arXiv subjects

Ignasi Pérez-Ràfols

Publications and source records attributed to Ignasi Pérez-Ràfols.

At least 73 records · Page 4Linked to original sources

arXiv2023

The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman-$α$ forest samples with Fast Fourier Transform

We present the one-dimensional Lyman-$α$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$, contained in the DESI Early Data Release and the first two months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated to the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on log-normal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Lyman-$α$ forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.

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arXiv2023

The miniJPAS survey quasar selection IV: Classification and redshift estimation with SQUEzE

We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning classification of photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a `black box' when compared with other classifiers. Another key advantage is that using user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, here we adapt it for multi-band photometric data, i.e. we treat multiple narrow-band filters as very low-resolution spectra. We train our models using specialized mocks from Queiroz et al. (2022). We estimate our redshift precision using the normalized median absolute deviation, $σ_{\rm NMAD}$ applied to our test sample. Our test sample returns an $f_1$ score (effectively the purity and completeness) of 0.49 for quasars down to magnitude $r=24.3$ with $z\geq2.1$ and 0.24 for quasars with $z<2.1$. For high-z quasars, this goes up to 0.9 for $r<21.0$. We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a $σ_{NMAD}=0.92\%$ for the entire sample, reduced to 0.81\% for $r<22.5$ and 0.74\% for $r<21.3$. Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings.

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arXiv2023

The cross-correlation of galaxies in absorption with the Lyman $α$ forest

We present the first clustering measurement of Strong Blended Lyman $α$ (SBLA) absorption systems by measuring their cross-correlation with the Lyman $α$ forest. SBLAs are a new population of absorbers detected within the Lyman $α$ forest. We find a bias of $2.329\pm0.057$, consistent with that of Damped Lyman $α$ absorbers (DLAs). For DLAs, we recover a bias of $2.331\pm0.057$ larger than previously reported (Pérez-Ràfols et al. 2018b). We also find a redshift space distortion parameter $β=0.417\pm0.010$, also consistent with the recovered value for DLAs ($β=0.416\pm0.010$). This is consistent with SBLA and DLA systems tracing different portions of the circumgalactic medium of a broadly common population of galaxies. Given these common clustering properties, we combined them to perform a cross-correlation of galaxies in absorption with the Ly$α$ forest. We find that the BAO scale uncertainty of this new measurement is $1.75\times$ that of Ly$α$ auto-correlation and $1.6\times$ that of the quasar cross-correlation with the Ly$α$ forest. We note that the current preferred metal contamination model for fitting the correlation functions with respect to the Ly$α$ forest is not realistic enough for SBLA systems, likely due to their status as high redshift precision sites of high metal enrichment. Mock spectra including SBLA systems and their associated metal absorption are required to understand this sample fully. We conclude that SBLAs have the potential to complement the standard Ly$α$ cosmological analyses in future surveys.

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arXiv2023

The miniJPAS survey quasar selection III: Classification with artificial neural networks and hybridisation

This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over $\sim$ 1 deg$^2$ in the AEGIS field. We developed two algorithms based on artificial neural networks (ANN) to classify objects into four categories: stars, galaxies, quasars at low redshift ($z < 2.1)$, and quasars at high redshift ($z \geq 2.1$). As inputs, we used miniJPAS fluxes for one of the classifiers (ANN$_1$) and colours for the other (ANN$_2$). The ANNs were trained and tested using mock data in the first place. We studied the effect of augmenting the training set by creating hybrid objects, which combines fluxes from stars, galaxies, and quasars. Nevertheless, the augmentation processing did not improve the score of the ANN. We also evaluated the performance of the classifiers in a small subset of the SDSS DR12Q superset observed by miniJPAS. In the mock test set, the f1-score for quasars at high redshift with the ANN$_1$ (ANN$_2$) are $0.99$ ($0.99$), $0.93$ ($0.92$), and $0.63$ ($0.57$) for $17 < r \leq 20$, $20 < r \leq 22.5$, and $22.5 < r \leq 23.6$, respectively, where $r$ is the J-PAS rSDSS band. In the case of low-redshift quasars, galaxies, and stars, we reached $0.97$ ($0.97$), $0.82$ ($0.79$), and $0.61$ ($0.58$); $0.94$ ($0.94$), $0.90$ ($0.89$), and $0.81$ ($0.80$); and $1.0$ ($1.0$), $0.96$ ($0.94$), and $0.70$ ($0.52$) in the same r bins. In the SDSS DR12Q superset miniJPAS sample, the weighted f1-score reaches 0.87 (0.88) for objects that are mostly within $20 < r \leq 22.5$. Finally, we estimate the number of point-like sources that are quasars, galaxies, and stars in miniJPAS.

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arXiv2023

The miniJPAS survey quasar selection II: Machine learning classification with photometric measurements and uncertainties

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a Machine Learning-based method that employs Convolutional Neural Networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the J-PAS collaboration covering $\sim$ 1 deg$^2$ of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established Machine Learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars and unresolved galaxies. Our results are a proof-of-concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence.

