scholarly journals Deep learning for intensity mapping observations: component extraction

2020 ◽  
Vol 496 (1) ◽  
pp. L54-L58 ◽  
Author(s):  
Kana Moriwaki ◽  
Nina Filippova ◽  
Masato Shirasaki ◽  
Naoki Yoshida
Keyword(s):  
Deep Learning ◽  
Galaxy Formation ◽  
Large Scale ◽  
Generative Adversarial Networks ◽  
Intensity Mapping ◽  
Adversarial Networks ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Emission Line Galaxies ◽  
Two Populations

ABSTRACT Line intensity mapping (LIM) is an emerging observational method to study the large-scale structure of the Universe and its evolution. LIM does not resolve individual sources but probes the fluctuations of integrated line emissions. A serious limitation with LIM is that contributions of different emission lines from sources at different redshifts are all confused at an observed wavelength. We propose a deep learning application to solve this problem. We use conditional generative adversarial networks to extract designated information from LIM. We consider a simple case with two populations of emission-line galaxies; H $\rm \alpha$ emitting galaxies at $z$ = 1.3 are confused with [O iii] emitters at $z$ = 2.0 in a single observed waveband at 1.5 $\mu{\textrm m}$. Our networks trained with 30 000 mock observation maps are able to extract the total intensity and the spatial distribution of H $\rm \alpha$ emitting galaxies at $z$ = 1.3. The intensity peaks are successfully located with 74 per cent precision. The precision increases to 91 per cent when we combine five networks. The mean intensity and the power spectrum are reconstructed with an accuracy of ∼10 per cent. The extracted galaxy distributions at a wider range of redshift can be used for studies on cosmology and on galaxy formation and evolution.

scholarly journals The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies

2020 ◽  
Vol 499 (4) ◽  
pp. 5486-5507 ◽  
Author(s):  
S Avila ◽  
V Gonzalez-Perez ◽  
F G Mohammad ◽  
A de Mattia ◽  
C Zhao ◽  
...  
Keyword(s):  
Emission Line ◽  
Galaxy Formation ◽  
Distribution Model ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Physical Effects ◽  
Emission Line Galaxies ◽  
Halo Masses ◽  
The Impact ◽  
Halo Occupation Distribution

ABSTRACT We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, wp, captures most of the effects from the PDF and satellites profile. The quadrupole, ξ2, captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. We fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.

scholarly journals LSUN-Stanford Car Dataset: Enhancing Large-Scale Car Image Datasets Using Deep Learning for Usage in GAN Training

2020 ◽  
Vol 10 (14) ◽  
pp. 4913
Author(s):  
Tin Kramberger ◽  
Božidar Potočnik
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Large Scale ◽  
Generative Adversarial Networks ◽  
Adversarial Networks ◽  
Image Dataset ◽  
Image Datasets

Currently there is no publicly available adequate dataset that could be used for training Generative Adversarial Networks (GANs) on car images. All available car datasets differ in noise, pose, and zoom levels. Thus, the objective of this work was to create an improved car image dataset that would be better suited for GAN training. To improve the performance of the GAN, we coupled the LSUN and Stanford car datasets. A new merged dataset was then pruned in order to adjust zoom levels and reduce the noise of images. This process resulted in fewer images that could be used for training, with increased quality though. This pruned dataset was evaluated by training the StyleGAN with original settings. Pruning the combined LSUN and Stanford datasets resulted in 2,067,710 images of cars with less noise and more adjusted zoom levels. The training of the StyleGAN on the LSUN-Stanford car dataset proved to be superior to the training with just the LSUN dataset by 3.7% using the Fréchet Inception Distance (FID) as a metric. Results pointed out that the proposed LSUN-Stanford car dataset is more consistent and better suited for training GAN neural networks than other currently available large car datasets.

scholarly journals Galaxy formation and evolution with the Dark Energy Survey

2012 ◽  
Vol 8 (S295) ◽  
pp. 137-140
Author(s):  
Diego Capozzi ◽  
Daniel Thomas ◽  
Claudia Maraston ◽  
Luke J. M. Davies
Keyword(s):  
Dark Energy ◽  
Galaxy Evolution ◽  
Galaxy Formation ◽  
Large Scale ◽  
Time Range ◽  
Data Set ◽  
Dark Energy Survey ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Energy Survey

