arXiv subjects

C. Ramírez-Pérez

Publications and source records attributed to C. Ramírez-Pérez.

11 recordsLinked to original sources

arXiv2025

Constraints on Neutrino Physics from DESI DR2 BAO and DR1 Full Shape

The Dark Energy Spectroscopic Instrument (DESI) Collaboration has obtained robust measurements of baryon acoustic oscillations (BAO) in the redshift range, $0.1 < z < 4.2$, based on the Lyman-$α$ forest and galaxies from Data Release 2 (DR2). We combine these measurements with external cosmic microwave background (CMB) data from Planck and ACT to place our tightest constraints yet on the sum of neutrino masses. Assuming the cosmological $Λ$CDM model and three degenerate neutrino states, we find $\sum m_ν<0.0642$ eV (95%) with a marginalized error of $σ(\sum m_ν)=0.020$ eV. We also constrain the effective number of neutrino species, finding $N_\rm{eff} = 3.23^{+0.35}_{-0.34}$ (95%), in line with the Standard Model prediction. When accounting for neutrino oscillation constraints, we find a preference for the normal mass ordering and an upper limit on the lightest neutrino mass of $m_l < 0.023$ eV (95%). However, we determine using frequentist and Bayesian methods that our constraints are in tension with the lower limits derived from neutrino oscillations. Correcting for the physical boundary at zero mass, we report a 95% Feldman-Cousins upper limit of $\sum m_ν<0.053$ eV, breaching the lower limit from neutrino oscillations. Considering a more general Bayesian analysis with an effective cosmological neutrino mass parameter, $\sum m_{ν,\rm{eff}}$, that allows for negative energy densities and removes unsatisfactory prior weight effects, we derive constraints that are in $3σ$ tension with the same oscillation limit. In the absence of unknown systematics, this finding could be interpreted as a hint of new physics not necessarily related to neutrinos. The preference of DESI and CMB data for an evolving dark energy model offers one possible solution. In the $w_0w_a$CDM model, we find $\sum m_ν<0.163$ eV (95%), relaxing the neutrino tension. [Abridged]

astro-ph.CO↗

arXiv2025

Construction of the Damped Ly$α$ Absorber Catalog for DESI DR2 Ly$α$ BAO

We present the Damped Ly$α$ Toolkit for automated detection and characterization of Damped Ly$α$ absorbers (DLA) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and \texttt{HI} column density. With an optimized quality cut on detection significance ($Δχ_{r}^2>0.03$), the technique achieves an estimated 80\% purity and 79\% completeness when evaluated on simulated spectra with S/N~$>2$ that are free of broad absorption lines (BAL). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21,719 were found in S/N~$>2$ spectra with predicted $\log_{10} (N_\texttt{HI}) > 20.3$ and detection significance $Δχ_{r}^2 >0.03$. We compare the Damped Ly$α$ Toolkit to two alternative DLA finders based on a convolutional neural network (CNN) and Gaussian process (GP) models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the Ly$α$ forest baryon acoustic oscillation measurement. The combined catalog contains 41,152 candidate DLAs with $\log_{10} (N_\texttt{HI}) > 20.3$ from quasar spectra with S/N~$>2$. We estimate this sample to be approximately 85\% pure and 79\% complete when BAL quasars are excluded.

astro-ph.CO↗

arXiv2025

Validation of the DESI DR2 Measurements of Baryon Acoustic Oscillations from Galaxies and Quasars

The Dark Energy Spectroscopic Instrument (DESI) data release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from DR1, providing improved statistical precision in BAO constraints across multiple tracers, including bright galaxies (BGS), luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars (QSOs). In this paper, we validate the BAO analysis of DR2. We present the results of robustness tests on the blinded DR2 data and, after unblinding, consistency checks on the unblinded DR2 data. All results are compared to those obtained from a suite of mock catalogs that replicate the selection and clustering properties of the DR2 sample. We confirm the consistency of DR2 BAO measurements with DR1 while achieving a reduction in statistical uncertainties due to the increased survey volume and completeness. We assess the impact of analysis choices, including different data vectors (correlation function vs. power spectrum), modeling approaches and systematics treatments, and an assumption of the Gaussian likelihood, finding that our BAO constraints are stable across these variations and assumptions with a few minor refinements to the baseline setup of the DR1 BAO analysis. We summarize a series of pre-unblinding tests that confirmed the readiness of our analysis pipeline, the final systematic errors, and the DR2 BAO analysis baseline. The successful completion of these tests led to the unblinding of the DR2 BAO measurements, ultimately leading to the DESI DR2 cosmological analysis, with their implications for the expansion history of the Universe and the nature of dark energy presented in the DESI key paper.

