scholarly journals On the Constraints of Galaxy Assembly Bias in Velocity Space

2021 ◽  
Author(s):  
Kevin S McCarthy ◽  
Zheng Zheng ◽  
Hong Guo ◽  
Wentao Luo ◽  
Yen-Ting Lin
Keyword(s):  
Dark Matter ◽  
Correlation Functions ◽  
Real Space ◽  
Velocity Space ◽  
Bias Effect ◽  
The Galaxy ◽  
History Of ◽  
Point Correlation ◽  
Galaxy Assembly ◽  
Velocity Bias

Abstract If the formation of central galaxies in dark matter haloes traces the assembly history of their host haloes, in haloes of fixed mass, central galaxy clustering may show dependence on properties indicating their formation history. Such a galaxy assembly bias effect has been investigated by Lin et al. (2016), with samples of central galaxies constructed in haloes of similar mass and with mean halo mass verified by galaxy lensing measurements, and no significant evidence of assembly bias is found from the analysis of the projected two-point correlation functions of early- and late-forming central galaxies. In this work, we extend the the investigation of assembly bias effect from real space to redshift (velocity) space, with an extended construction of early- and late-forming galaxies. We carry out halo occupation distribution modelling to constrain the galaxy-halo connection to see whether there is any sign of the effect of assembly bias. We find largely consistent host halo mass for early- and late-forming central galaxies, corroborated by lensing measurements. The central velocity bias parameters, which are supposed to characterise the mutual relaxation between central galaxies and their host haloes, are inferred to overlap between early- and late-forming central galaxies. However, we find a large amplitude of velocity bias for early-forming central galaxies (e.g. with central galaxies moving at more than 50% that of dark matter velocity dispersion inside host haloes), which may signal an assembly bias effect. A large sample with two-point correlation functions and other clustering measurements and improved modelling will help reach a conclusive result.

scholarly journals Dark matter response to galaxy assembly history

2019 ◽  
Vol 622 ◽  
pp. A197 ◽  
Author(s):  
María Celeste Artale ◽  
Susana E. Pedrosa ◽  
Patricia B. Tissera ◽  
Pedro Cataldi ◽  
Arianna Di Cintio
Keyword(s):  
Dark Matter ◽  
Stellar Mass ◽  
Dark Matter Halo ◽  
Stable Configuration ◽  
The Galaxy ◽  
Central Regions ◽  
Grid Scheme ◽  
History Of ◽  
Galaxy Assembly ◽  
Baryonic Mass

Aims. It is well known that the presence of baryons affects the dark matter host haloes. Exploring the galaxy assembly history together with the dark matter haloes properties through time can provide a way to measure these effects. Methods. We have studied the properties of four Milky Way mass dark matter haloes from the Aquarius project during their assembly history, between z = 0 − 4. In this work, we used a published SPH run and the dark matter only counterpart as case studies. To asses the robustness of our findings, we compared them with one of the haloes run using a moving-mesh technique and different sub-grid scheme. Results. Our results show that the cosmic evolution of the dark matter halo profiles depends on the assembly history of the baryons. We find that the dark matter profiles do not significantly change with time, hence they become stable, when the fraction of baryons accumulated in the central regions reaches 80 per cent of its present mass within the virial radius. Furthermore, the mass accretion history shows that the haloes that assembled earlier are those that contain a larger amount of baryonic mass aforetime, which in turn allows the dark matter halo profiles to reach a stable configuration earlier. For the SPH haloes, we find that the specific angular momentum of the dark matter particles within the five per cent of the virial radius at z = 0, remains approximately constant from the time at which 60 per cent of the stellar mass is gathered. We have explored different theoretical and empirical models for the contraction of the haloes through redshift. A model to better describe the contraction of the haloes through redshift evolution must depend on the stellar mass content in the inner regions.

scholarly journals Kinematical & Chemical Characteristics of the Thin and Thick Disks

2008 ◽  
Vol 4 (S254) ◽  
pp. 179-190 ◽  
Author(s):  
Rosemary F. G. Wyse
Keyword(s):  
Dark Matter ◽  
Cold Dark Matter ◽  
Milky Way ◽  
Observational Evidence ◽  
Chemical Characteristics ◽  
Chemical Abundance ◽  
The Galaxy ◽  
History Of ◽  
Thin And Thick Disks ◽  
Thick Disks

