Related papers: Error analysis for stellar population synthesis as…
Stellar population synthesis (SPS) models are a key tool for deriving the age, metallicity, radial velocity and reddening of star clusters from their integrated spectra. Using a sample of 129 star clusters with high-quality spectra, we…
Understanding stellar composition is fundamental not only to our comprehension of the galaxy, especially chemical evolution, but it can also shed light on the interior structure and mineralogy of exoplanets, which are formed from the same…
It is well known that, when analyzed at the light of current synthesis model predictions, variations in the physical properties of single stellar populations (e.g. age, metallicity, initial mass function, element abundance ratios) may have…
Stellar fundamental properties (masses, radii, effective temperatures) can be extracted from observations of eclipsing binary systems with remarkable precision, often better than 2%. Such precise measurements afford us the opportunity to…
We present a novel statistical algorithm, Stellar Ages, which currently infers the age, metallicity, and extinction posterior distributions of stellar populations from their magnitudes. While this paper focuses on these parameters, the…
Decision analysis deals with modeling and enhancing decision processes. A principal challenge in improving behavior is in obtaining a transparent description of existing behavior in the first place. In this paper, we develop an expressive,…
Exoplanet surveys have revealed a wide diversity of planetary systems, requiring integrated models of planet formation to explain their origin. Planet population synthesis (PPS) modelling is a key tool for linking theory with the…
We develop techniques to solve ill-posed inverse problems on the sphere by sparse regularisation, exploiting sparsity in both axisymmetric and directional scale-discretised wavelet space. Denoising, inpainting, and deconvolution problems,…
Combining multiple events into population analyses is a cornerstone of gravitational-wave astronomy. A critical component of such studies is the assumed population model, which can range from astrophysically motivated functional forms to…
The focus of this book is on the analysis of regularization methods for solving \emph{nonlinear inverse problems}. Specifically, we place a strong emphasis on techniques that incorporate supervised or unsupervised data derived from prior…
During the last few years, the Geneva stellar evolution group has released new grids of stellar models, including the effect of rotation and with updated physical inputs (Ekstr\"om et al. 2012; Georgy et al. 2013a,b). To ease the comparison…
We present a new method for detecting and correcting systematic errors in the distances to stars when both proper motions and line-of-sight velocities are available. The method, which is applicable for samples of 200 or more stars that have…
In this paper we cover a few topics on how to treat inverse problems. There are two different flows of ideas. One approach is based on Morse Lemma. The other is based on analyticity which proves that the number of solutions to the inverse…
Context. Existing samples of strong lenses have been assembled by giving priority to sample size, at the cost of having a complex selection function. With the advent of the next generation of wide-field photometric surveys, however, it…
We summarize the principles and fundamental ingredients of evolutionary synthesis models, which are stellar evolution, stellar atmospheres, the IMF, star-formation histories, nebular emission, and also attenuation from the ISM and IGM. The…
Recent advances in stellar population modelling and avalanches of data from mega-surveys have revived the interest in techniques to extract information about galaxy evolution from integrated spectra. This contribution provides an informal…
Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundamental level. Producing thousands of such models requires hundreds of CPU hours, but…
Inverse imaging problems that are ill-posed can be encountered across multiple domains of science and technology, ranging from medical diagnosis to astronomical studies. To reconstruct images from incomplete and distorted data, it is…
Inverse problems involve making inference about unknown parameters of a physical process using observational data. This paper investigates an important class of inverse problems -- the estimation of the initial condition of a…
Big data presents potential but unresolved value as a source for analysis and inference. However,selection bias, present in many of these datasets, needs to be accounted for so that appropriate inferences can be made on the target…