AbstractThe Dark Energy Survey (DES) will be the new state-of the-art in large-scale galaxy imaging surveys. With 5,000 deg2, it will cover an area of the sky similar to SDSS-II, but will go over two magnitudes deeper, reaching 24th magnitude in all four optical bands (griz). DES will further provide observations in the redder Y-band and will be complemented with VISTA observations in the near-infrared bands JHK. Hence DES will furnish an unprecedented combination of sky and wavelength coverage and depth, unreached by any of the existing galaxy surveys. The very nature of the DES data set – large volume at intermediate photometric depth – allows us to probe galaxy formation and evolution within a cosmic-time range of ~ 10 Gyr and in different environments. In fact there will be many galaxy clusters available for galaxy evolution studies, given that one of the main aims of DES is to use their abundance to constrain the equation of state of dark energy. The X-ray follow up of these clusters, coupled with the use of gravitational lensing, will provide very precise measures of their masses, enabling us to study in detail the influence of the environment on galaxy formation and evolution processes. DES will leverage the study of these processes by allowing us to perform a detailed investigation of the galaxy luminosity and stellar mass functions and of the relationship between dark and baryonic matter as described by the Halo Occupation Distribution.

scholarly journals Dusty Starbursts within a z=3 Large Scale Structure revealed by ALMA

2015 ◽  
Vol 11 (S319) ◽  
pp. 109-109
Author(s):  
Hideki Umehata
Keyword(s):  
Galaxy Formation ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Massive Black Hole ◽  
Rich Cluster ◽  
Galaxy Formation And Evolution ◽  
Submillimeter Galaxies ◽  
Formation And Evolution

AbstractThe role of the large-scale structure is one of the most important theme in studying galaxy formation and evolution. However, it has been still mystery especially at z>2. On the basis of our ALMA 1.1 mm observations in a z ~ 3 protocluster field, it is suggested that submillimeter galaxies (SMGs) preferentially reside in the densest environment at z ~ 3. Furthermore we find a rich cluster of AGN-host SMGs at the core of the protocluster, combining with Chandra X-ray data. Our results indicate the vigorous star-formation and accelerated super massive black hole (SMBH) growth in the node of the cosmic web.

The relationship between black hole accretion rate and gas properties at the Bondi radius

2019 ◽  
Vol 15 (S356) ◽  
pp. 214-217
Author(s):  
De-Fu Bu
Keyword(s):  
Black Hole ◽  
Galaxy Formation ◽  
Large Scale ◽  
Accretion Rate ◽  
Black Hole Accretion ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
The Relationship ◽  
Large Scale Simulations ◽  
Hole Accretion

AbstractThe mass accretion rate determines the black hole accretion mode and the corresponding efficiency of active galactic nuclei (AGNs) feedback. In large-scale simulations studying galaxy formation and evolution, the Bondi radius can be at most marginally resolved. In these simulations, the Bondi accretion formula is always used to estimate the black hole accretion rate. The Bondi solution can not represent the real accretion process. We perform 77 simulations with varying density and temperature at Bondi radius. We find a formula to calculate the black hole accretion rate based on gas density and temperature at Bondi radius. We find that the formula can accurately predict the luminosity of observed low-luminosity AGNs. This formula can be used in sub-grid models in large-scale simulations with AGNs feedback.

scholarly journals The Deep Project

1998 ◽  
Vol 11 (1) ◽  
pp. 468-472
Author(s):  
David C. Koo
Keyword(s):  
Galaxy Formation ◽  
Large Scale ◽  
High Redshift ◽  
Chemical Abundances ◽  
Large Numbers ◽  
Galaxy Formation And Evolution ◽  
Kinematic Studies ◽  
Formation And Evolution ◽  
Hubble Deep Field ◽  
Imaging Spectrograph

