scholarly journals The cosmic web through the lens of graph entropy

2020 ◽  
Vol 498 (1) ◽  
pp. L145-L149
Author(s):  
M V García-Alvarado ◽  
X-D Li ◽  
J E Forero-Romero
Keyword(s):  
Information Theory ◽  
Observational Data ◽  
Cosmological Parameters ◽  
Discrete Analogue ◽  
Important Influence ◽  
Number Density ◽  
Continuous Density ◽  
Redshift Surveys ◽  
Galaxy Redshift

ABSTRACT We explore the information theory entropy of a graph as a scalar to quantify the cosmic web. We find entropy values in the range between 1.5 and 3.2 bits. We argue that this entropy can be used as a discrete analogue of scalars used to quantify the connectivity in continuous density fields. After showing that the entropy clearly distinguishes between clustred and random points, we use simulations to gauge the influence of survey geometry, cosmic variance, redshift space distortions, redshift evolution, cosmological parameters, and spatial number density. Cosmic variance shows the least important influence while changes from the survey geometry, redshift space distortions, cosmological parameters, and redshift evolution produce larger changes of the order of 10−2 bits. The largest influence on the graph entropy comes from changes in the number density of clustred points. As the number density decreases, and the cosmic web is less pronounced, the entropy can diminish up to 0.2 bits. The graph entropy is simple to compute and can be applied both to simulations and observational data from large galaxy redshift surveys; it is a new statistic that can be used in a complementary way to other kinds of topological or clustering measurements.

scholarly journals Dynamics of The Tranquil Cosmic Web

2014 ◽  
Vol 11 (S308) ◽  
pp. 77-86
Author(s):  
Adi Nusser
Keyword(s):  
Phase Space ◽  
Structure Formation ◽  
Observational Data ◽  
Space Distribution ◽  
Phase Space Distribution ◽  
Redshift Surveys ◽  
Data Analyses ◽  
Galaxy Redshift ◽  
Insight Into

AbstractThe phase space distribution of matter out to ∼ 100 \rm Mpc is probed by two types of observational data: galaxy redshift surveys and peculiar motions of galaxies. Important information on the process of structure formation and deviations from standard gravity have been extracted from the accumulating data. The remarkably simple Zel'dovich approximation is the basis for much of our insight into the dynamics of structure formation and the development of data analyses methods. Progress in the methodology and some recent results is reviewed.

scholarly journals Cosmological inference from Bayesian forward modelling of deep galaxy redshift surveys

2019 ◽  
Vol 621 ◽  
pp. A69 ◽  
Author(s):  
Doogesh Kodi Ramanah ◽  
Guilhem Lavaux ◽  
Jens Jasche ◽  
Benjamin D. Wandelt
Keyword(s):  
Bayesian Inference ◽  
Large Scale ◽  
Initial Conditions ◽  
Cosmological Parameters ◽  
Density Fluctuations ◽  
Density Field ◽  
Space Representation ◽  
Underlying Assumption ◽  
Redshift Surveys ◽  
Galaxy Redshift

We present a large-scale Bayesian inference framework to constrain cosmological parameters using galaxy redshift surveys, via an application of the Alcock-Paczyński (AP) test. Our physical model of the non-linearly evolved density field, as probed by galaxy surveys, employs Lagrangian perturbation theory (LPT) to connect Gaussian initial conditions to the final density field, followed by a coordinate transformation to obtain the redshift space representation for comparison with data. We have implemented a Hamiltonian Monte Carlo sampler to generate realisations of three-dimensional (3D) primordial and present-day matter fluctuations from a non-Gaussian LPT-Poissonian density posterior given a set of observations. This hierarchical approach encodes a novel AP test, extracting several orders of magnitude more information from the cosmic expansion compared to classical approaches, to infer cosmological parameters and jointly reconstruct the underlying 3D dark matter density field. The novelty of this AP test lies in constraining the comoving-redshift transformation to infer the appropriate cosmology which yields isotropic correlations of the galaxy density field, with the underlying assumption relying purely on the geometrical symmetries of the cosmological principle. Such an AP test does not rely explicitly on modelling the full statistics of the field. We verified in depth via simulations that this renders our test robust to model misspecification. This leads to another crucial advantage, namely that the cosmological parameters exhibit extremely weak dependence on the currently unresolved phenomenon of galaxy bias, thereby circumventing a potentially key limitation. This is consequently among the first methods to extract a large fraction of information from statistics other than that of direct density contrast correlations, without being sensitive to the amplitude of density fluctuations. We perform several statistical efficiency and consistency tests on a mock galaxy catalogue, using the SDSS-III survey as template, taking into account the survey geometry and selection effects, to validate the Bayesian inference machinery implemented.

