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Register a new userSimulations of BAO reconstruction with a quasar Lyman-alpha survey
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The imprint of Baryonic Acoustic Oscillations (BAO) on the matter power spectrum can be constrained using the neutral hydrogen density in the intergalactic medium as a tracer of the matter density. One of the goals of the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS-III) is to derive the Hubble expansion rate and the angular scale from the BAO signal in the IGM. To this aim, the Lyman-alpha forest of 10^5 quasars will be observed in the redshift range 2.2<z<3.5 and over 10,000 deg^2. We simulated the BOSS QSO survey to estimate the statistical accuracy on the BAO scale determination provided by such a large scale survey. In particular, we discuss the effect of the poorly constrained estimate of the unabsorbed intrinsic quasar spectrum. The volume of current N-body simulations being too small for such studies, we resorted to Gaussian random field (GRF) simulations. We validated the use of GRFs by comparing the output of GRF simulations with that of the Horizon N-body simulation with the same initial conditions. Realistic mock samples of QSO Lyman-alpha forest were generated; their power spectrum was computed and fitted to obtain the BAO scale. The rms of the results for 100 different simulations provides an estimate of the statistical error expected from the BOSS survey. We confirm the results from Fisher matrix estimate. In the absence of error on the unabsorbed quasar spectrum, the BOSS quasar survey should measure the BAO scale with an error of the order of 2.3%, or the transverse and radial BAO scales separately with errors of the order of 6.8% and 3.9%, respectively. The significance of the BAO detection is assessed by an average Deltachi^2=17 but for individual realizations Deltachi^2 ranges from 2 t o 35. The error on the unabsorbed quasar spectrum increases the error on the BAO scale by 10 to 20% and results in a sub percent bias.
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Several interesting Dark Matter (DM) models invoke a dark sector leading to two types of relic particles, possibly interacting with each other: non-relativistic DM, and relativistic Dark Radiation (DR). These models have interesting consequences for cosmological observables, and could in principle solve problems like the small-scale cold DM crisis, Hubble tension, and/or low $sigma_8$ value. Their cosmological behaviour is captured by the ETHOS parametrisation, which includes a DR-DM scattering rate scaling like a power-law of the temperature, $T^n$. Scenarios with $n=0$, $2$, or $4$ can easily be realised in concrete dark sector set-ups. Here we update constraints on these three scenarios using recent CMB, BAO, and high-resolution Lyman-$alpha$ data. We introduce a new Lyman-$alpha$ likelihood that is applicable to a wide range of cosmological models with a suppression of the matter power spectrum on small scales. For $n=2$ and $4$, we find that Lyman-$alpha$ data strengthen the CMB+BAO bounds on the DM-DR interaction rate by many orders of magnitude. However, models offering a possible solution to the missing satellite problem are still compatible with our new bounds. For $n=0$, high-resolution Lyman-$alpha$ data bring no stronger constraints on the interaction rate than CMB+BAO data, except for extremely small values of the DR density. Using CMB+BAO data and a theory-motivated prior on the minimal density of DR, we find that the $n=0$ model can reduce the Hubble tension from $4.1sigma$ to $2.7sigma$, while simultaneously accommodating smaller values of the $sigma_8$ and $S_8$ parameters hinted by cosmic shear data.
