Predicting star formation properties of galaxies using deep learning
ThoughtWorks Technologies（思特沃克科技公司）；National Centre for Radio Astrophysics, TIFR（塔塔基础研究所国家射电天体物理中心）；Centre for Modeling and Simulation, Savitribai Phule Pune University（萨维特里拜·普利大学建模与仿真中心）
Understanding the star-formation properties of galaxies as a function of cosmic epoch is a critical exercise in studies of galaxy evolution. Traditionally, stellar population synthesis models have been used to obtain best fit parameters that characterise star formation in galaxies. As multiband flux measurements become available for thousands of galaxies, an alternative approach to characterising star formation using machine learning becomes feasible. In this work, we present the use of deep learning techniques to predict three important star formation properties -- stellar mass, star formation rate and dust luminosity. We characterise the performance of our deep learning models through comparisons with outputs from a standard stellar population synthesis code.
We predict the mass fraction of oxygen lost from galaxies in a cosmological simulation as a function of stellar mass and environment at the present day. The distribution with stellar mass is bimodal, separating star-forming and quenched galaxies. The metallicity of gas and stars is self-consistently calculated using a chemical evolution model that includes supernovae type II and Ia, hypernovae, and asymptotic giant branch stars. The mass of oxygen lost from each galaxy is calculated by comparing the existing oxygen in gas and stars in the galaxy to the oxygen that should have been produced by …
Predicting CO and dust emission of star-forming galaxies
Université de Strasbourg（斯特拉斯堡大学）；CNRS（法国国家科学研究中心）；Observatoire Astronomique de Strasbourg（斯特拉斯堡天文台）；Univ. Bordeaux（波尔多大学）；Laboratoire d’Astrophysique de Bordeaux（波尔多天体物理学实验室）；Jagiellonian University（雅盖隆大学）；Astronomical Observatory, Jagiellonian University（雅盖隆大学天文台）
We present a deep learning model to predict the r-band bulge-to-total light ratio (B/T) of nearby galaxies using their multi-band JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample of galaxies with reliable decomposition into the bulge and disk components. The existing approaches to estimate the B/T use galaxy light-profile modelling to find the best fit. This method is computationally expensive, prohibitively so for large samples of galaxies, and requires a significant amount of human intervention. Machine learning models have the pot…
Connecting Star Formation in the Milky Way and Nearby Galaxies -II. An Observationally Driven Analytical Model for Predicting Cloud-Scale Star Formation Rates
Max-Planck-Institut für Radioastronomie（马克斯·普朗克射电天文研究所）；Max-Planck-Institut für Astronomie（马克斯·普朗克天文学研究所）；Helmholtz-Institut für Strahlen- und Kernphysik (HISKP), Universität Bonn（波恩大学赫尔姆霍兹辐射与核物理研究所）；Charles University in Prague, Faculty of Mathematics and Physics, Astronomical Institute（布拉格查理大学数学物理学院天文研究所）
The ISM is a turbulent, multi-phase, and multi-scale medium following scaling relations. Analytical models of galactic gaseous disks need to take into account the multi-scale and multi-phase nature of the interstellar medium. They can be described as clumpy star-forming accretion disks in vertical hydrostatic equilibrium, with the mid-plane pressure balancing the gravity of the gaseous and stellar disk. ISM turbulence is taken into account by applying Galactic scaling relations to the cold atomic and molecular gas phases. Turbulence is maintained through energy injection by supernovae. With th…
Modeling Dust Production, Growth, and Destruction in Reionization-Era Galaxies with the CROC Simulations II: Predicting the Dust Content of High-Redshift Galaxies
Predicting HCN, HCO+, multi-transition CO, and dust emission of star-forming galaxies From local spiral and ultraluminous infrared galaxies to high-z star-forming and submillimeter galaxies
Far-infrared (FIR) emission lines are a powerful tool to investigate the properties of the interstellar medium, especially in high-redshift galaxies, where ALMA observations have provided unprecedented information. Interpreting such data with state-of-the-art cosmological simulations post-processed with CLOUDY, has provided insights on the internal structure and gas dynamics of these systems. However, no detailed investigation of the consistency and uncertainties of this kind of analysis has been performed to date. Here, we compare different approaches to estimate FIR line emission from state-…