scholarly journals Improved correction of VIPERS angular selection effects in clustering measurements

2014 ◽  
Vol 11 (S308) ◽  
pp. 167-168
Author(s):  
A. Pezzotta ◽  
B.R. Granett ◽  
J. Bel ◽  
L. Guzzo ◽  
S. de la Torre ◽  
...  
Keyword(s):  
Growth Rate ◽  
Correlation Function ◽  
Cosmological Parameters ◽  
Selection Effects ◽  
Redshift Surveys ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Redshift Survey ◽  
Galaxy Redshift ◽  
Better Than

AbstractClustering estimates in galaxy redshift surveys need to account and correct for the way targets are selected from the general population, as to avoid biasing the measured values of cosmological parameters. The VIMOS Public Extragalactic Redshift Survey (VIPERS) is no exception to this, involving slit collisions and masking effects. Pushed by the increasing precision of the measurements, e.g. of the growth rate f, we have been re-assessing these effects in detail. We present here an improved correction for the two-point correlation function, capable to recover the amplitude of the monopole of the two-point correlation function ξ(r) above 1 h-1 Mpc to better than 2.

scholarly journals Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys

2004 ◽  
Vol 350 (4) ◽  
pp. 1153-1173 ◽  
Author(s):  
Xiaohu Yang ◽  
H. J. Mo ◽  
Y. P. Jing ◽  
Frank C. van den Bosch ◽  
YaoQuan Chu
Keyword(s):  
Dark Matter ◽  
Redshift Surveys ◽  
Galaxy Redshift

scholarly journals Probing neutrino masses with future galaxy redshift surveys

2004 ◽  
Vol 70 (4) ◽  
Author(s):  
Julien Lesgourgues ◽  
Sergio Pastor ◽  
Laurence Perotto
Keyword(s):  
Neutrino Masses ◽  
Redshift Surveys ◽  
Galaxy Redshift

scholarly journals FORECASTS OF DARK ENERGY CONSTRAINTS FROM BARYON ACOUSTIC OSCILLATIONS

2010 ◽  
Vol 25 (37) ◽  
pp. 3093-3113 ◽  
Author(s):  
YUN WANG
Keyword(s):  
Dark Energy ◽  
Figure Of Merit ◽  
Real Space ◽  
Number Density ◽  
Acoustic Oscillations ◽  
Energy Constraints ◽  
Redshift Survey ◽  
Galaxy Redshift ◽  
Baryon Acoustic Oscillations ◽  
Systematic Noise

The measurement of baryon acoustic oscillations (BAO) from a galaxy redshift survey provides one of the most promising methods for probing dark energy. In this paper, we clarify the assumptions that go into the forecasts of dark energy constraints from BAO. We show that assuming a constant nP0.2/G2(z) (where P0.2 is the real space galaxy power spectrum at k = 0.2 h/ Mpc and redshift z) gives a good approximation of the observed galaxy number density expected from a realistic flux-limited galaxy redshift survey. We find that assuming nP0.2/G2(z) = 10 gives very similar dark energy constraints to assuming nP0.2 = 3, but the latter corresponds to a galaxy number density larger than ~70% at z = 2. We show how the Figure-of-Merit (FoM) for constraining dark energy depends on the assumed galaxy number density, redshift accuracy, redshift range, survey area, and the systematic errors due to calibration and uncertainties in the theory of nonlinear evolution and galaxy biasing. We find that an additive systematic noise of up to 0.4–0.5% per Δz = 0.1 redshift slice does not lead to significant decrease in the BAO FoM.

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