相关论文: Multi-Layer Perceptron for Predicting Galaxy Param…

Astrochemical modelling of the interstellar medium typically makes use of complex computational codes with parameters whose values can be varied. It is not always clear what the exact nature of the relationship is between these input…

Galaxy morphology is a key parameter in galaxy evolution studies. The enormous number of galaxies which current and future surveys will observe demand of automated methods for morphological classification. Supervised learning techniques…

The star formation rate - stellar mass relation (SFR-M*) and its evolution (i.e., the SFR main sequence) describes the growth rate of galaxies of a given stellar mass and at a given redshift. Assuming that present-day star-forming galaxies…

Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and…

In this work we focus on the determination of the relative distributions of young, intermediate-age and old populations of stars in galaxies. Starting from a grid of theoretical population synthesis models we constructed a set of model…

Perception is a fundamental task in the field of computer vision, encompassing a diverse set of subtasks that can be systematically categorized into four distinct groups based on two dimensions: prediction type and instruction type.…

We present a dataset built for machine learning applications consisting of galaxy photometry, images, spectroscopic redshifts, and structural properties. This dataset comprises 286,401 galaxy images and photometry from the Hyper-Suprime-Cam…

Upcoming large galaxy surveys will subject the standard cosmological model, $\Lambda$CDM, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering…

The formation processes and the evolutionary stages of high-mass stars are poorly understood compared to low-mass stars. Large-scale surveys are needed to provide an unbiased census of high column density sites which can potentially host…

Nearly 1/3 of the sources listed in the Third Fermi Large Area Telescope (LAT) catalog (3FGL) remain unassociated. It is possible that predicted and even unanticipated gamma-ray source classes are present in these data waiting to be…

First stars can only form in structures that are suitably dense, which can be parametrized by the minimum dark matter halo mass $M_{\rm min}$. $M_{\rm min}$ must plays an important role in star formation. The connection of long gamma-ray…

In this study, we develop an artificial neural network to estimate the infrared (IR) luminosity and star formation rates (SFR) of galaxies. Our network is trained using 'true' IR luminosity values derived from modeling the IR spectral…

In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…

The advent of space-based observatories such as CoRoT and Kepler has enabled the testing of our understanding of stellar evolution on thousands of stars. Evolutionary models typically require five input parameters, the mass, initial Helium…

Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physically motivated prescriptions. They have also proven to be an efficient alternative for generating…

Stellar population synthesis models can now reproduce the photometry of old stellar systems (age $>$ 2 Gyr) in the near-infrared (NIR) bands at 3.4 and 4.6$\mu$m (WISE W1 $\&$ W2 or IRAC 1 $\&$ 2). In this paper we derive stellar…

The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar…

This paper introduces the Multi-wavelength Extreme Starburst Sample (MESS), a new catalog of 138 star-forming galaxies (0.1 < z < 0.3) optically selected from the SDSS using emission line strength diagnostics to have high absolute SFR…

In this empirical work, we aim to quantify the systematic uncertainties in stellar mass $(M_\star)$ estimates made from spectral energy distribution (SED) fitting through stellar population synthesis (SPS), for galaxies in the local…

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the…