相关论文: Exploring galactic properties with machine learnin…
All-sky radio surveys are set to revolutionise the field with new discoveries. However, the vast majority of the tens of millions of radio galaxies won't have the spectroscopic redshift measurements required for a large number of science…
It has recently been demonstrated that one can accurately derive galaxy morphology from particular primary and secondary isophotal shape estimates in the Sloan Digital Sky Survey imaging catalog. This was accomplished by applying Machine…
We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC…
The ultraviolet (UV) to sub-millimetre (submm) spectral energy distribution of galaxies can be roughly divided into two sections: the stellar emission (attenuated by dust) at UV to near-infrared wavelengths and dust emission at longer…
We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an…
The identification of physically associated kiloparsec-scale quasar pairs is important for understanding galaxy evolution, the growth of supermassive black holes, and their co-evolution with host galaxies. However, their rarity and the high…
In this paper, we test the age matching hypothesis that the star formation rate (SFR) of a galaxy of fixed stellar mass is determined by its dark matter halo formation history, and as such, that more quiescent galaxies reside in older…
We present the results of various automated classification methods, based on machine learning (ML), of objects from data releases 6 and 7 (DR6 and DR7) of the Sloan Digital Sky Survey (SDSS), primarily distinguishing stars from quasars. We…
Mass ($M$) and luminosity ($L$) are fundamental parameters of stars but can only be measured indirectly. Typically, effective temperature ($T_{\rm eff}$), surface gravity (${\rm log}\ g$) and metallicity ([M/H]) are derived from stellar…
We review theoretical approaches to the study of galaxy formation, with emphasis on the role of hydrodynamic simulations in modeling the high redshift galaxy population. We present new predictions for the abundance of star-forming galaxies…
We used near-infrared integral field spectroscopic observations from the AMAZE and LSD programs to constrain the metallicity in a sample of 40 star forming galaxies at 3<z<5 (most of which at z~3.4). We measure metallicities by exploiting…
In recent years, machine learning (ML) algorithms have been successfully employed in Astronomy for analyzing and interpreting the data collected from various surveys. The need for new robust and efficient data analysis tools in Astronomy is…
We present a new method of predicting the ages of galaxies using a machine learning (ML) algorithm with the goal of providing an alternative to traditional methods. We aim to match the ability of traditional models to predict the ages of…
We present analyses of data augmentation for machine learning redshift estimation. Data augmentation makes a training sample more closely resemble a test sample, if the two base samples differ, in order to improve measured statistics of the…
Large galaxy surveys have demonstrated that galaxy-galaxy mergers can dramatically change the morphologies, star formation rates (SFRs) and metallicities of their constituents. However, most statistical studies have been limited to the…
Machine learning (ML) has become a key tool in astronomy, driving advancements in the analysis and interpretation of complex datasets from observations. This article reviews the application of ML techniques in the identification and…
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z's). A wide plethora of methods have been developed, based either on template models fitting or on empirical…
Using the most recent measurements of the ultraviolet (UV) luminosity functions (LFs) and dust estimates of early galaxies, we derive updated dust-corrected star-formation rate functions (SFRFs) at z~4-8, which we model to predict the…
Knowledge of stellar atmospheric parameters ($T_{\rm eff}$, $\log{g}$, [Fe/H]) of M dwarfs can be used to constrain both theoretical stellar models and Galactic chemical evolutionary models, and guide exoplanet searches, but their…
The spectra of emission-line galaxies (ELGs) from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digit Sky Survey (SDSS) are used to study the mass-metallicity relation (MZR) at $z\sim0.8$. The selected sample…