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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.
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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.
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.
We present the first observations of foreground Lyman-$alpha$ forest absorption from high-redshift galaxies, targeting 24 star-forming galaxies (SFGs) with $zsim 2.3-2.8$ within a $5 times 15$ region of the COSMOS field. The transverse sightline separation is $sim 2,h^{-1}mathrm{Mpc}$ comoving, allowing us to create a tomographic reconstruction of the 3D Ly$alpha$ forest absorption field over the redshift range $2.20leq zleq 2.45$. The resulting map covers $6,h^{-1}mathrm{Mpc} times 14,h^{-1}mathrm{Mpc}$ in the transverse plane and $230,h^{-1}mathrm{Mpc}$ along the line-of-sight with a spatial resolution of $approx 3.5,h^{-1}mathrm{Mpc}$, and is the first high-fidelity map of large-scale structure on $simmathrm{Mpc}$ scales at $z>2$. Our map reveals significant structures with $gtrsim 10,h^{-1}mathrm{Mpc}$ extent, including several spanning the entire transverse breadth, providing qualitative evidence for the filamentary structures predicted to exist in the high-redshift cosmic web. Simulated reconstructions with the same sightline sampling, spectral resolution, and signal-to-noise ratio recover the salient structures present in the underlying 3D absorption fields. Using data from other surveys, we identified 18 galaxies with known redshifts coeval with our map volume enabling a direct comparison to our tomographic map. This shows that galaxies preferentially occupy high-density regions, in qualitative agreement with the same comparison applied to simulations. Our results establishes the feasibility of the CLAMATO survey, which aims to obtain Ly$alpha$ forest spectra for $sim 1000$ SFGs over $sim 1 ,mathrm{deg}^2$ of the COSMOS field, in order to map out IGM large-scale structure at $langle z rangle sim 2.3$ over a large volume $(100,h^{-1}mathrm{Mpc})^3$.
We use the Ly-$alpha$ Mass Association Scheme (LyMAS; Peirani et al. 2014) to predict cross-correlations at $z=2.5$ between dark matter halos and transmitted flux in the Ly-$alpha$ forest, and compare to cross-correlations measured for quasars and damped Ly-$alpha$ systems (DLAs) from the Baryon Oscillation Spectroscopic Survey (BOSS) by Font-Ribera et al. (2012, 2013). We calibrate LyMAS using Horizon-AGN hydrodynamical cosmological simulations of a $(100 h^{-1} mathrm{Mpc})^3$ comoving volume. We apply this calibration to a $(1 h^{-1} mathrm{Gpc})^3$ simulation realized with $2048^3$ dark matter particles. In the 100 $h^{-1}$ Mpc box, LyMAS reproduces the halo-flux correlations computed from the full hydrodynamic gas distribution very well. In the 1 $h^{-1}$ Gpc box, the amplitude of the large scale cross-correlation tracks the halo bias $b_h$ as expected. We provide empirical fitting functions that describe our numerical results. In the transverse separation bins used for the BOSS analyses, LyMAS cross-correlation predictions follow linear theory accurately down to small scales. Fitting the BOSS measurements requires inclusion of random velocity errors; we find best-fit RMS velocity errors of 399 km s$^{-1}$ and 252 km s$^{-1}$ for quasars and DLAs, respectively. We infer bias-weighted mean halo masses of $M_h/10^{12} h^{-1}M_odot=2.19^{+0.16}_{-0.15}$ and $0.69^{+0.16}_{-0.14}$ for the host halos of quasars and DLAs, with $sim 0.2$ dex systematic uncertainty associated with redshift evolution, IGM parameters, and selection of data fitting range.
(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.
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