AbstractI discuss how the chemical abundance distributions, kinematics and age distributions of stars in the thin and thick disks of the Galaxy can be used to decipher the merger history of the Milky Way, a typical large galaxy. The observational evidence points to a rather quiescent past merging history, unusual in the context of the ‘consensus’ cold-dark-matter cosmology favoured from observations of structure on scales larger than individual galaxies.

scholarly journals N-body Simulations to Test the Reliability of Two-point Correlation Functions of Galaxies

1992 ◽  
Vol 9 ◽  
pp. 703-704
Author(s):  
Yasushi Suto
Keyword(s):  
Correlation Functions ◽  
Large Scale ◽  
Sample Volume ◽  
Limited Data ◽  
Observable Universe ◽  
Large N ◽  
The Galaxy ◽  
Point Correlation ◽  
Systematic Biases ◽  
Redshift Survey

The shape and amplitude of the galaxy – galaxy correlation functions, ξgg(r), are among the most widely used measures of the large-scale structure in the universe (Totsuji & Kihara 1969). The estimates, however, might be seriously affected by the limited size of the sample volume, or equivalently, the limited number of available galaxies. In fact, while the observable universe extends c/H0 ~ 3000h-1Mpc, most observational works to map the distribution of galaxies so far have been mainly applied to samples within ~ 100h-1Mpc from us. Thus a CfA redshift survey slice, for example, of 8h < α < 17h, 26.5° < δ < 32.5°, and cz ≾ 15000km/sec (de Lapparent et al. 1986, 1988) represents merely ~ 2 x 10-5 of the total volume of the observable universe. This clearly illustrates the importance of examining possible systematic biases and variations in the estimates of two-point correlation functions from instrinsically limited data. We studied such sample-to-sample variations by analysing subsamples extracted from large N-body simulation data.

scholarly journals Origin of the galaxy morphology

2003 ◽  
Vol 208 ◽  
pp. 431-432
Author(s):  
N. Nakasato
Keyword(s):  
Dark Matter ◽  
Star Formation ◽  
High Resolution ◽  
Cold Dark Matter ◽  
Star Formation History ◽  
The Galaxy ◽  
Particle Hydrodynamics ◽  
History Of ◽  
Analytic Models ◽  
Galaxy Morphology

In the current most plausible Cold Dark Matter (CDM) cosmology, larger halos increase their mass by the progressive mergers of smaller clumps. Due to these progressive merger events, galaxies have formed and evolved. Such merger events could trigger star bursts depending on mass of a merging object. In other words, star formation history reflects the strength of the interaction between a galaxy and merging objects. Also, a several merger events strongly affect the development of the morphology of galaxies as assumed in semi-analytic models. In the most advanced semi-analytic models, N-body simulations of dark matter particles are used to obtain the merging history of halos. By combining the description of radiative cooling, hydrodynamics and star formation with the obtained merging history, such models successfully have explained the various qualitative predictions. Here, we show the results of similar approach but using a fullly numerical model. In contrast to the semi-analytic models, we use our high resolution Smoothed Particle Hydrodynamics (SPH) models. With our SPH code, we try to tackle the problem of the galaxy morphology. We have done a several handful high-resolution SPH simulations and analyzed the merging history of such models. Accordingly, we can see the relation between the obtained morphology and the merging history or other physical properties of the model.

scholarly journals Generating approximate halo catalogues for blind challenges in precision cosmology

2019 ◽  
Vol 485 (2) ◽  
pp. 2407-2416 ◽  
Author(s):  
Lehman H Garrison ◽  
Daniel J Eisenstein
Keyword(s):  
Dark Matter ◽  
Transfer Function ◽  
Power Spectrum ◽  
High Precision ◽  
Real Space ◽  
Dark Matter Halo ◽  
The Real ◽  
The Galaxy ◽  
Similar Accuracy ◽  
Better Than

