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Register a new userThe Lyman-alpha forest in three dimensions: measurements of large scale flux correlations from BOSS 1st-year data
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Using a sample of approximately 14,000 z>2.1 quasars observed in the first year of the Baryon Oscillation Spectroscopic Survey (BOSS), we measure the three-dimensional correlation function of absorption in the Lyman-alpha forest. The angle-averaged correlation function of transmitted flux (F = exp(-tau)) is securely detected out to comoving separations of 60 Mpc/h, the first detection of flux correlations across widely separated sightlines. A quadrupole distortion of the redshift-space correlation function by peculiar velocities, the signature of the gravitational instability origin of structure in the Lyman-alpha forest, is also detected at high significance. We obtain a good fit to the data assuming linear theory redshift-space distortion and linear bias of the transmitted flux, relative to the matter fluctuations of a standard LCDM cosmological model (inflationary cold dark matter with a cosmological constant). At 95% confidence, we find a linear bias parameter 0.16<b<0.24 and redshift-distortion parameter 0.44<beta<1.20, at central redshift z=2.25, with a well constrained combination b(1+beta)=0.336 +/- 0.012. The errors on beta are asymmetric, with beta=0 excluded at over 5 sigma confidence level. The value of beta is somewhat low compared to theoretical predictions, and our tests on synthetic data suggest that it is depressed (relative to expectations for the Lyman-alpha forest alone) by the presence of high column density systems and metal line absorption. These results set the stage for cosmological parameter determinations from three-dimensional structure in the Lyman-alpha forest, including anticipated constraints on dark energy from baryon acoustic oscillations.
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We present the BOSS Lyman-alpha (Lya) Forest Sample from SDSS Data Release 9, comprising 54,468 quasar spectra with zqso > 2.15 suitable for Lya forest analysis. This data set probes the intergalactic medium with absorption redshifts 2.0 < z_alpha < 5.7 over an area of 3275 square degrees, and encompasses an approximate comoving volume of 20 h^-3 Gpc^3. With each spectrum, we have included several products designed to aid in Lya forest analysis: improved sky masks that flag pixels where data may be unreliable, corrections for known biases in the pipeline estimated noise, masks for the cores of damped Lya systems and corrections for their wings, and estimates of the unabsorbed continua so that the observed flux can be converted to a fractional transmission. The continua are derived using a principal component fit to the quasar spectrum redwards of restframe Lya (lambda > 1216 Ang), extrapolated into the forest region and normalized by a linear function to fit the expected evolution of the Lya forest mean-flux. The estimated continuum errors are ~5% rms. We also discuss possible systematics arising from uncertain spectrophotometry and artifacts in the flux calibration; global corrections for the latter are provided. Our sample provides a convenient starting point for users to analyze clustering in BOSS Lya forest data, and it provides a fiducial data set that can be used to compare results from different analyses of baryon acoustic oscillations in the Lya forest. The full data set is available from the SDSS-III DR9 web site.
Using the Ly$alpha$ mass assignment scheme (LyMAS), we make theoretical predictions for the 3-dimensional 3-point correlation function (3PCF) of the Ly$alpha$ forest at redshift $z=2.3$. We bootstrap results from the (100 $h^{-1} mbox{ Mpc}$)$^3$ Horizon hydrodynamic simulation to a (1 $h^{-1}$ Gpc)$^3$ $N$-body simulation, considering both a uniform UV background (UVB) and a fluctuating UVB sourced by quasars with a comoving $n_q approx 10^{-5}$ $h^3$ Mpc$^{-3}$ placed either in massive halos or randomly. On scales of $10-30$ $h^{-1} mbox{ Mpc}$, the flux 3PCF displays hierarchical scaling with the square of the 2PCF, but with an unusual value of $Q equiv zeta_{123}/(xi_{12} xi_{13} + xi_{12} xi_{23} + xi_{13} xi_{23}) approx -4.5$ that reflects the low bias of the Ly$alpha$ forest and the anti-correlation between mass density and transmitted flux. For halo-based quasars and an ionizing photon mean free path of $lambda = 300$ $h^{-1} mbox{ Mpc}$ comoving, UVB fluctuations moderately depress the 2PCF and 3PCF, with cancelling effects on $Q$. For $lambda = 100$ $h^{-1} mbox{ Mpc}$ or 50 $h^{-1} mbox{ Mpc}$, UVB fluctuations substantially boost the 2PCF and 3PCF on large scales, shifting the hierarchical ratio to $Q approx -3$. We scale our simulation results to derive rough estimate of the 3PCF detectability in observational data sets for the redshift range $z=2.1 - 2.6$. At $r = 10$ $h^{-1} mbox{ Mpc}$ and 20 $h^{-1} mbox{ Mpc}$, we predict a signal-to-noise (SNR) of $sim$ 9 and $sim$ 7, respectively, for both BOSS and eBOSS, and $sim$ 37 and $sim$ 25 for DESI. At $r = 40$ $h^{-1} mbox{ Mpc}$ the predicted SNR is lower by $sim$ 3$-$5 times. Measuring the flux 3PCF would be a novel test of the conventional paradigm of the Ly$alpha$ forest and help separate the contributions of UVB fluctuations and density fluctuations to Ly$alpha$ forest clustering.
