Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userCosmological Parameter Estimation Using the Genus Amplitude - Application to Mock Galaxy Catalogs
110
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We study the topology of the matter density field in two dimensional slices, and consider how we can use the amplitude $A$ of the genus for cosmological parameter estimation. Using the latest Horizon Run 4 simulation data, we calculate the genus of the smoothed density field constructed from lightcone mock galaxy catalogs. Information can be extracted from the amplitude of the genus by considering both its redshift evolution and magnitude. The constancy of the genus amplitude with redshift can be used as a standard population, from which we derive constraints on the equation of state of dark energy $w_{rm de}$ - by measuring $A$ at $z sim 0.1$ and $z sim 1$, we can place an order $Delta w_{rm de} sim {cal O}(15%)$ constraint on $w_{rm de}$. By comparing $A$ to its Gaussian expectation value we can potentially derive an additional stringent constraint on the matter density $Delta Omega_{rm mat} sim 0.01$. We discuss the primary sources of contamination associated with the two measurements - redshift space distortion and shot noise. With accurate knowledge of galaxy bias, we can successfully remove the effect of redshift space distortion, and the combined effect of shot noise and non-linear gravitational evolution is suppressed by smoothing over suitably large scales $R_{rm G} ge 15 {rm Mpc}/h$. Without knowledge of the bias, we discuss how joint measurements of the two and three dimensional genus can be used to constrain the growth factor $beta = f/b$. The method can be applied optimally to redshift slices of a galaxy distribution generated using the drop-off technique.
rate research
Read More
We assess the performance of a perturbation theory inspired method for inferring cosmological parameters from the joint measurements of galaxy-galaxy weak lensing ($DeltaSigma$) and the projected galaxy clustering ($w_{rm p}$). To do this, we use a wide variety of mock galaxy catalogs constructed based on a large set of $N$-body simulations that mimic the Subaru HSC-Y1 and SDSS galaxies, and apply the method to the mock signals to address whether to recover the underlying true cosmological parameters in the mocks. We find that, as long as the appropriate scale cuts, $12$ and $8~h^{-1}{rm Mpc}$ for $DeltaSigma$ and $w_{rm p}$ respectively, are adopted, a minimal-bias model using the linear bias parameter $b_1$ alone and the nonlinear matter power spectrum can recover the true cosmological parameters (here focused on $Omega_{rm m}$ and $sigma_8$) to within the 68% credible interval, for all the mocks we study including one in which an assembly bias effect is implemented. This is as expected if physical processes inherent in galaxy formation/evolution are confined to local, small scales below the scale cut, and thus implies that real-space observables have an advantage in filtering out the impact of small-scale nonlinear effects in parameter estimation, compared to their Fourier-space counterparts. In addition, we find that a theoretical template including the higher-order bias contributions such as nonlinear bias parameter $(b_2)$ does not improve the cosmological constraints, but rather leads to a larger parameter bias compared to the baseline $b_1$-method.
We measure the genus of the galaxy distribution in two-dimensional slices of the SDSS-III BOSS catalog to constrain the cosmological parameters governing the expansion history of the Universe. The BOSS catalogs are divided into twelve concentric shells over the redshift range $0.25 < z < 0.6$ and we repeatedly measure the genus from the two-dimensional galaxy density fields, each time varying the cosmological parameters used to infer the distance-redshift relation to the shells. We also indirectly reconstruct the two-dimensional genus amplitude using the three-dimensional genus measured from SDSS Main Galaxy Sample with galaxies at low redshift $z < 0.12$. We combine the low- and high-redshift measurements, finding the cosmological model which minimizes the redshift evolution of the genus amplitude, using the fact that this quantity should be conserved. Being a distance measure, the test is sensitive to the matter density parameter ($Omega_{rm m}$) and equation of state of dark energy ($w_{rm de}$). We find a constraint of $w_{rm de} = -1.05^{+0.13}_{-0.12}$, $Omega_{rm m} = 0.303 pm 0.036$ after combining the high- and low-redshift measurements and combining with Planck CMB data. Higher redshift data and combining data sets at low redshift will allow for stronger constraints.
The ability to obtain reliable point estimates of model parameters is of crucial importance in many fields of physics. This is often a difficult task given that the observed data can have a very high number of dimensions. In order to address this problem, we propose a novel approach to construct parameter estimators with a quantifiable bias using an order expansion of highly compressed deep summary statistics of the observed data. These summary statistics are learned automatically using an information maximising loss. Given an observation, we further show how one can use the constructed estimators to obtain approximate Bayes computation (ABC) posterior estimates and their corresponding uncertainties that can be used for parameter inference using Gaussian process regression even if the likelihood is not tractable. We validate our method with an application to the problem of cosmological parameter inference of weak lensing mass maps. We show in that case that the constructed estimators are unbiased and have an almost optimal variance, while the posterior distribution obtained with the Gaussian process regression is close to the true posterior and performs better or equally well than comparable methods.
We present measurements of the two-dimensional genus of the SDSS-III BOSS catalogs to constrain cosmological parameters governing the shape of the matter power spectrum. The BOSS data are divided into twelve concentric shells over the redshift range $0.2 < z < 0.6$, and we extract the genus from the projected two-dimensional galaxy density fields. We compare the genus amplitudes to their Gaussian expectation values, exploiting the fact that this quantity is relatively insensitive to non-linear gravitational collapse. The genus amplitude provides a measure of the shape of the linear matter power spectrum, and is principally sensitive to $Omega_{rm c}h^{2}$ and scalar spectral index $n_{rm s}$. A strong negative degeneracy between $Omega_{rm c}h^{2}$ and $n_{rm s}$ is observed, as both can increase small scale power by shifting the peak and tilting the power spectrum respectively. We place a constraint on the particular combination $n_{rm s}^{3/2} Omega_{rm c}h^{2}$ -- we find $n_{rm s}^{3/2} Omega_{rm c}h^{2} = 0.1121 pm 0.0043$ after combining the LOWZ and CMASS data sets, assuming a flat $Lambda$CDM cosmology. This result is practically insensitive to reasonable variations of the power spectrum amplitude and linear galaxy bias. Our results are consistent with the Planck best fit $n_{rm s}^{3/2}Omega_{rm c}h^{2} = 0.1139 pm 0.0009$.
Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including CAMB, Planck, cosmic shear calculations, and a suite of samplers. We illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
