ABSTRACT
We use data from the DESI Legacy Survey imaging to probe the galaxy density field in tomographic slices covering the redshift range 0 < z < 0.8. After careful consideration of completeness ...corrections and galactic cuts, we obtain a sample of 4.9 × 107 galaxies covering 17 739 deg2. We derive photometric redshifts with precision σz/(1 + z) = 0.012−0.015, and compare with alternative estimates.1 Cross-correlation of the tomographic galaxy maps with Planck maps of cosmic microwave background (CMB) temperature and lensing convergence probe the growth of structure since z = 0.8. The signals are compared with a fiducial Planck ΛCDM model, and require an overall scaling in amplitude of Aκ = 0.901 ± 0.026 for the lensing cross-correlation and AISW = 0.984 ± 0.349 for the temperature cross-correlation, interpreted as the integrated Sachs–Wolfe effect. The ISW amplitude is consistent with the fiducial Λ cold dark matter (ΛCDM) prediction, but lies significantly below the prediction of the AvERA model of Rácz et al., which has been proposed as an alternative explanation for cosmic acceleration. Within ΛCDM, our low amplitude for the lensing cross-correlation requires a reduction either in fluctuation normalization or in matter density compared to the Planck results, so that $\Omega _\mathrm{ m}^{0.78}\sigma _8=0.297\pm 0.009$. In combination with the total amplitude of CMB lensing, this favours a shift mainly in density: Ωm = 0.274 ± 0.024. We discuss the consistency of this figure with alternative evidence. A conservative compromise between lensing and primary CMB constraints would require Ωm = 0.296 ± 0.006, where the 95 per cent confidence regions of both probes overlap.
ABSTRACT
We introduce zeus, a well-tested Python implementation of the Ensemble Slice Sampling (ESS) method for Bayesian parameter inference. ESS is a novel Markov chain Monte Carlo (MCMC) algorithm ...specifically designed to tackle the computational challenges posed by modern astronomical and cosmological analyses. In particular, the method requires only minimal hand-tuning of 1−2 hyperparameters that are often trivial to set; its performance is insensitive to linear correlations and it can scale up to 1000s of CPUs without any extra effort. Furthermore, its locally adaptive nature allows to sample efficiently even when strong non-linear correlations are present. Lastly, the method achieves a high performance even in strongly multimodal distributions in high dimensions. Compared to emcee, a popular MCMC sampler, zeus performs 9 and 29 times better in a cosmological and an exoplanet application, respectively.
ABSTRACT
We cross-correlate maps of the thermal Sunyaev–Zeldovich (tSZ) Compton-y parameter published by Planck with the projected distribution of galaxies in a set of low-redshift tomographic bins. ...We use the nearly full-sky 2MASS Photometric Redshift and WISE × SuperCOSMOS public catalogues, covering the redshift range z ≲ 0.4. Our measurements allow us to place constraints on the redshift dependence of the mass–observable relation for tSZ cluster count analyses in terms of the so-called hydrostatic mass bias parameter $1-b_{\scriptscriptstyle \rm H}$. These results can also be interpreted as measurements of the bias-weighted average gas pressure 〈bPe〉 as a function of redshift, a quantity that can be related to the thermodynamics of gas inside haloes and used to constrain energy injection processes. We measure $1-b_{\scriptscriptstyle \rm H}$ with $\sim \!13{{\ \rm per\ cent}}$ precision in six equispaced redshift bins, and find no evidence for a redshift-dependent mass bias parameter, in agreement with previous analyses. Our mean value of $1-b_{\scriptscriptstyle \rm H}= 0.59\pm 0.03$ is also in good agreement with the one estimated by the joint analysis of Planck cluster counts and cosmic microwave background anisotropies. Our measurements of 〈bPe〉, at the level of $\sim \!10{{\ \rm per\ cent}}$ in each bin, are the most stringent constraints on the redshift dependence of this parameter to date, and agree well both with previous measurements and with theoretical expectations from shock-heating models.
A long-standing question in cosmology is whether gravitational lensing changes the distance–redshift relation D (z) or the mean flux density of sources. Interest in this has been rekindled by recent ...studies in non-linear relativistic perturbation theory that find biases in both the area of a surface of constant redshift and in the mean distance to this surface, with a fractional bias in both cases of the order of the mean squared convergence 〈κ2〉. Any such area bias could alter cosmic microwave background (CMB) cosmology, and the corresponding bias in mean flux density could affect supernova cosmology. We show that the perturbation to the area of a surface of constant redshift is in reality much smaller, being of the order of the cumulative bending angle squared, or roughly a part-in-a-million effect. This validates the arguments of Weinberg that the mean magnification of sources is unity and of Kibble & Lieu that the mean direction-averaged inverse magnification is unity. It also validates the conventional treatment of CMB lensing. But the existence of a scatter in magnification will cause any non-linear function of these conserved quantities to be statistically biased. The fractional bias in such quantities is generally of order 〈κ2〉, which is orders of magnitude larger than the area perturbation. Claims for large bias in area or flux density of sources appear to have resulted from misinterpretation of such effects: they do not represent a new non-Newtonian effect, nor do they invalidate standard cosmological analyses.
Redshift-space distortions around voids Cai, Yan-Chuan; Taylor, Andy; Peacock, John A ...
