Related papers: Prototype selection for parameter estimation in co…
The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This situation is indeed one that astronomers must contend with…
The star formation history (SFH) is a key issue in the evolution of galaxies. In this work, we developed a model based on a Gaussian and gamma function mixture to fit SFHs with varying numbers of components. Our primary objective was to use…
Global Stellar Formation Rates or SFRs are crucial to constrain theories of galaxy formation and evolution. SFR's are usually estimated via spectroscopic observations which require too much previous telescope time and therefore cannot match…
The spectral energy distribution (SED) of galaxies is essential for deriving fundamental properties like stellar mass and star formation history (SFH). However, conventional methods, including both parametric and non-parametric approaches,…
We adapt the L-Galaxies semi-analytic model to follow the star-formation histories (SFH) of galaxies -- by which we mean a record of the formation time and metallicities of the stars that are present in each galaxy at a given time. We use…
To study the effect of supermassive black holes (SMBHs) on their host galaxies it is important to study the hosts when the SMBH is near its peak activity. A method to investigate the host galaxies of high luminosity quasars is to obtain…
Star formation estimates based on the counting of YSOs is commonly applied to nearby star-forming regions in the Galaxy. With this method, the SFRs are measured using the counts of YSOs in a particular protostellar Class, a typical…
This paper investigates the problem of prediction of stellar parameters, based on the star's electromagnetic spectrum. The knowledge of these parameters permits to infer on the evolutionary state of the star. From a statistical point of…
We present a probabilistic formulation of the classical problem of synthesizing spectral properties of a galaxy using a base of star clusters. The problem consists of estimating the population vector x, composed by the contributions of…
The star formation histories (SFHs) of galaxies contain imprints of the physical processes responsible for regulating star formation during galaxy growth and quenching. We improve the Dense Basis SFH reconstruction method of Iyer & Gawiser…
The growth of sky surveys and the large amount of stellar spectra in the current databases, has generated the necessity of developing new methods to estimate atmospheric parameters, a fundamental task on stellar research. In this work we…
Large scale, deep survey missions such as GAIA will collect enormous amounts of data on a significant fraction of the stellar content of our Galaxy. These missions will require a careful optimisation of their observational systems in order…
We introduce a new methodology for the direct extraction of galaxy physical parameters from multi-wavelength photometry and spectroscopy. We use semi-analytic models that describe galaxy evolution in the context of large scale cosmological…
We investigate the optimal approach for recovering the star formation histories (SFHs) and spatial distribution of stellar mass in high-redshift galaxies ($z\sim 2-5$), focusing on the impact of assumed SFH models on derived galaxy…
As the reconstruction of the star-formation histories (SFH) of galaxies from spectroscopic data becomes increasingly popular, we explore the best age resolution achievable with stellar population synthesis (SPS) models, relying on different…
Understanding how and when galaxies formed stars over the history of the Universe is fundamental to the study of galaxy evolution. The star formation histories (SFHs) of galaxies in the local Universe can be measured with high precision…
We present a machine learning method to assign stellar parameters (temperature, surface gravity, metallicity) to the photometric data of large photometric surveys such as SDSS and SKYMAPPER. The method makes use of our previous effort in…
We present a new method to estimate the average star formation rate per unit stellar mass (SSFR) of a stacked population of galaxies. We combine the spectra of 600-1000 galaxies with similar stellar masses and parameterise the star…
The primary method for inferring the stellar mass ($M_*$) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history and dust attenuation law…
We present DiffstarPop, a differentiable forward model of cosmological populations of galaxy star formation histories (SFH). In the model, individual galaxy SFH is parametrized by Diffstar, which has parameters $\theta_{\rm SFH}$ that have…