scholarly journals Cosmic variance of z > 7 galaxies: prediction from bluetides

2020 ◽  
Vol 496 (1) ◽  
pp. 754-766
Author(s):  
Aklant K Bhowmick ◽  
Rachel S Somerville ◽  
Tiziana Di Matteo ◽  
Stephen Wilkins ◽  
Yu Feng ◽  
...  

ABSTRACT In the coming decade, a new generation of telescopes, including JWST and WFIRST, will probe the period of the formation of first galaxies and quasars, and open up the last frontier for structure formation. Recent simulations and observations have suggested that these galaxies are strongly clustered (with large-scale bias ≳6), and therefore have significant cosmic variance. In this work, we use bluetides, the largest volume cosmological simulation of galaxy formation, to directly estimate the cosmic variance for current and upcoming surveys. Given its resolution and volume, bluetides can probe the bias and cosmic variance of z > 7 galaxies between magnitude MUV ∼ −16 and MUV ∼ −22 over survey areas ∼0.1 arcmin2 to ∼10 deg2. Within this regime, the cosmic variance decreases with survey area/ volume as a power law with exponents between ∼−0.25 and ∼−0.45. For the planned 10 deg2 field of WFIRST, the cosmic variance is between $3{{\ \rm per\ cent}}$ and $10{{\ \rm per\ cent}}$. Upcoming JWST medium/ deep surveys with areas up to A ∼ 100 arcmin2 will have cosmic variance ranging from ${\sim}20\,\mathrm{ to}\,50{{\ \rm per\ cent}}$. Lensed surveys have the highest cosmic variance ${\gtrsim}40{{\ \rm per\ cent}}$; the cosmic variance of MUV ≲ −16 galaxies is ${\lesssim}100{{\ \rm per\ cent}}$ up to z ∼ 11. At higher redshifts such as z ∼ 12 (14), effective volumes of ≳ (8 Mpc h−1)3 (≳(12 Mpc h−1)3) are required to limit the cosmic variance to within $100{{\ \rm per\ cent}}$. Finally, we find that cosmic variance is larger than Poisson variance and forms the dominant component of the overall uncertainty in all current and upcoming surveys. We present our calculations in the form of simple fitting functions and an online cosmic variance calculator (CV_AT_COSMIC_DAWN) that we publicly release.

2005 ◽  
Vol 216 ◽  
pp. 120-128
Author(s):  
Matthias Steinmetz

Maps of the cosmos, in particular maps of the cosmic microwave background and of the large scale distribution of galaxies have been crucial ingredients in the development of the standard model of structure formation, sometimes also labeled “concordance model”. This model has proven to be remarkably successful in explaining an impressive array of observations on scales of hundreds of kpc to thousands of Mpc. In this contribution I will attempt to extend those studies to smaller, (sub)galactic scales and will confront detailed gas-dynamical simulations of the formation of individual galaxies with observational data on these scales, reporting some successes and failures of this endeavor. Ongoing surveys that are mapping the distribution of stars in the Milky Way should be able to clearly identify the imprints of the hierarchical galaxy formation process providing an independent check of the validity of the structure formation paradigm.


2019 ◽  
Vol 15 (S352) ◽  
pp. 43-43
Author(s):  
Pratika Dayal

AbstractGalaxy formation in the first billion years mark a time of great upheaval in the history of the Universe: the first galaxies started both the ‘metal age’ as well as the era of cosmic reionization. I will start by reviewing the dust production mechanisms and dust masses for high-redshift galaxies which will be revolutionized in the ALMA era. I will then show how the JWST will be an invaluable experiment to shed light on the impact of reionization feedback on early galaxy formation. As we look forward towards the era of 21cm cosmology, I will highlight the crucial and urgent synergies required between 21cm facilities (such as the SKA) and galaxy experiments (JWST, E-ELT and Subaru to name a few) to understand the physics of the epoch of reionization that remains a crucial frontier in the field of astrophysics and physical cosmology. Time permitting, I will try to give a flavour of how the assembly of early galaxies, accessible with the forthcoming JWST, can provide a powerful testbed for Dark Matter models beyond ‘Cold Dark Matter’.


