A new method to measure galaxy bias by combining the density and weak lensing fields

 

Authors: A. Pujol, C. Chang, E. Gaztañaga et al.
Journal: MNRAS
Year: 10/2016
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Abstract

We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.

The Dark Energy Survey and operations: years 1 to 3

 

Authors: H. T. Diehl, E. Neilsen, R. Gruendl et al.
Journal: Proceedings of the SPIE
Year: 07/2016
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Abstract

The Dark Energy Survey (DES) is an operating optical survey aimed at understanding the accelerating expansion of the universe using four complementary methods: weak gravitational lensing, galaxy cluster counts, baryon acoustic oscillations, and Type Ia supernovae. To perform the 5000 sq-degree wide field and 30 sq-degree supernova surveys, the DES Collaboration built the Dark Energy Camera (DECam), a 3 square-degree, 570-Megapixel CCD camera that was installed at the prime focus of the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory (CTIO). DES has completed its third observing season out of a nominal five. This paper describes DES "Year 1" (Y1) to "Year 3" (Y3), the strategy, an outline of the survey operations procedures, the efficiency of operations and the causes of lost observing time. It provides details about the quality of the first three season's data, and describes how we are adjusting the survey strategy in the face of the El Niño Southern Oscillation.

Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

 

Authors: C. Chang, A. Pujol, E. Gaztañaga et al.
Journal: MNRAS
Year: 07/2016
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Abstract

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ˜116 deg2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2-0.4), 0.97 ± 0.15 (z = 0.4-0.6), 1.38 ± 0.39 (z = 0.6-0.8), and 1.45 ± 0.56 (z = 0.8-1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

nIFTy cosmology: comparison of galaxy formation models

 

Authors: A. Knebe, F. R. Pearce, P. A. Thomas et al.
Journal: MNRAS 
Year: 08/2015
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Abstract

We present a comparison of 14 galaxy formation models: 12 different semi-analytical models and 2 halo occupation distribution models for galaxy formation based upon the same cosmological simulation and merger tree information derived from it. The participating codes have proven to be very successful in their own right but they have all been calibrated independently using various observational data sets, stellar models, and merger trees. In this paper, we apply them without recalibration and this leads to a wide variety of predictions for the stellar mass function, specific star formation rates, stellar-to-halo mass ratios, and the abundance of orphan galaxies. The scatter is much larger than seen in previous comparison studies primarily because the codes have been used outside of their native environment within which they are well tested and calibrated. The purpose of the `nIFTy comparison of galaxy formation models' is to bring together as many different galaxy formation modellers as possible and to investigate a common approach to model calibration. This paper provides a unified description for all participating models and presents the initial, uncalibrated comparison as a baseline for our future studies where we will develop a common calibration framework and address the extent to which that reduces the scatter in the model predictions seen here.

The Dark Energy Survey and operations: Year 1

 

Authors: H. T. Diehl, T. M. C. Abbott, J. Annis et al.
Journal: Proceedings of the SPIE
Year: 08/2014
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Abstract

The Dark Energy Survey (DES) is a next generation optical survey aimed at understanding the accelerating expansion of the universe using four complementary methods: weak gravitational lensing, galaxy cluster counts, baryon acoustic oscillations, and Type Ia supernovae. To perform the 5000 sq-degree wide field and 30 sq-degree supernova surveys, the DES Collaboration built the Dark Energy Camera (DECam), a 3 square-degree, 570-Megapixel CCD camera that was installed at the prime focus of the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory (CTIO). DES started its first observing season on August 31, 2013 and observed for 105 nights through mid-February 2014. This paper describes DES "Year 1" (Y1), the strategy and goals for the first year's data, provides an outline of the operations procedures, lists the efficiency of survey operations and the causes of lost observing time, provides details about the quality of the first year's data, and hints at the "Year 2" plan and outlook.

Are the halo occupation predictions consistent with large-scale galaxy clustering?

 

Authors: A. Pujol and E. Gaztañaga
Journal: MNRAS 
Year: 08/2014
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Abstract

We study how well we can reconstruct the two-point clustering of galaxies on linear scales, as a function of mass and luminosity, using the halo occupation distribution (HOD) in several semi-analytical models (SAMs) of galaxy formation from the Millennium Simulation. We find that the HOD with Friends-of-Friends groups can reproduce galaxy clustering better than gravitationally bound haloes. This indicates that Friends-of-Friends groups are more directly related to the clustering of these regions than the bound particles of the overdensities. In general, we find that the reconstruction works at best to ≃5 per cent accuracy: it underestimates the bias for bright galaxies. This translates to an overestimation of 50 per cent in the halo mass when we use clustering to calibrate mass. We also found a degeneracy on the mass prediction from the clustering amplitude that affects all the masses. This effect is due to the clustering dependence on the host halo substructure, an indication of assembly bias. We show that the clustering of haloes of a given mass increases with the number of subhaloes, a result that only depends on the underlying matter distribution. As the number of galaxies increases with the number of subhaloes in SAMs, this results in a low bias for the HOD reconstruction. We expect this effect to apply to other models of galaxy formation, including the real Universe, as long as the number of galaxies increases with the number of subhaloes. We have also found that the reconstructions of galaxy bias from the HOD model fail for low-mass haloes with M ≲ 3-5 × 1011 h-1 M. We find that this is because galaxy clustering is more strongly affected by assembly bias for these low masses.

Subhaloes gone Notts: the clustering properties of subhaloes

 

Authors: A. Pujol, E. Gaztañaga,  C. Giocoli et al.
Journal: MNRAS 
Year: 03/2014
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Abstract

We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and study their differences in the density profile, mass fraction and two-point correlation function of subhaloes in haloes. We also study the mass and vmax dependence of subhalo clustering. As the Aquarius Simulation has been run at different resolutions, we study the convergence with higher resolutions. We find that the agreement between finders is at around the 10 per cent level inside R200 and at intermediate resolutions when a mass threshold is applied, and better than 5 per cent when vmax is restricted instead of mass. However, some discrepancies appear in the highest resolution, underlined by an observed resolution dependence of subhalo clustering. This dependence is stronger for the smallest subhaloes, which are more clustered in the highest resolution, due to the detection of subhaloes within subhaloes (the sub-subhalo term). This effect modifies the mass dependence of clustering in the highest resolutions. We discuss implications of our results for models of subhalo clustering and their relation with galaxy clustering.