Abstract DEEP is a multi-institutional program designed to undertake a major new spectroscopic survey of faint field galaxies with the Keck II 10-m telescope. The scientific goals are broad and include exploring galaxy formation and evolution, mapping the large scale structure at moderate to high redshifts, and constraining the nature and distribution of dark matter and cosmology. Besides the primary goal of securing large numbers of redshifts (10, 000+) to very faint limits of I ~ 23, DEEP intends to acquire spectra of high enough quality and spectral resolution to extract rotation curves, velocity dispersions, age estimates, and chemical abundances for a brighter subset of galaxies. A new imaging spectrograph for Keck called DEIMOS has been specifically designed to achieve these goals and is currently scheduled for completion by the end of 1998. DEIMOS will provide anoverall gain for multi-object spectroscopy of about 7x compared to the current low-resolution spectrograph (LRIS). While awaiting for DEIMOS to be operational, the interim DEEP science programs have been diverse, but largely concentrated on spectroscopy of faint galaxies observed with HST, especially in the “Groth Strip” and Hubble Deep Field (HDF) and its flanking fields. Recent highlights include redshift and kinematic studies of compact galaxies, high redshift (z ~ 3) galaxies, and distantspirals.

scholarly journals What Radio Astronomy Can Tell us about Galaxy Formation

2010 ◽  
Vol 6 (S277) ◽  
pp. 75-78
Author(s):  
Bruce Partridge
Keyword(s):  
Star Formation ◽  
Cosmic Microwave Background ◽  
Galaxy Formation ◽  
Radio Astronomy ◽  
Large Scale ◽  
Cosmological Parameters ◽  
Microwave Background ◽  
Molecular Line ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution

AbstractRadio astronomy, broadly interpreted, has made important contributions to the study of galaxy formation and evolution. Maps of the cosmic microwave background provide information on the seeds of large-scale structure, in addition to refined values of the cosmological parameters. Examples of contributions from more conventional radio astronomy include:–The use of radio observations to track star formation rates since they are not affected by dust obscuration as optical/UV observations are, and the use of molecular line observations to make purely “radio” redshift determinations.

scholarly journals [O ii] emitters in MultiDark-Galaxies and DEEP2

2020 ◽  
Vol 497 (4) ◽  
pp. 5432-5453
Author(s):  
G Favole ◽  
V Gonzalez-Perez ◽  
D Stoppacher ◽  
Á Orsi ◽  
J Comparat ◽  
...  
Keyword(s):  
Galaxy Formation ◽  
Broad Band ◽  
Analytical Models ◽  
Data Sets ◽  
Luminosity Functions ◽  
Galaxy Formation And Evolution ◽  
The Galaxy ◽  
Formation And Evolution ◽  
Emission Line Galaxies ◽  
Absolute Magnitudes

ABSTRACT We use three semi-analytical models (SAMs) of galaxy formation and evolution run on the same 1 h−1 Gpc MultiDark Planck2 cosmological simulation to investigate the properties of [O ii] emission line galaxies at redshift z ∼ 1. We compare model predictions with different observational data sets, including DEEP2–firefly galaxies with absolute magnitudes. We estimate the [O ii] luminosity ($L{\left[\rm{O\,{\small II}}\right]}$) of our model galaxies using the public code get_ emlines , which ideally assumes as input the instantaneous star formation rates (SFRs). This property is only available in one of the SAMs under consideration, while the others provide average SFRs, as most models do. We study the feasibility of inferring galaxies’    $L{\left[\rm{O\,{\small II}}\right]}$  from average SFRs in post-processing. We find that the result is accurate for model galaxies with dust attenuated   $L{\left[\rm{O\,{\small II}}\right]}$ ≲ 1042.2 erg s−1 ($\lt 5{{\ \rm per\ cent}}$ discrepancy). The galaxy properties that correlate the most with the model   $L{\left[\rm{O\,{\small II}}\right]}$ are the SFR and the observed-frame u and g broad-band magnitudes. Such correlations have r-values above 0.64 and a dispersion that varies with   $L{\left[\rm{O\,{\small II}}\right]}$ . We fit these correlations with simple linear relations and use them as proxies for   $L{\left[\rm{O\,{\small II}}\right]}$ , together with an observational conversion that depends on SFR and metallicity. These proxies result in [O ii] luminosity functions and halo occupation distributions with shapes that vary depending on both the model and the method used to derive   $L{\left[\rm{O\,{\small II}}\right]}$ . The amplitude of the clustering of model galaxies with   $L{\left[\rm{O\,{\small II}}\right]}$ >1040.4 erg s−1 remains overall unchanged on scales above 1 $\, h^{-1}$ Mpc, independently of the $L{\left[\rm{O\,{\small II}}\right]}$ computation.

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