Andreu Font-Ribera

We present a multi-redshift Baryon Acoustic Oscillations (BAO) analysis of the DESI Data Release 2 (DR2) Lyman- α (Ly α ) forest, splitting the forest auto-correlation and its cross-correlation with quasars into three redshift bins. We obtain BAO measurements at effective redshifts z _eff = 2.13, 2.40, and 2.81 with ∼ 2.0–2.5% precision per bin in the radial and transverse directions, corresponding to ∼ 1.1–1.2% precision for the isotropic BAO measurement. Using the same data products and modeling framework as the DESI DR2 Ly α BAO analysis, we validate the pipeline on 400 synthetic datasets and find unbiased BAO recovery with well-calibrated uncertainties. The measurements show an increase in the isotropic dilation parameter D _V / r _d from 30.26 ± 0.39 to 32.22 ± 0.47 and in the Alcock-Paczyński parameter D _M / D _H from 3.96 ± 0.15 to 5.63 ^+0.22 _-0.24 . The Hubble distance D _H / r _d decreases from 9.40 ± 0.20 to 7.22 ± 0.17, providing a direct measurement of the expansion history consistent with ΛCDM and the expected matter-dominated scaling, with H ( z ) ∝ (1 + z ) ⁿ giving n = 1.34 ± 0.16. The redshift split also provides a self-consistent measurement of clustering evolution: the Ly α forest bias evolves as (1 + z ) ^γ with γ _α = 3.05 ± 0.16, the RSD parameter has a redshift evolution described by γ _β = -0.97 ± 0.26, and the quasar bias evolves with γ _Q = 1.56 ± 0.23, consistent with independent quasar clustering measurements. Combining these three-bin BAO measurements with DESI DR2 galaxy and quasar BAO measurements yields cosmological constraints consistent with the single-bin Ly α BAO analysis in flat ΛCDM and w ₀ w _a CDM and improves curvature constraints by ∼ 12% in ΛCDM+Ω _K .

We present and validate a blinding method for the Lyman- α (Ly α ) forest analysis based on a modification of the Alcock-Paczynski test. In order to hide the background expansion history, the method employs a geometrical shift of each quasar (QSO) forest in wavelength space, once the quasar continuum has been fitted and the fluctuation field is extracted. The redshift positions for the QSO sample are also changed in a consistent manner. We show that the method remains effective when applied to real data, where contamination from metals and Lyman- β is intrinsically mixed with the Lyman- α forest. This limitation is primarily visible in the 1D correlation function, where other blinding strategies can mitigate the effect. To assess its effectiveness, the prescription is tested against a series of datasets of increasing complexity: from idealized low-noise mocks, to realistic DESI year one synthetic datasets, and finally to data from DESI first data release (DR1), using both the auto (Ly α ×Ly α ) and cross (Ly α × QSO) correlations. We find that the method robustly shifts the BAO peak position from the 3D correlation functions to the expected value for cosmology changes of around 5% in the matter content, without altering the shape of the posteriors in the model parameters. In conclusion, this catalog-level blinding strategy is a viable method for cosmological inference with the Lyman- α forest, particularly if a cross-analysis with other tracers using the same blinding strategy is pursued.

Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1028 CVs, 221 of which are new including ten of the AMCVn subtype. We have spectroscopically confirmed 440 CV candidates and obtained 85 new or improved orbital periods.We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion.

We present an automatic method based on machine learning convolutional neural network (CNN) architecture to detect Ly α emitters (LAEs) hidden in the Data Release 1 spectroscopic data set of the Dark Energy Spectroscopic Instrument (DESI). Those LAEs mostly have incorrect redshift estimations because the current DESI pipeline is not designed to detect and measure the redshifts of galaxies at z > 2. To uncover those sources, we first visually inspect 4134 DESI spectra and construct a sample, consisting of both LAEs and non-LAEs, for training and testing the CNN-based model to (1) detect LAEs in DESI spectra and (2) determine their Ly α redshifts. The final model yields 95.2% purity and 95.9% completeness for detecting LAEs. We apply this model to approximately 2 × 10 ⁶ spectra of sources targeted as emission-line galaxies and detect 19,685 LAEs from z ∼ 2 to 3.5 within 12 minutes with a single GPU, illustrating the high efficiency of this model for identifying LAEs. The detected LAEs are mostly at the bright end of the luminosity function with Ly α luminosity L _{Ly α} ≳ 10 ⁴³ erg s ⁻¹ . The high signal-to-noise composite spectrum of the detected LAEs further shows various spectral features, including P-Cygni profiles of metal lines and Mg ii emission lines, possible indicators of Lyman continuum escape fraction, revealing the rich astrophysical information in this LAE sample. Finally, this sample can be used to train and validate the pipelines for redshift determination of LAEs for the preparation of the DESI-II survey.

We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy–galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. Our analysis includes four samples drawn from the Bright Galaxy Survey (BGS) and the luminous red galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing data from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to 0.4 h ⁻¹ Mpc for clustering and 2.5 h ⁻¹ Mpc for lensing, leading to stringent constraints on S 8 = σ 8 Ω m / 0.3 and Ω _m when fixing other cosmological parameters to those preferred by the cosmic microwave background. We find S 8 = 0.79 7 − 0.024 + 0.023 and Ω _m = 0.292 ± 0.011 when using lensing measurements from DES and KiDS. Similarly, for HSC, we find S 8 = 0.79 1 − 0.021 + 0.020 and Ω _m = 0.300 ± 0.009 when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of nonlinear scales.

