nearby cluster Abell 2744 to create the deepest view of our universe to date by leveraging strong gravitational lensing. In this work, we perform photometric…
Stellar flares are abundant in space photometric light curves. As they are now available in large enough numbers, the statistical study of their overall temporal morphology is timely. We use light curves from the Transiting Exoplanet Survey…
We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…
For a galaxy, given its observed rotation curve, can one directly infer parameters of the dark matter density profile (such as dark matter particle mass $m$, scaling parameter $s$, core-to-envelope transition radius $r_t$ and NFW scale…
Over the last two decades, machine learning models have been widely applied and have proven effective in classifying variable stars, particularly with the adoption of deep learning architectures such as convolutional neural networks,…
Stellar surface processes represent a fundamental limit to the detection of extrasolar planets with the currently most heavily-used techniques. As such, considerable effort has gone into trying to mitigate the impact of these processes on…
The dynamics of flexible filaments entrained in flow, important for understanding many biological and industrial processes, are computationally expensive to model with full-physics simulations. This work describes a data-driven technique to…
Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of…
We present a unified framework to derive fundamental stellar parameters by combining all available observational and theoretical information for a star. The algorithm relies on the method of Bayesian inference, which for the first time…
Continuous high-precision photometry of stars, provided by space missions such as CoRoT, Kepler, and K2, represents a unique way to study stellar rotation and magnetism. The coupling of these studies of the surface dynamics with…
We study the photometric properties of stars in the data archive of the Sloan Digital Sky Survey (SDSS), the prime aim being to understand the photometric calibration over the entire data set. It is confirmed that the photometric…
We present a new method for inferring photometric redshifts in deep galaxy and quasar surveys, based on a data driven model of latent spectral energy distributions (SEDs) and a physical model of photometric fluxes as a function of redshift.…
Abstract abridged. Eclipsing binary systems provide the opportunity to measure the fundamental parameters of their component stars in a stellar-model-independent way. This makes them ideal candidates for testing and calibrating theories of…
The catalog of stellar evolution tracks discussed in our previous work is meant to help characterize exoplanet host-stars of interest for follow-up observations with future missions like JWST. However, the utility of the catalog has been…
Space-based projects are providing a wealth of high-quality asteroseismic data, including frequencies for a large number of stars showing solar-like oscillations. These data open the prospect for precise determinations of key stellar…
This article reviews our current understanding of modelling convection dynamics in stars. Several semi-analytical time-dependent convection models have been proposed for pulsating one-dimensional stellar structures with different…
We present a new approach to constrain galaxy physical parameters from the combined interpretation of stellar and nebular emission in wide ranges of observations. This approach relies on the Bayesian analysis of any type of galaxy spectral…
Relations between stellar properties independent of the nuclear equation of state offer profound insights into neutron star physics and have practical applications in data analysis. Commonly, these relations are derived from utilizing…
Accurately determining the properties of stars is of prime importance for characterizing stellar populations in our Galaxy. The field of asteroseismology has been thought to be particularly successful in such an endeavor for stars in…