ABSTRACT We present a method for generating suites of dark matter halo catalogues with only a few N-body simulations, focusing on making small changes to the underlying cosmology of a simulation with high precision. In the context of blind challenges, this allows us to re-use a simulation by giving it a new cosmology after the original cosmology is revealed. Starting with full N-body realizations of an original cosmology and a target cosmology, we fit a transfer function that displaces haloes in the original so that the galaxy/HOD power spectrum matches that of the target cosmology. This measured transfer function can then be applied to a new realization of the original cosmology to create a new realization of the target cosmology. For a 1 per cent change in σ8, we achieve 0.1 per cent accuracy to $k = 1\, h\, \mathrm{Mpc}^{-1}$ in the real-space power spectrum; this degrades to 0.3 per cent when the transfer function is applied to a new realization. We achieve similar accuracy in the redshift-space monopole and quadrupole. In all cases, the result is better than the sample variance of our $1.1\, h^{-1}\, \mathrm{Gpc}$ simulation boxes.

scholarly journals Self-consistent redshift estimation using correlation functions without a spectroscopic reference sample

2019 ◽  
Vol 485 (3) ◽  
pp. 3642-3660 ◽  
Author(s):  
Ben Hoyle ◽  
Markus Michael Rau
Keyword(s):  
Dark Matter ◽  
Correlation Functions ◽  
Reference Sample ◽  
Data Driven ◽  
Model Parameters ◽  
Redshift Distribution ◽  
Self Consistent ◽  
The Galaxy ◽  
Consistent Manner ◽  
Order Of Magnitude

ABSTRACT We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation redshift methods, this approach does not require a reference sample with known redshifts. By measuring the projected cross- and auto-correlations of different galaxy sub-samples, e.g. as chosen by simple cells in colour–magnitude space, we are able to estimate the galaxy-dark matter bias model parameters, and the shape of the redshift distributions of each sub-sample. This method fully marginalizes over a flexible parametrization of the redshift distribution and galaxy-dark matter bias parameters of sub-samples of galaxies, and thus provides a general Bayesian framework to incorporate redshift uncertainty into the cosmological analysis in a data-driven, consistent, and reproducible manner. This result is improved by an order of magnitude by including cross-correlations with the cosmic microwave background and with galaxy–galaxy lensing. We showcase how this method could be applied to real galaxies. By using idealized data vectors, in which all galaxy-dark matter model parameters and redshift distributions are known, this method is demonstrated to recover unbiased estimates on important quantities, such as the offset Δz between the mean of the true and estimated redshift distribution and the 68 per cent, 95 per cent, and 99.5 per cent widths of the redshift distribution to an accuracy required by current and future surveys.

scholarly journals How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

2019 ◽  
Vol 488 (3) ◽  
pp. 3541-3567 ◽  
Author(s):  
Kuan Wang ◽  
Yao-Yuan Mao ◽  
Andrew R Zentner ◽  
Frank C van den Bosch ◽  
Johannes U Lange ◽  
...  
Keyword(s):  
Survey Data ◽  
Frequent Use ◽  
The Galaxy ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Redshift Survey ◽  
Galaxy Halo ◽  
Statistical Connection ◽  
Galaxy Assembly ◽  
Halo Occupation Distribution

ABSTRACT Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy–halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function wp(rp), the galaxy–galaxy lensing signal ΔΣ(rp), the void probability function VPF(r), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P(N2/N5). We find that despite the frequent use of the combination wp(rp) + ΔΣ(rp) in interpreting galaxy data, the count statistics, P(NCIC) and P(NCIA), are generally more efficient in constraining galaxy assembly bias when combined with wp(rp). Constraints based upon wp(rp) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of wp(rp) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy–halo connection.

scholarly journals MAPPING THE REAL-SPACE DISTRIBUTIONS OF GALAXIES IN SDSS DR7. I. TWO-POINT CORRELATION FUNCTIONS

2016 ◽  
Vol 833 (2) ◽  
pp. 241 ◽  
Author(s):  
Feng Shi ◽  
Xiaohu Yang ◽  
Huiyuan Wang ◽  
Youcai Zhang ◽  
H. J. Mo ◽  
...  
Keyword(s):  
Correlation Functions ◽  
Real Space ◽  
The Real ◽  
Point Correlation
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