Reconstruction techniques for intrinsic quasar continua are crucial for the precision study of Lyman-$alpha$ (Ly-$alpha$) and Lyman-$beta$ (Ly-$beta$) transmission at $z>5.0$, where the $lambda<1215 A$ emission of quasars is nearly completely absorbed. While the number and quality of spectroscopic observations has become theoretically sufficient to quantify Ly-$alpha$ transmission at $5.0<z<6.0$ to better than $1%$, the biases and uncertainties arising from predicting the unabsorbed continuum are not known to the same level. In this paper, we systematically evaluate eight reconstruction techniques on a unified testing sample of $2.7<z<3.5$ quasars drawn from eBOSS. The methods include power-law extrapolation, stacking of neighbours, and six variants of Principal Component Analysis (PCA) using direct projection, fitting of components, or neural networks to perform weight mapping. We find that power-law reconstructions and the PCA with fewest components and smallest training sample display the largest biases in the Ly-$alpha$ forest ($-9.58%/+8.22%$ respectively). Power-law extrapolations have larger scatters than previously assumed of $+13.1%/-13.2%$ over Ly-$alpha$ and $+19.9%/-20.1%$ over Ly-$beta$. We present two new PCAs which achieve the best current accuracies of $9%$ for Ly-$alpha$ and $17%$ for Ly-$beta$. We apply the eight techniques after accounting for wavelength-dependent biases and scatter to a sample $19$ quasars at $z>5.7$ with IR X-Shooter spectroscopy, obtaining well-characterised measurements for the mean flux transmission at $4.7<z<6.3$. Our results demonstrate the importance of testing and, when relevant, training, continuum reconstruction techniques in a systematic way.
We propose a new method for fitting the full-shape of the Lyman-$alpha$ (Ly$alpha$) forest three-dimensional (3D) correlation function in order to measure the Alcock-Paczynski (AP) effect. Our method preserves the robustness of baryon acoustic oscillations (BAO) analyses, while also providing extra cosmological information from a broader range of scales. We compute idealized forecasts for the Dark Energy Spectroscopic Instrument (DESI) using the Ly$alpha$ auto-correlation and its cross-correlation with quasars, and show how this type of analysis improves cosmological constraints. The DESI Ly$alpha$ BAO analysis is expected to measure $H(z_mathrm{eff})r_mathrm{d}$ and $D_mathrm{M}(z_mathrm{eff})/r_mathrm{d}$ with a precision of $sim0.9%$ each, where $H$ is the Hubble parameter, $r_mathrm{d}$ is the comoving BAO scale, $D_mathrm{M}$ is the comoving angular diameter distance and the effective redshift of the measurement is $z_mathrm{eff}simeq2.3$. By fitting the AP parameter from the full shape of the two correlations, we show that we can obtain a precision of $sim0.5-0.6%$ on each of $H(z_mathrm{eff})r_mathrm{d}$ and $D_mathrm{M}(z_mathrm{eff})/r_mathrm{d}$. Furthermore, we show that a joint full-shape analysis of the Ly$alpha$ auto-correlation and its cross-correlation with quasars can measure the linear growth rate times the amplitude of matter fluctuations in spheres of $8;h^{-1}$Mpc, $fsigma_8(z_mathrm{eff})$. Such an analysis could provide the first ever measurement of $fsigma_8(z_mathrm{eff})$ at redshift $z_mathrm{eff}>2$. By combining this with the quasar auto-correlation in a joint analysis of the three high-redshift two-point correlation functions, we show that DESI could be able to measure $fsigma_8(z_mathrm{eff}simeq2.3)$ with a precision of $5-12%$, depending on the smallest scale fitted.
The statistical power of Lyman-${alpha}$ forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, we present LyaCoLoRe: a package for producing synthetic Lyman-${alpha}$ forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers - high column density systems and metal absorbers - which act as potential complications for BAO analyses.
We describe mock data-sets generated to simulate the high-redshift quasar sample in Data Release 11 (DR11) of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). The mock spectra contain Ly{alpha} forest correlations useful for studying the 3D correlation function including Baryon Acoustic Oscillations (BAO). They also include astrophysical effects such as quasar continuum diversity and high-density absorbers, instrumental effects such as noise and spectral resolution, as well as imperfections introduced by the SDSS pipeline treatment of the raw data. The Ly{alpha} forest BAO analysis of the BOSS collaboration, described in Delubac et al. 2014, has used these mock data-sets to develop and cross-check analysis procedures prior to performing the BAO analysis on real data, and for continued systematic cross checks. Tests presented here show that the simulations reproduce sufficiently well important characteristics of real spectra. These mock data-sets will be made available together with the data at the time of the Data Release 11.
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