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Register a new userGalaxy clustering in the DESI Legacy Survey and its imprint on the CMB
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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 $4.9times 10^7$ galaxies covering 17 739 deg$^2$. We derive photometric redshifts with precision $sigma_z/(1+z)=0.012 - 0.015$, and compare with alternative estimates. Cross-correlation of the tomographic galaxy maps with Planck maps of CMB temperature and lensing convergence probe the growth of structure since $z=0.8$. The signals are compared with a fiducial Planck $Lambda$CDM model, and require an overall scaling in amplitude of $A_kappa=0.901pm 0.026$ for the lensing cross-correlation and $A_{rm ISW} = 0.984 pm 0.349$ for the temperature cross-correlation, interpreted as the Integrated Sachs-Wolfe effect. The ISW amplitude is consistent with the fiducial $Lambda$CDM prediction, but lies significantly below the prediction of the AvERA model of Racz et al. (2017), which has been proposed as an alternative explanation for cosmic acceleration. Within $Lambda$CDM, 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 $Omega_m^{0.78}sigma_8=0.297pm 0.009$. In combination with the total amplitude of CMB lensing, this favours a shift mainly in density: $Omega_m=0.274pm0.024$. We discuss the consistency of this figure with alternative evidence. A conservative compromise between lensing and primary CMB constraints would require $Omega_m=0.296pm0.006$, where the 95% confidence regions of both probes overlap.
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The imprints of large-scale structures on the Cosmic Microwave Background can be studied via the CMB lensing and Integrated Sachs-Wolfe (ISW) signals. In particular, the stacked ISW signal around supervoids has been claimed in several works to be anomalously high. In this study, we find cluster and void superstructures using four tomographic redshift bins with $0<z<0.8$ from the DESI Legacy Survey, and measure the stacked CMB lensing and ISW signals around them. To compare our measurements with $Lambda$CDM model predictions, we construct a mock catalogue with matched galaxy number density and bias, and apply the same photo-$z$ uncertainty as the data. The consistency between the mock and data is verified via the stacked galaxy density profiles around the superstructures and their quantity. The corresponding lensing convergence and ISW maps are then constructed and compared. The stacked lensing signal agrees with data well except at the highest redshift bin in density peaks, where the mock prediction is significantly higher, by approximately a factor 1.3. The stacked ISW signal is generally consistent with the mock prediction. We do not obtain a significant signal from voids, $A_{rm ISW}=-0.10pm0.69$, and the signal from clusters, $A_{rm ISW}=1.52pm0.72$, is at best weakly detected. However, these results are strongly inconsistent with previous claims of ISW signals at many times the level of the $Lambda$CDM prediction. We discuss the comparison of our results with past work in this area, and investigate possible explanations for this discrepancy.
Quintessence can cluster only on horizon scales. What is the effect on the observed matter distribution? To answer this, we need a relativistic approach that goes beyond the standard Newtonian calculation and deals properly with large scales. Such an approach has recently been developed for the case when dark energy is vacuum energy, which does not cluster at all. We extend this relativistic analysis to deal with dynamical dark energy. Using three quintessence potentials as examples, we compute the angular power spectrum for the case of an HI intensity map survey. Compared to the concordance model with the same small-scale power at z=0, quintessence boosts the angular power by up to ~15% at high redshifts, while power in the two models converges at low redshifts. The difference is mainly due to the background evolution, driven mostly by the normalization of the power spectrum today. The dark energy perturbations make only a small contribution on the largest scales, and a negligible contribution on smaller scales. Ironically, the dark energy perturbations remove the false boost of large-scale power that arises if we impose the (unphysical) assumption that the dark energy is smooth.
The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next five years. The aim of this work is to validate the quasar selection by studying the impact of imaging systematics as well as stellar and galactic contaminants, and to develop a procedure to mitigate them. Density fluctuations of quasar targets are found to be related to photometric properties such as seeing and depth of the Data Release 9 of the DESI Legacy Imaging Surveys. To model this complex relation, we explore machine learning algorithms (Random Forest and Multi-Layer Perceptron) as an alternative to the standard linear regression. Splitting the footprint of the Legacy Imaging Surveys into three regions according to photometric properties, we perform an independent analysis in each region, validating our method using eBOSS EZ-mocks. The mitigation procedure is tested by comparing the angular correlation of the corrected target selection on each photometric region to the angular correlation function obtained using quasars from the Sloan Digital Sky Survey (SDSS)Data Release 16. With our procedure, we recover a similar level of correlation between DESI quasar targets and SDSS quasars in two thirds of the total footprint and we show that the excess of correlation in the remaining area is due to a stellar contamination which should be removed with DESI spectroscopic data. We derive the Limber parameters in our three imaging regions and compare them to previous measurements from SDSS and the 2dF QSO Redshift Survey.
We perform a semi-automated search for strong gravitational lensing systems in the 9,000 deg$^2$ Dark Energy Camera Legacy Survey (DECaLS), part of the DESI Legacy Imaging Surveys (Dey et al.). The combination of the depth and breadth of these surveys are unparalleled at this time, making them particularly suitable for discovering new strong gravitational lensing systems. We adopt the deep residual neural network architecture (He et al.) developed by Lanusse et al. for the purpose of finding strong lenses in photometric surveys. We compile a training set that consists of known lensing systems in the Legacy Surveys and DES as well as non-lenses in the footprint of DECaLS. In this paper we show the results of applying our trained neural network to the cutout images centered on galaxies typed as ellipticals (Lang et al.) in DECaLS. The images that receive the highest scores (probabilities) are visually inspected and ranked. Here we present 335 candidate strong lensing systems, identified for the first time.
(abridged) We investigate the signatures left by the cosmic neutrino background on the clustering of matter, CDM+baryons and halos in redshift-space using a set of more than 1000 N-body and hydrodynamical simulations with massless and massive neutrinos. We find that the effect neutrinos induce on the clustering of CDM+baryons in redshift-space on small scales is almost entirely due to the change in $sigma_8$. Neutrinos imprint a characteristic signature in the quadrupole of the matter (CDM+baryons+neutrinos) field on small scales, that can be used to disentangle the effect of $sigma_8$ and $M_ u$. We show that the effect of neutrinos on the clustering of halos is very different, on all scales, to the one induced by $sigma_8$. We find that the effects of neutrinos of the growth rate of CDM+baryons ranges from $sim0.3%$ to $2%$ on scales $kin[0.01, 0.5]~h{rm Mpc}^{-1}$ for neutrinos with masses $M_ u leqslant 0.15$ eV. We compute the bias between the momentum of halos and the momentum of CDM+baryon and find it to be 1 on large scales for all models with massless and massive neutrinos considered. This point towards a velocity bias between halos and total matter on large scales that it is important to account for in order to extract unbiased neutrino information from velocity/momentum surveys such as kSZ observations. We show that baryonic effects can affect the clustering of matter and CDM+baryons in redshift-space by up to a few percent down to $k=0.5~h{rm Mpc}^{-1}$. We find that hydrodynamics and astrophysical processes, as implemented in our simulations, only distort the relative effect that neutrinos induce on the anisotropic clustering of matter, CDM+baryons and halos in redshift-space by less than $1%$. Thus, the effect of neutrinos in the fully non-linear regime can be written as a transfer function with very weak dependence on astrophysics.
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