We derive and numerically implement an algorithm for estimating the 3D power spectrum of the Lyman-α (Lyα) forest flux fluctuations. The algorithm exploits the unique geometry of Lyα forest data to efficiently measure the cross-spectrum between lines of sight as a function of parallel wavenumber, transverse separation and redshift. We start by approximating the global covariance matrix as block-diagonal, where only pixels from the same spectrum are correlated. We then compute the eigenvectors of the derivative of the signal covariance with respect to cross-spectrum parameters, and project the inverse-covariance-weighted spectra onto them. This acts much like a radial Fourier transform over redshift windows. The resulting cross-spectrum inference is then converted into our final product, an approximation of the likelihood for the 3D power spectrum expressed as second order Taylor expansion around a fiducial model. We demonstrate the accuracy and scalability of the algorithm and comment on possible extensions. Our algorithm will allow efficient analysis of the upcoming Dark Energy Spectroscopic Instrument dataset.

We present a new determination of the large-scale clustering of the CIV forest (i.e., the absorption due to all CIV absorbers) using its cross-correlation with quasars in the Sloan Digital Sky Survey (SDSS) Data Release 12 (DR12). We fit a linear bias model to the measured cross-correlation. We find that the transmission bias of the CIV forest, $b_{Fc}$, at a mean redshift of $z=2.3$, obeys the relation $(1+\beta_c)b_{F c} = -0.024 \pm 0.003$. Here, $\beta_{c}$ is the linear redshift space distortion parameter of the CIV absorption, which can only be poorly determined at $\beta_c=1.1\pm 0.6$ from our data. This transmission bias is related to the bias of CIV absorbers and their host halos through the effective mean optical depth of the CIV forest, $\bar\tau_c$. Estimating a value $\bar \tau_c(z) \simeq 0.01$ from previous studies of the CIV equivalent width distribution, our measurement implies a CIV absorber bias near unity, with a large error due to uncertainties in both $\beta_c$ and $\bar\tau_c$. This makes it compatible with the higher DLA bias $b_{\rm DLA}\simeq 2$ measured previously from the cross-correlation of DLAs and the Lyman-$\alpha$ forest. We discuss the implications of the CIV absorber bias for the mass distribution of their host halos. More accurate determinations of $\bar \tau_c(z)$ and $\beta_c$ are necessary to obtain a more robust measurement of this CIV absorber bias.

We present a new method of finding cosmic voids using tomographic maps of Lyα forest flux. We identify cosmological voids with radii of 2-12 h-1 Mpc in a large N-body simulation at z=2.5, and characterize the signal of the high-redshift voids in density and Lyα forest flux. The void properties are similar to what has been found at lower redshifts, but they are smaller and have steeper radial density profiles. Similarly towhat has been found for low-redshift voids, the radial velocity profiles have little scatter and agree very well with the linear theory prediction. We run the same void finder on an ideal Lyα flux field and tomographic reconstructions at various spatial samplings. We compare the tomographic map void catalogues to the density void catalogue and find good agreement even with modest-sized voids (r > 6 h-1 Mpc). Using our simple void-finding method, the configuration of the ongoing COSMOS Lyman Alpha Mapping And Tomography Observations (CLAMATO) survey covering 1 deg2 would provide a sample of about 100 high-redshift voids. We also provide void-finding forecasts for larger area surveys, and discuss how these void samples can be used to test modified gravity models, study high-redshift void galaxies, and to make an Alcock-Paczynski measurement. To aid future work in this area, we provide public access to our simulation products, catalogues, and sample tomographic flux maps.

Interpreting observations of the Lyman-α forest flux power spectrum requires interpolation between a small number of expensive simulations. We present a Gaussian process emulator modelling the 1D flux power spectrum as a function of the amplitude and slope of the small-scale linear matter power spectrum, and the state of the intergalactic medium at the epoch of interest (2 < z < 4). This parameterisation enables the prediction of the flux power spectrum in extended cosmological models that are not explicitly included in the training set, eliminating the need to construct bespoke emulators for a number of extensions to ΛCDM. Our emulator is appropriate for cosmologies in which the linear matter power spectrum is described to percent level accuracy by just an amplitude and slope across the epoch of interest, and in the regime probed by eBOSS/DESI data. We demonstrate this for massive neutrino cosmologies, where the emulator is able to predict the flux power spectrum in a Σ mν=0.3 eV neutrino cosmology to sub-percent accuracy, without including massive neutrinos in the training simulations. Further parameters would be required to describe models with sharp features in the linear power, such as warm or light axion dark matter. This work will facilitate the combination of upcoming DESI data with observations of the cosmic microwave background, to obtain constraints on neutrino mass and other extensions to ΛCDM cosmology.

Using a suite of hydrodynamical simulations with cold dark matter, baryons, and neutrinos, we present a detailed study of the effect of massive neutrinos on the 1-D and 3-D flux power spectra of the Lyman-α (Lyα) forest. The presence of massive neutrinos in cosmology induces a scale- and time-dependent suppression of structure formation that is strongest on small scales. Measuring this suppression is a key method for inferring neutrino masses from cosmological data, and is one of the main goals of ongoing and future surveys like eBOSS, DES, LSST, Euclid or DESI . The clustering in the Lyα forest traces the quasi-linear power at late times and on small scales. In combination with observations of the cosmic microwave background, the forest therefore provides some of the tightest constraints on the sum of the neutrino masses. However there is a well-known degeneracy between Σmν and the amplitude of perturbations in the linear matter power spectrum. We study the corresponding degeneracy in the 1-D flux power spectrum of the Lyα forest, and for the first time also study this degeneracy in the 3-D flux power spectrum. We show that the non-linear effects of massive neutrinos on the Lyα forest, beyond the effect of linear power amplitude suppression, are negligible, and this degeneracy persists in the Lyα forest observables to a high precision. We discuss the implications of this degeneracy for choosing parametrisations of the Lyα forest for cosmological analysis.

