Quasar Host Environments: The view from Planck

We measure the far-infrared emission of the general quasar (QSO) population using Planck observations of the Baryon Oscillation Spectroscopic Survey QSO sample. By applying multi-component matched multi-filters to the seven highest Planck frequencies, we extract the amplitudes of dust, synchrotron and thermal Sunyaev-Zeldovich (SZ) signals for nearly 300,000 QSOs over the redshift range $0.1<z<5$. We bin these individually low signal-to-noise measurements to obtain the mean emission properties of the QSO population as a function of redshift. The emission is dominated by dust at all redshifts, with a peak at $z \sim 2$, the same location as the peak in the general cosmic star formation rate. Restricting analysis to radio-loud QSOs, we find synchrotron emission with a monochromatic luminosity at $100\,\rm{GHz}$ (rest-frame) rising from $\overline{L_{\rm synch}}=0$ to $0.2 \, {\rm L_\odot} {\rm Hz}^{-1}$ between $z=0$ and 3. The radio-quiet subsample does not show any synchrotron emission, but we detect thermal SZ between $z=2.5$ and 4; no significant SZ emission is seen at lower redshifts. Depending on the supposed mass for the halos hosting the QSOs, this may or may not leave room for heating of the halo gas by feedback from the QSO.Comment: 14 pages, 11 figures, accepted by A&

New approach for precise computation of Lyman-alpha forest power spectrum with hydrodynamical simulations

Current experiments are providing measurements of the flux power spectrum from the Lyman-α forests observed in quasar spectra with unprecedented accuracy. Their interpretation in terms of cosmological constraints requires specific simulations of at least equivalent precision. In this paper, we present a suite of cosmological N-body simulations with cold dark matter and baryons, specifically aiming at modeling the low-density regions of the inter-galactic medium as probed by the Lyman-α forests at high redshift. The simulations were run using the GADGET-3 code and were designed to match the requirements imposed by the quality of the current SDSS-III/BOSS or forthcoming SDSS-IV/eBOSS data. They are made using either 2 × 7683 1 billion or 2 × 1923 14 million particles, spanning volumes ranging from (25 Mpc h−1)3 for high-resolution simulations to (100 Mpc h−1)3 for large-volume ones. Using a splicing technique, the resolution is further enhanced to reach the equivalent of simulations with 2 × 30723 58 billion particles in a (100 Mpc h−1)3 box size, i.e. a mean mass per gas particle of 1.2 × 105M⊙ h−1. We show that the resulting power spectrum is accurate at the 2% level over the full range from a few Mpc to several tens of Mpc. We explore the effect on the one-dimensional transmitted-flux power spectrum of four cosmological parameters (ns, σ8, Ωm and H0) and two astrophysical parameters (T0 and γ) that are related to the heating rate of the intergalactic medium. By varying the input parameters around a central model chosen to be in agreement with the latest Planck results, we built a grid of simulations that allows the study of the impact on the flux power spectrum of these six relevant parameters. We improve upon previous studies by not only measuring the effect of each parameter individually, but also probing the impact of the simultaneous variation of each pair of parameters. We thus provide a full second-order expansion, including cross-terms, around our central model. We check the validity of the second-order expansion with independent simulations obtained either with different cosmological parameters or different seeds. Finally, a comparison to the one-dimensional Lyman-α forest power spectrum obtained with BOSS by [1] shows an excellent agreement

The large-scale Quasar-Lyman \alpha\ Forest Cross-Correlation from BOSS

We measure the large-scale cross-correlation of quasars with the Lyman \alpha\ forest absorption in redshift space, using ~ 60000 quasar spectra from Data Release 9 (DR9) of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is detected over a wide range of scales, up to comoving separations r of 80 Mpc/h. For r > 15 Mpc/h, we show that the cross-correlation is well fitted by the linear theory prediction for the mean overdensity around a quasar host halo in the standard \Lambda CDM model, with the redshift distortions indicative of gravitational evolution detected at high confidence. Using previous determinations of the Lyman \alpha\ forest bias factor obtained from the Lyman \alpha\ autocorrelation, we infer the quasar bias factor to be b_q = 3.64^+0.13_-0.15 at a mean redshift z=2.38, in agreement with previous measurements from the quasar auto-correlation. We also obtain a new estimate of the Lyman \alpha\ forest redshift distortion factor, \beta_F = 1.1 +/- 0.15, slightly larger than but consistent with the previous measurement from the Lyman \alpha\ forest autocorrelation. The simple linear model we use fails at separations r < 15 Mpc/h, and we show that this may reasonably be due to the enhanced ionization due to radiation from the quasars. We also provide the expected correction that the mass overdensity around the quasar implies for measurements of the ionizing radiation background from the line-of-sight proximity effect.Comment: 24 pages, 6 figures, published in JCA

Detection of Ly\beta auto-correlations and Ly\alpha-Ly\beta cross-correlations in BOSS Data Release 9

The Lyman-$\beta$ forest refers to a region in the spectra of distant quasars that lies between the rest-frame Lyman-$\beta$ and Lyman-$\gamma$ emissions. The forest in this region is dominated by a combination of absorption due to resonant Ly$\alpha$ and Ly$\beta$ scattering. When considering the 1D Ly$\beta$ forest in addition to the 1D Ly$\alpha$ forest, the full statistical description of the data requires four 1D power spectra: Ly$\alpha$ and Ly$\beta$ auto-power spectra and the Ly$\alpha$-Ly$\beta$ real and imaginary cross-power spectra. We describe how these can be measured using an optimal quadratic estimator that naturally disentangles Ly$\alpha$ and Ly$\beta$ contributions. Using a sample of approximately 60,000 quasar sight-lines from the BOSS Data Release 9, we make the measurement of the one-dimensional power spectrum of fluctuations due to the Ly$\beta$ resonant scattering. While we have not corrected our measurements for resolution damping of the power and other systematic effects carefully enough to use them for cosmological constraints, we can robustly conclude the following: i) Ly$\beta$ power spectrum and Ly$\alpha$-Ly$\beta$ cross spectra are detected with high statistical significance; ii) the cross-correlation coefficient is $\approx 1$ on large scales; iii) the Ly$\beta$ measurements are contaminated by the associated OVI absorption, which is analogous to the SiIII contamination of the Ly$\alpha$ forest. Measurements of the Ly$\beta$ forest will allow extension of the usable path-length for the Ly$\alpha$ measurements while allowing a better understanding of the physics of intergalactic medium and thus more robust cosmological constraints.Comment: 26 pages, 10 figures; matches version accepted by JCA

Characterizing unknown systematics in large scale structure surveys

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.Comment: 24 pages, 6 figures; Expanded discussion of results, added figure 2; Version to be published in JCA

Angular clustering properties of the DESI QSO target selection using DR9 Legacy Imaging Surveys

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next 5 yr. 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 multilayer 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 extended Baryon Oscillation Spectroscopic Survey (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 that 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.This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under contract no. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under contract no. AST-0950945 to the NSF’s National Optical–Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology, Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. ADM was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0019022

Sloan Digital Sky Survey III Photometric Quasar Clustering: Probing the Initial Conditions of the Universe using the Largest Volume

The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z = 0.5 and z = 2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans ~11,000 square degrees and probes a volume of 80(Gpc/h)^3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ~25% over a bin width of l ~10 - 15 on scales corresponding to matter-radiation equality and larger (l ~ 2 - 30). Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = -113+/-154 (1\sigma error). [Abridged]Comment: 35 pages, 15 figure