Predicting Potential Host Galaxies of Supermassive Black Hole Binaries Based on Stellar Kinematics in Archival IFU Surveys
Bishop’s University（主教大学）；Trottier Space Institute and Department of Physics, McGill University（麦吉尔大学特鲁蒂尔太空研究所和物理系）；California Institute of Technology（加州理工学院）；Vanderbilt University（范德堡大学）
The primary difficulty in understanding the sources and processes that powered cosmic reionization is that it is not possible to directly probe the ionizing Lyman Continuum (LyC) radiation at that epoch as those photons have been absorbed by the intervening neutral hydrogen in the IGM on their way to us. It is therefore imperative to build a model to accurately predict LyC emission using other properties of galaxies in the reionization era. In recent years, studies have shown that the LyC emission from galaxies may be correlated to their Lya emission. Here, we study this correlation by analyzi…
Predicting the Spectroscopic Features of Galaxies by Applying Manifold Learning on Their Broad-Band Colors: Proof of Concept and Potential Applications for Euclid, Roman, and Rubin LSST
Performance of Photometric Template Fitting for Ultra-High Redshift Galaxies
Cosmic Dawn Center (DAWN)（宇宙黎明中心）；Niels Bohr Institute, University of Copenhagen（哥本哈根大学尼尔斯·玻尔研究所）；Department of Physics and Astronomy, University of Missouri（密苏里大学物理与天文学系）；DARK Cosmology Center, University of Copenhagen（哥本哈根大学暗宇宙学中心）；California Institute of Technology（加州理工学院）
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 wavelengths. In Dobbels et al. (2020), we show that these two sections are strongly related, and we can predict the global dust properties from the integrated UV to mid-infrared emission with the help of machine learning techniques. We investigate if these machine learning techniques can also be extended to resolved scales. Our aim is to predict resolved maps of …
Spiral galaxies undergo strong ram-pressure effects when they fall into the galaxy cluster potential. As a consequence, their gas is stripped to form extended tails within which star formation can happen, giving them the typical jellyfish appearance. The ultraviolet imaging observations of jellyfish galaxies provide an opportunity to understand ongoing star formation in the stripped tails. We report the ultraviolet observations of the jellyfish galaxies JW39, JO60, JO194 and compare with observations in optical continuum and $\mathrm{H}α$. We detect knots of star formation in the disk and tail…
The OTELO survey: New evidence of downsizing from the specific star formation rates, stellar mass functions, and star formation histories of a sample of low-mass galaxies at 0.38<z<1.43
Predicting HCN, HCO$^+$, multi-transition CO, and dust emission of star-forming galaxies -- Extension to luminous infrared galaxies and the role of cosmic ray ionization
Star formation in galaxies hosting AGN: A flat trend of star-formation rate with X-ray luminosity of galaxies hosting AGN in the SCUBA-2 Cosmology Legacy Survey
Star-forming dwarf galaxies have properties similar to those expected in high-redshift galaxies. Hence, these local galaxies may provide insights into the evolution of the first galaxies, and the physical processes at work. We present a sample of eleven potential local analogs to high-$z$ (LAHz) galaxies. The sample consists of blue compact dwarf galaxies, selected to have spectral energy distributions that fit galaxies at $1.5<z<4$. We use SOFIA-HAWC+ observations combined with optical and near-infrared data to characterize the dust properties, star formation rate (SFR) and star formation his…
Nuclear star clusters (NSCs) are massive star clusters found in all types of galaxies from dwarfs to massive galaxies. Recent studies show that while low-mass NSCs in dwarf galaxies ($M_\text{gal} < 10^{9} M_\odot$) form predominantly out of the merger of globular clusters (GCs), high-mass NSCs in massive galaxies have assembled most of their mass through central enriched star formation. So far, these results of a transition in the dominant NSC formation channel have been based on studies of early-type galaxies and massive late-type galaxies. Here, we present the first spectroscopic analysis o…