We measure the two-point clustering of spectroscopically confirmed quasars from the final sample of the Baryon Oscillation Spectroscopic Survey (BOSS) on comoving scales of 4 ≲ s ≲ 22 h-1 Mpc. The sample covers 6950 deg2 [~19 (h-1Gpc)3] and, over the redshift range 2.2 ≲ z ≲ 2.8, contains 55 826 homogeneously selected quasars, which is twice as many as in any similar work. We deduce bQ = 3.54 ± 0.10; the most precise measurement of quasar bias to date at these redshifts. This corresponds to a host halo mass of ~2 × 1012 h-1M⊙ with an implied quasar duty cycle of ~1 per cent. The real-space projected correlation function is well fitted by a power law of index 2 and correlation length r0 = (8.12 ± 0.22) h-1 Mpc over scales of 4 ≲ rp ≲ 25 h-1 Mpc. To better study the evolution of quasar clustering at moderate redshift, we extend the redshift range of our study to z ~ 3.4 and measure the bias and correlation length of three subsamples over 2.2 ≲ z ≲ 3.4. We find no significant evolution of r0 or bias over this range, implying that the host halo mass of quasars decreases somewhat with increasing redshift. We find quasar clustering remains similar over a decade in luminosity, contradicting a scenario in which quasar luminosity is monotonically related to halo mass at z ≈ 2.5. Our results are broadly consistent with previous BOSS measurements, but they yield more precise constraints based upon a larger and more uniform data set.

We measure the 1D Ly α power spectrum P1D from Keck Observatory Database of Ionized Absorption toward Quasars (KODIAQ), The Spectral Quasar Absorption Database (SQUAD), and XQ-100 quasars using the optimal quadratic estimator. We combine KODIAQ and SQUAD at the spectrum level, but perfo a separate XQ-100 estimation to control its large resolution corrections in check. Our final analysis measures P1D at scales k < 0.1 s km-1 between redshifts $z$ = 2.0-4.6 using 538 quasars. This sample provides the largest number of high-resolution, high-S/N observations; and combined with the power of optimal estimator it provides exceptional precision at small scales. These small-scale modes (k 0.02 s km-1), unavailable in Sloan Digital Sky Survey and Dark Energy Spectroscopic Instrument analyses, are sensitive to the theal state and reionization history of the intergalactic medium, as well as the nature of dark matter. As an example, a simple Fisher forecast analysis estimates that our results can improve small-scale cut-off sensitivity by more than a factor of 2.

We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Lyα systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H i column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel-1. Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N > 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms.

We measure the large-scale cross-correlation of quasars with the Lyα 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 h-1Mpc. For r > 15 h-1Mpc, 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 ΛCDM model, with the redshift distortions indicative of gravitational evolution detected at high confidence. Using previous determinations of the Lyα forest bias factor obtained from the Lyα autocorrelation, we infer the quasar bias factor to be bq = 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 Lyα forest redshift distortion factor, βF = 1.1±0.15, slightly larger than but consistent with the previous measurement from the Lyα forest autocorrelation. The simple linear model we use fails at separations r < 15h-1Mpc, 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.© 2013 IOP Publishing Ltd and Sissa Medialab srl.

Using moderate-resolution optical spectra from 58 background Lyman-break galaxies and quasars at z ∼ 2.3-3 within a 11′.5 × 13′.5 area of the COSMOS field (∼1200 deg-2 projected area density or ∼2.4 h-1 Mpc mean transverse separation), we reconstruct a 3D tomographic map of the foreground Lyα forest absorption at 2.2 < z < 2.5 with an effective smoothing scale of ∈3D ≈ 2.5 h-1 Mpc comoving. Comparing with 61 coeval galaxies with spectroscopic redshifts in the same volume, we find that the galaxy positions are clearly biased toward regions with enhanced intergalactic medium (IGM) absorption in the tomographic map. We find an extended IGM overdensity with deep absorption troughs at z = 2.45 associated with a recently discovered galaxy protocluster at the same redshift. Based on simulations matched to our data, we estimate the enclosed dark matter mass within this IGM overdensity to be Mdm (z= 2.45) = (1.1 ± 0.6) ×1014 h-1 M⊙, and argue based on this mass and absorption strength that it will form at least one z ∼ 0 galaxy cluster with M(z = 0) = (3 ± 1.5) ×1014 h-1 M⊙, although its elongated nature suggests that it will likely collapse into two separate clusters. We also point out a compact overdensity of six MOSDEF galaxies at z = 2.30 within a r ∼ 1 h-1 Mpc radius and Δz ∼ 0.006, which does not appear to have a large associated IGM overdensity. These results demonstrate the potential of Lyα forest tomography on larger volumes to study galaxy properties as a function of environment, as well as revealing the large-scale IGM overdensities associated with protoclusters or other features of large-scale structure.