1994 ◽  
Vol 03 (01) ◽  
pp. 241-244 ◽  
Author(s):  
VOLKER MÜLLER

It is shown that fourth-order-gravity with a scalar field leads naturally to double inflation models. If both inflationary episodes are disconnected by a stage of power law expansion, we get a primordial inflation spectrum with a break in the power possibly relevant for the formation of large scale structures in the universe.


2000 ◽  
Vol 174 ◽  
pp. 434-444
Author(s):  
Antonaldo Diaferio

AbstractFor the first time, the combination of semi-analytic modelling of galaxy formation and N-body simulations of cosmic structure formation enables us to model, at the same time, both the photometric and the clustering properties of galaxies. Two Cold Dark Matter Universes provide a reasonable fit to the observed properties of galaxies, groups and clusters, including luminosities, colours, density and velocity biases. We show how the properties of galaxies and groups on small scales are inextricably connected with the global properties of the Universe.


Author(s):  
Abraham Loeb ◽  
Steven R. Furlanetto

This book provides a comprehensive, self-contained introduction to one of the most exciting frontiers in astrophysics today: the quest to understand how the oldest and most distant galaxies in our universe first formed. Until now, most research on this question has been theoretical, but the next few years will bring about a new generation of large telescopes that promise to supply a flood of data about the infant universe during its first billion years after the big bang. This book bridges the gap between theory and observation. It is an invaluable reference for students and researchers on early galaxies. The book starts from basic physical principles before moving on to more advanced material. Topics include the gravitational growth of structure, the intergalactic medium, the formation and evolution of the first stars and black holes, feedback and galaxy evolution, reionization, 21-cm cosmology, and more.


2020 ◽  
Author(s):  
Lungwani Muungo

The purpose of this review is to evaluate progress inmolecular epidemiology over the past 24 years in canceretiology and prevention to draw lessons for futureresearch incorporating the new generation of biomarkers.Molecular epidemiology was introduced inthe study of cancer in the early 1980s, with theexpectation that it would help overcome some majorlimitations of epidemiology and facilitate cancerprevention. The expectation was that biomarkerswould improve exposure assessment, document earlychanges preceding disease, and identify subgroupsin the population with greater susceptibility to cancer,thereby increasing the ability of epidemiologic studiesto identify causes and elucidate mechanisms incarcinogenesis. The first generation of biomarkers hasindeed contributed to our understanding of riskandsusceptibility related largely to genotoxic carcinogens.Consequently, interventions and policy changes havebeen mounted to reduce riskfrom several importantenvironmental carcinogens. Several new and promisingbiomarkers are now becoming available for epidemiologicstudies, thanks to the development of highthroughputtechnologies and theoretical advances inbiology. These include toxicogenomics, alterations ingene methylation and gene expression, proteomics, andmetabonomics, which allow large-scale studies, includingdiscovery-oriented as well as hypothesis-testinginvestigations. However, most of these newer biomarkershave not been adequately validated, and theirrole in the causal paradigm is not clear. There is a needfor their systematic validation using principles andcriteria established over the past several decades inmolecular cancer epidemiology.


Technologies ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 2
Author(s):  
Ashish Jaiswal ◽  
Ashwin Ramesh Babu ◽  
Mohammad Zaki Zadeh ◽  
Debapriya Banerjee ◽  
Fillia Makedon

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same sample close to each other while trying to push away embeddings from different samples. This paper provides an extensive review of self-supervised methods that follow the contrastive approach. The work explains commonly used pretext tasks in a contrastive learning setup, followed by different architectures that have been proposed so far. Next, we present a performance comparison of different methods for multiple downstream tasks such as image classification, object detection, and action recognition. Finally, we conclude with the limitations of the current methods and the need for further techniques and future directions to make meaningful progress.


Author(s):  
Marta B. Silva ◽  
Ely D. Kovetz ◽  
Garrett K. Keating ◽  
Azadeh Moradinezhad Dizgah ◽  
Matthieu Bethermin ◽  
...  