Monthly notices of the Royal Astronomical Society,
11/2016, Volume:
462, Issue:
3
Journal Article
Peer reviewed
We have derived estimators for the linear growth rate of density fluctuations using the cross-correlation function (CCF) of voids and haloes in redshift space. In linear theory, this CCF contains ...only monopole and quadrupole terms. At scales greater than the void radius, linear theory is a good match to voids traced out by haloes; small-scale random velocities are unimportant at these radii, only tending to cause small and often negligible elongation of the CCF near its origin. By extracting the monopole and quadrupole from the CCF, we measure the linear growth rate without prior knowledge of the void profile or velocity dispersion. We recover the linear growth parameter β to 9 per cent precision from an effective volume of 3( h
−1Gpc)3 using voids with radius >25 h
−1Mpc. Smaller voids are predominantly sub-voids, which may be more sensitive to the random velocity dispersion; they introduce noise and do not help to improve measurements. Adding velocity dispersion as a free parameter allows us to use information at radii as small as half of the void radius. The precision on β is reduced to 5 per cent. Voids show diverse shapes in redshift space, and can appear either elongated or flattened along the line of sight. This can be explained by the competing amplitudes of the local density contrast, plus the radial velocity profile and its gradient. The distortion pattern is therefore determined solely by the void profile and is different for void-in-cloud and void-in-void. This diversity of redshift-space void morphology complicates measurements of the Alcock–Paczynski effect using voids.
Key cosmological applications require the three-dimensional (3D) galaxy distribution on the entire celestial sphere. These include measuring the gravitational pull on the Local Group, estimating the ...large-scale bulk flow, and testing the Copernican principle. However, the largest all-sky redshift surveys-the 2MASS Redshift Survey and IRAS Point Source Catalog Redshift Survey-have median redshifts of only z = 0.03 and sample the very local universe. All-sky galaxy catalogs exist that reach much deeper-SuperCOSMOS in the optical, the Two Micron All Sky Survey (2MASS) in the near-IR, and WISE in the mid-IR-but these lack complete redshift information. At present, the only rapid way toward larger 3D catalogs covering the whole sky is through photometric redshift techniques. The all-sky photo-z catalogs, with a median z ~ 0.1 for the 2MPZ, and significantly deeper for future WISE-based samples, will be the largest and most complete of their kind for the foreseeable future.
ABSTRACT
We develop a new Multitracer Halo Occupation Distribution (MTHOD) framework for the galaxy distribution and apply it to the extended Baryon Oscillation Spectroscopic Survey (eBOSS) final ...data between z = 0.7 − 1.1. We obtain a best fitting MTHOD for each tracer and describe the host halo properties of these galaxies. The mean halo masses for LRGs, ELGs, and QSOs are found to be $1.9 \times 10^{13} \, h^{-1}M_\odot$, $1.1 \times 10^{12} \, h^{-1}M_\odot$, and $5 \times 10^{12} \, h^{-1}M_\odot$ respectively in the eBOSS data. We use the MTHOD framework to create mock galaxy catalogues and predict auto- and cross-correlation functions for all the tracers. Comparing these results with data, we investigate galactic conformity, the phenomenon whereby the properties of neighbouring galaxies are mutually correlated in a manner that is not captured by the basic halo model. We detect 1-halo conformity at more than 3σ statistical significance, while obtaining upper limits on 2-halo conformity. We also look at the environmental dependence of the galaxy quenching efficiency and find that halo mass driven quenching successfully explains the behaviour in high density regions, but it fails to describe the quenching efficiency in low density regions. In particular, we show that the quenching efficiency in low density filaments is higher in the observed data, as compared to the prediction of the MTHOD with halo mass driven quenching. The mock galaxy catalogue constructed in this paper is publicly available on this website1.
ABSTRACT
We constrain models of the galaxy distribution in the cosmic web using data from the Galaxy and Mass Assembly (GAMA) survey. We model the redshift-space behaviour of the 2-point correlation ...function (2pcf) and the recently proposed Voronoi volume function (VVF) – which includes information beyond two-point statistics. We extend the standard halo model using extra satellite degrees of freedom and two assembly bias parameters: αcen and αsat, which correlate the occupation numbers of central and satellite galaxies with their host halo’s tidal environment, respectively. We measure $\alpha _{\rm sat}=1.44^{+0.25}_{-0.43}$ and $\alpha _{\rm cen}=-0.79^{+0.29}_{-0.11}$ using a combination of 2pcf and VVF measurements, representing a detection of assembly bias at the 3.3σ (2.4σ) significance level for satellite (central) galaxies. This result remains robust to possible anisotropies in the halocentric distribution of satellites as well as technicalities of estimating the data covariance. We show that the growth rate (fσ8) deduced using models with assembly bias is about 7 per cent (i.e. 1.5σ) lower than if assembly bias is ignored. When projected on to the Ωm–σ8 plane, the model constraints without assembly bias overlap with Planck expectations, while allowing assembly bias introduces significant tension with Planck, preferring either a lower Ωm or a lower σ8. Finally, we find that the all-galaxy weak-lensing signal is unaffected by assembly bias, but the central and satellite sub-populations individually show significantly different signals in the presence of assembly bias. Our results illustrate the importance of accurately modelling galaxy formation for cosmological inference from future surveys.
ABSTRACT
We introduce preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial geometry. ...PMC utilizes a Normalizing Flow (NF) in order to decorrelate the parameters of the distribution and then proceeds by sampling from the preconditioned target distribution using an adaptive Sequential Monte Carlo (SMC) scheme. The results produced by PMC include samples from the posterior distribution and an estimate of the model evidence that can be used for parameter inference and model comparison, respectively. The aforementioned framework has been thoroughly tested in a variety of challenging target distributions achieving state-of-the-art sampling performance. In the cases of primordial feature analysis and gravitational wave inference, PMC is approximately 50 and 25 times faster, respectively, than nested sampling (NS). We found that in higher dimensional applications, the acceleration is even greater. Finally, PMC is directly parallelisable, manifesting linear scaling up to thousands of CPUs.
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