DESI observational data for the GD-1 and C-19 streams are compared to stream simulations in an evolving multihalo potential of a Milky Way–like galaxy based on a cosmological Milky Way–like simulation. The number of subhalos decreases with time, and the subhalo-stream encounter velocities rise as the galaxy and its disk build up their mass. The streams develop from star clusters inserted at ≃1 Gyr after the Big Bang and evolved for 13 Gyr to their current orbital positions. The measured velocity widths of the streams are compared to the matched simulations. Streams in a cold dark matter (CDM) subhalo population provide the best match to the velocity width, on average, with considerable scatter. Streams younger than ≃12 Gyr in CDM subhalos are insufficiently hot. Streams in the same potentials but with populations of warm dark matter (WDM) 5.5 keV subhalos are not, on average, heated to the observed velocity widths, although some of the realizations do reach the observed levels. The stream density power spectrum measured along the length of the DESI GD-1 sample agrees with the CDM stream simulations, with 1.3–2.3 times more power than WDM 7 and 5.5 keV simulations. The simulations show that modeling specific streams from the time of the formation of their progenitor clusters is both feasible and necessary to reproduce their stream-averaged kinematic properties.

Ly α emitters (LAEs) are star-forming galaxies with significant Ly α emission and are often used as tracers of large-scale structure at high redshift. We explore the relationship between the Ly α line profile and environmental density with spectroscopy from the Dark Energy Spectroscopic Instrument (DESI) of LAEs selected with narrowband photometry through the One-hundred-deg ² DECam Imaging in Narrowbands (ODIN) survey. We use LAE surface density maps in the N419 ( z ∼ 2.45) and N501 ( z ∼ 3.12) narrow bands to probe the relationship between local environmental density and the Ly α line profile. In both narrow bands, we stack the LAE spectra in bins of environmental density and inside and outside of protocluster regions. The N501 data show ∼15% higher Ly α line luminosity for galaxies in protoclusters, suggesting increased star formation in these regions. However, the line luminosity is not appreciably greater in protocluster galaxies in the N419 band, suggesting a potential redshift evolution of this effect. The shape of the line profile itself does not vary with environmental density, suggesting that line shape changes are caused by local effects independent of a galaxy’s environment. These data indicate a potential relationship between LAE local environmental density, ionized gas distribution, and Ly α line luminosity.

We present details regarding a composite spectrum of quasar (QSO) absorption line systems. In this composite spectrum, we identify more than 70 absorption lines and observe oxygen and hydrogen emission features at a higher signal-to-noise ratio than any previous study. As the light from a distant quasar travels towards an observer, it may interact with the circumgalactic medium of an intervening galaxy, forming absorption lines. In order to maximize the signal of these absorption lines, we have selected a sample of 239,174 quasar spectra from the second data release of the Dark Energy Spectroscopic Instrument (DESI), each identified to have absorption lines resulting from such an interaction. By stacking these spectra in the rest frame of the absorption and calculating a median composite spectrum, we are able to isolate and enhance these absorption lines. We provide a full atlas of all detected absorption and emission lines as well as their fit centroids and equivalent width values. We additionally provide analysis of composites constructed using subsamples of absorbers in both redshift and Mg ii equivalent width bins. We find that there is minimal redshift evolution across the considered absorber samples. Additionally, we find that dense gas signatures, such as the presence of Na I absorption, are strongest in the highest equivalent width absorber sample, and that the strengths of the Si IV and C IV absorption lines show a relatively weak correlation with Mg II equivalent width. This atlas should aid in future studies investigating the compositions and physical conditions of these absorbers.

We present clustering measurements for high-redshift quasars using data from the Dark Energy Spectroscopic Instrument Data Release 2. Our sample consists of quasars with 2.0 < z < 3.5 in the luminosity range M ₁₄₅₀ ≤ -19.94 mag. We measure the mean quasar bias b _Q ( z ̅ = 2.48) = 3.61 ± 0.01 for the full sample of ∼ 715,000 quasars and quantify the redshift evolution of quasar bias by dividing the sample into four equal redshift bins. There is strong evolution of the quasar bias with redshift that is well fit by the function b _Q ( z ) = a [(1 + z ) ² - 6.565] + b with a = 0.230 ± 0.007 and b = 2.394 ± 0.035, and this fit is also a good match to lower redshift measurements in the literature. This bias evolution is consistent with a characteristic halo mass of M ̅ _h ∼ 10 ¹² M _⊙ that does not vary significantly with redshift. The inferred duty cycles for quasars in our sample are f _duty ∼ 10 ^-2 , staying mostly constant over redshifts. We investigate the luminosity dependence of quasar clustering by dividing each of our four redshift bins into three luminosity bins. The size of our quasar sample permits the first statistically significant measurement of the luminosity dependence of quasar bias at these redshifts. We measure weak dependence of quasar bias on luminosity at fixed redshift, inconsistent with no dependence, but weaker than predicted by a model in which quasar luminosity is tightly correlated with halo mass. These clustering measurements provide a stringent test for models of active black hole light curves and the black hole-halo connection at high redshift.