AbstractThis paper outlines the science case for line-intensity mapping with a space-borne instrument targeting the sub-millimeter (microwaves) to the far-infrared (FIR) wavelength range. Our goal is to observe and characterize the large-scale structure in the Universe from present times to the high redshift Epoch of Reionization. This is essential to constrain the cosmology of our Universe and form a better understanding of various mechanisms that drive galaxy formation and evolution. The proposed frequency range would make it possible to probe important metal cooling lines such as [CII] up to very high redshift as well as a large number of rotational lines of the CO molecule. These can be used to trace molecular gas and dust evolution and constrain the buildup in both the cosmic star formation rate density and the cosmic infrared background (CIB). Moreover, surveys at the highest frequencies will detect FIR lines which are used as diagnostics of galaxies and AGN. Tomography of these lines over a wide redshift range will enable invaluable measurements of the cosmic expansion history at epochs inaccessible to other methods, competitive constraints on the parameters of the standard model of cosmology, and numerous tests of dark matter, dark energy, modified gravity and inflation. To reach these goals, large-scale structure must be mapped over a wide range in frequency to trace its time evolution and the surveyed area needs to be very large to beat cosmic variance. Only a space-borne mission can properly meet these requirements.


Author(s):  
Joseph A O’Leary ◽  
Benjamin P Moster ◽  
Thorsten Naab ◽  
Rachel S Somerville

Abstract We explore the galaxy-galaxy merger rate with the empirical model for galaxy formation, emerge. On average, we find that between 2 per cent and 20 per cent of massive galaxies (log10(m*/M⊙) ≥ 10.3) will experience a major merger per Gyr. Our model predicts galaxy merger rates that do not scale as a power-law with redshift when selected by descendant stellar mass, and exhibit a clear stellar mass and mass-ratio dependence. Specifically, major mergers are more frequent at high masses and at low redshift. We show mergers are significant for the stellar mass growth of galaxies log10(m*/M⊙) ≳ 11.0. For the most massive galaxies major mergers dominate the accreted mass fraction, contributing as much as 90 per cent of the total accreted stellar mass. We reinforce that these phenomena are a direct result of the stellar-to-halo mass relation, which results in massive galaxies having a higher likelihood of experiencing major mergers than low mass galaxies. Our model produces a galaxy pair fraction consistent with recent observations, exhibiting a form best described by a power-law exponential function. Translating these pair fractions into merger rates results in an inaccurate prediction compared to the model intrinsic values when using published observation timescales. We find the pair fraction can be well mapped to the intrinsic merger rate by adopting an observation timescale that decreases linearly with redshift as Tobs = −0.36(1 + z) + 2.39 [Gyr], assuming all observed pairs merge by z = 0.


2020 ◽  
Vol 501 (2) ◽  
pp. 1755-1765
Author(s):  
Andrew Pontzen ◽  
Martin P Rey ◽  
Corentin Cadiou ◽  
Oscar Agertz ◽  
Romain Teyssier ◽  
...  

ABSTRACT We introduce a new method to mitigate numerical diffusion in adaptive mesh refinement (AMR) simulations of cosmological galaxy formation, and study its impact on a simulated dwarf galaxy as part of the ‘EDGE’ project. The target galaxy has a maximum circular velocity of $21\, \mathrm{km}\, \mathrm{s}^{-1}$ but evolves in a region that is moving at up to $90\, \mathrm{km}\, \mathrm{s}^{-1}$ relative to the hydrodynamic grid. In the absence of any mitigation, diffusion softens the filaments feeding our galaxy. As a result, gas is unphysically held in the circumgalactic medium around the galaxy for $320\, \mathrm{Myr}$, delaying the onset of star formation until cooling and collapse eventually triggers an initial starburst at z = 9. Using genetic modification, we produce ‘velocity-zeroed’ initial conditions in which the grid-relative streaming is strongly suppressed; by design, the change does not significantly modify the large-scale structure or dark matter accretion history. The resulting simulation recovers a more physical, gradual onset of star formation starting at z = 17. While the final stellar masses are nearly consistent ($4.8 \times 10^6\, \mathrm{M}_{\odot }$ and $4.4\times 10^6\, \mathrm{M}_{\odot }$ for unmodified and velocity-zeroed, respectively), the dynamical and morphological structure of the z = 0 dwarf galaxies are markedly different due to the contrasting histories. Our approach to diffusion suppression is suitable for any AMR zoom cosmological galaxy formation simulations, and is especially recommended for those of small galaxies at high redshift.


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