(Abridged) We detect the large-scale structure of Lya emission in the Universe at redshifts z=2-3.5 by measuring the cross-correlation of Lya surface brightness with quasars in SDSS/BOSS. We use a million spectra targeting Luminous Red Galaxies at z<0.8, after subtracting a best fit model galaxy spectrum from each one, as an estimate of the high-redshift Lya surface brightness. The quasar-Lya emission cross-correlation we detect has a shape consistent with a LambdaCDM model with Omega_M =0.30^+0.10-0.07. The predicted amplitude of this cross-correlation is proportional to the product of the mean Lya surface brightness, <mu_alpha>, the amplitude of mass fluctuations, and the quasar and Lya emission bias factors. Using known values, we infer <mu_alpha>(b_alpha/3) = (3.9 +/- 0.9) x 10^-21 erg/s cm^-2 A^-1 arcsec^-2, where b_alpha is the Lya emission bias factor. If the dominant sources of Lya emission are star forming galaxies, we infer rho_SFR = (0.28 +/- 0.07) (3/b_alpha) /yr/Mpc^3 at z=2-3.5. For b_alpha=3, this value is a factor of 21-35 above previous estimates from individually detected Lya emitters, although consistent with the total rho_SFR derived from dust-corrected, continuum UV surveys. 97% of the Lya emission in the Universe at these redshifts is therefore undetected in previous surveys of Lya emitters. Our measurement is much greater than seen from stacking analyses of faint halos surrounding previously detected Lya emitters, but we speculate that it arises from similar Lya halos surrounding all luminous star-forming galaxies. We also detect redshift space anisotropy of the quasar-Lya emission cross-correlation, finding evidence at the 3.0 sigma level that it is radially elongated, consistent with distortions caused by radiative-transfer effects (Zheng et al. (2011)). Our measurements represent the first application of the intensity mapping technique to optical observations.
This work presents a new physically-motivated supervised machine learning method, Hydro-BAM, to reproduce the three-dimensional Lyman-$alpha$ forest field in real and in redshift space learning from a reference hydrodynamic simulation, thereby saving about 7 orders of magnitude in computing time. We show that our method is accurate up to $ksim1,h,rm{Mpc}^{-1}$ in the one- (PDF), two- (power-spectra) and three-point (bi-spectra) statistics of the reconstructed fields. When compared to the reference simulation including redshift space distortions, our method achieves deviations of $lesssim2%$ up to $k=0.6,h,rm{Mpc}^{-1}$ in the monopole, $lesssim5%$ up to $k=0.9,h,rm{Mpc}^{-1}$ in the quadrupole. The bi-spectrum is well reproduced for triangle configurations with sides up to $k=0.8,h,rm{Mpc}^{-1}$. In contrast, the commonly-adopted Fluctuating Gunn-Peterson approximation shows significant deviations already neglecting peculiar motions at configurations with sides of $k=0.2-0.4,h,rm{Mpc}^{-1}$ in the bi-spectrum, being also significantly less accurate in the power-spectrum (within 5$%$ up to $k=0.7,h,rm{Mpc}^{-1}$). We conclude that an accurate analysis of the Lyman-$alpha$ forest requires considering the complex baryonic thermodynamical large-scale structure relations. Our hierarchical domain specific machine learning method can efficiently exploit this and is ready to generate accurate Lyman-$alpha$ forest mock catalogues covering large volumes required by surveys such as DESI and WEAVE.
Using cosmological particle hydrodynamical simulations and uniform ultraviolet backgrounds, we compare Lyman-$alpha$ forest flux spectra predicted by the conventional cold dark matter (CDM) model, the free-particle wave dark matter (FP$psi$DM) model and extreme-axion wave dark matter (EA$psi$DM) models of different initial axion field angles against the BOSS Lyman-$alpha$ forest absorption spectra with a fixed boson mass $m_bsim 10^{-22}$eV. We recover results reported previously (Irv{s}iv{c} et al. 2017b; Armengaud et al. 2017) that the CDM model agrees better with the BOSS data than the FP$psi$DM model by a large margin, and we find the difference of total $chi^2$s is $120$ for $420$ data bins. These previous results demand a larger boson mass by a factor $>10$ to be consistent with the date and are in tension with the favoured value determined from local satellite galaxies. We however find that such tension is removed as some EA$psi$DM models predict Lyman-$alpha$ flux spectra agreeing better with the BOSS data than the CDM model, and the difference of total $chi^2$s can be as large as $24$ for the same bin number. This finding arises with no surprise since EA$psi$DM models have unique spectral shapes with spectral bumps in excess of the CDM power near the small-scale cutoff typical of $psi$DM linear matter power spectra as well as more extended cutoffs than FP$psi$DM (Zhang & Chiueh 2017a,b).
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