astro-ph.CO↗

arXiv2025

Validation of the DESI DR2 Ly$α$ BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-$α$ (Ly$α$) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the Baryonic Acoustic Oscillation (BAO) analysis using Ly$α$ forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Ly$α$ mocks that use a quasi-linear input power spectrum to incorporate the non-linear broadening of the BAO peak. We have also increased the number of realisations used in the validation to 400, compared to the 150 realisations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask Damped Lyman-$α$ Absorbers (DLAs) in our spectra. The BAO measurement from the Ly$α$ dataset of DESI DR2 is presented in a companion publication.

astro-ph.IM↗

arXiv2025

Synthetic spectra for Lyman-$α$ forest analysis in the Dark Energy Spectroscopic Instrument

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-$α$ quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use full survey synthetic data to forecast the BAO scale constraining power with DESI.

astro-ph.CO↗

arXiv2024

Characterization of contaminants in the Lyman-alpha forest auto-correlation with DESI

Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-alpha forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants to the lyman-alpha forest which are mainly caused by correlated signals introduced by the spectroscopic data processing pipeline as well as astrophysical contaminants due to foreground absorption in the intergalactic medium. Notably, an excess signal caused by the sky background subtraction noise is present in the lyman-alpha auto-correlation in the first line-of-sight separation bin. We use synthetic data to isolate this contribution, we also characterize the effect of spectro-photometric calibration noise, and propose a simple model to account for both effects in the analysis of the lyman-alpha forest. We then measure the auto-correlation of the quasar flux transmission fraction of low redshift quasars, where there is no lyman-alpha forest absorption but only its contaminants. We demonstrate that we can interpret the data with a two-component model: data processing noise and triply ionized Silicon and Carbon auto-correlations. This result can be used to improve the modeling of the lyman-alpha auto-correlation function measured with DESI.

astro-ph.CO↗

arXiv2024

Broad Absorption Line Quasars in the Dark Energy Spectroscopic Instrument Early Data Release

Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed 0.1c. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman-alpha forest. We present a catalog of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are 243 km/s smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study.

astro-ph.CO↗

arXiv2024

Validation of the DESI 2024 Ly$α$ forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$α$ (Ly$α$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$α$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$α$ forest. The synthetic data sets span a redshift range $1.8<z<3.8$, and are analysed using the same framework and pipeline used for the DESI 2024 Ly$α$ forest BAO measurement. To measure BAO, we use both the Ly$α$ auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Ly$α$ forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Ly$α$ forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

astro-ph.CO↗

arXiv2024

Impact of Systematic Redshift Errors on the Cross-correlation of the Lyman-$α$ Forest with Quasars at Small Scales Using DESI Early Data

The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-$α$ forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-$α$ forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-$α$ optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at $z > 1.6$ and we found the redshift dependent bias, $Δr_\parallel$, increased from $-1.94 \pm 0.15$ $h^{-1}$ Mpc to $-0.08 \pm 0.04$ $h^{-1}$ Mpc ($-205 \pm 15~\text{km s}^{-1}$ to $-9.0 \pm 4.0~\text{km s}^{-1}$). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.

astro-ph.CO↗

arXiv2024

Optimal 1D Ly$α$ Forest Power Spectrum Estimation -- III. DESI early data

The one-dimensional power spectrum $P_{\mathrm{1D}}$ of the Ly$α$ forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of $P_{\mathrm{1D}}$ with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of $54~600$ quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with two-dimensional image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly$α$ emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and implications for the upcoming DESI Year 1 analysis.

astro-ph.CO↗

arXiv2023

3D Correlations in the Lyman-$α$ Forest from Early DESI Data

We present the first measurements of Lyman-$α$ (Ly$α$) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Ly$α$ absorption using 88,509 quasars at $z>2$, and its cross-correlation with quasars using a further 147,899 tracer quasars at $z\gtrsim1.77$. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of $3.8σ$, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. We validate the existing analysis methods of Ly$α$ correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

astro-ph.CO↗