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arXiv2022

The impact and mitigation of broad absorption line quasars in Lyman$-α$ forest correlations

Correlations in and with the flux transmission of the Lyman$-α$ (Ly$α$) forest in the spectra of high-redshift quasars are powerful cosmological tools, yet these measurements can be compromised if the intrinsic quasar continuum is significantly uncertain. One particularly problematic case is broad absorption line (BAL) quasars, which exhibit blueshifted absorption associated with many spectral features that are consistent with outflows of up to $\sim0.1c$. As these absorption features can both fall in the forest region and be difficult to distinguish from Ly$α$ absorption, cosmological analyses eliminate the 12 - 16% of quasars that exhibit BALs. In this paper we explore an alternate approach that includes BALs in the Ly$α$ auto correlation function, with the exception of the expected locations of the BAL absorption troughs. This procedure returns over 95% of the pathlength that is lost by the exclusion of BALs, as well as increases the density of sightlines. We show that including BAL quasars reduces the fractional uncertainty in the covariance matrix and correlation function and does not significantly change the shape of the correlation function relative to analyses that exclude BAL quasars. We also evaluate different definitions of BALs, masking strategies, and potential differences in the quasar continuum in the forest region for BALs with different amounts of absorption.

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arXiv2022

The effect of quasar redshift errors on Lyman-$α$ forest correlation functions

Using synthetic Lyman-$α$ forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-$α$ correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred $\text{km s}^{-1}\,$ due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-$α$-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.

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arXiv2022

The miniJPAS survey quasar selection I: Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range $17.5\leq r<24$, we augment our sample of available spectra by shifting the original $r$-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

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arXiv2022

Forecasts for WEAVE-QSO: 3D clustering and connectivity of critical points with Lyman-$α$ tomography

The upcoming WEAVE-QSO survey will target a high density of quasars over a large area, enabling the reconstruction of the 3D density field through Lyman-$α$ tomography over unprecedented volumes smoothed on intermediate scales ($\approx$ 16 Mpc/$h$). We produce mocks of the Lyman-$α$ forest using LyMAS, and reconstruct the 3D density field between sightlines through Wiener filtering in a configuration compatible with the future WEAVE-QSO observations. The fidelity of the reconstruction is assessed by measuring one- and two-point statistics from the distribution of critical points in the cosmic web. In addition, initial Lagrangian statistics are predicted from first principles, and measurements of the connectivity of the cosmic web are performed. The reconstruction captures well the expected features in the auto- and cross-correlations of the critical points. This remains true after a realistic noise is added to the synthetic spectra, even though sparsity of sightlines introduces systematics, especially in the cross-correlations of points with mixed signature. Specifically, for walls and filaments, the most striking clustering features could be measured with up to 4 sigma of significance with a WEAVE-QSO-like survey. Moreover, the connectivity of each peak identified in the reconstructed field is globally consistent with its counterpart in the original field, indicating that the reconstruction preserves the geometry of the density field not only statistically, but also locally. Hence the critical points relative positions within the tomographic reconstruction could be used as standard rulers for dark energy by WEAVE-QSO and similar surveys.

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arXiv2020

Probing Large-scale UV Background Inhomogeneity Associated with Quasars using Metal Absorption

We study large-scale UV background inhomogeneity in three-dimensions associated with the observed quasar populations at high redshift. We do this by measuring metal absorption through quasar absorption spectrum stacking as a function distance to closest quasar in SDSS-IV/eBOSS on 10s of comoving megaparsec scales. We study both intergalactic medium absorbers and mixed circumgalactic medium absorbers and probe absorption in O VI, C IV, and Si IV, and Si III. Overall stronger high ionization species absorption is seen closer to quasars at $2.4<z<3.1$. O VI absorption shows a particularly strong change, with effects in C IV evident in some cases, and more marginal effects in Si III and Si IV. We further study $2.05<z<2.4$ (with weak signs of increasing homogeneity with time) and explore the study of metal absorption as a function of integrated SDSS-r band flux quasar flux (yielding consistent but less significant results). While the metal absorption does show sensitivity to large-scale 3D quasar proximity, the current incomplete quasar samples limit detailed interpretation. This work does, however, demonstrate that UV background inhomogeneities exist on scales of several 10s of comoving megaparsecs associated with quasars and that they can be measured with precision by examining metal absorption in the intergalactic medium.

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arXiv2020

LyaCoLoRe: Synthetic Datasets for Current and Future Lyman-$α$ Forest BAO Surveys

The statistical power of Lyman-$α$ forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, we present LyaCoLoRe: a package for producing synthetic Lyman-$α$ forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers - high column density systems and metal absorbers - which act as potential complications for BAO analyses.

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arXiv2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Baryon acoustic oscillations with Lyman-$α$ forests

We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$α$ (Ly$α$) absorption and quasars at an effective redshift $z=2.33$ using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS). The sixteenth and final eBOSS data release (SDSS DR16) contains all data from eBOSS and its predecessor, the Baryonic Oscillation Spectroscopic Survey (BOSS), providing $210,005$ quasars with $z_{q}>2.10$ that are used to measure Ly$α$ absorption. We measure the BAO scale both in the auto-correlation of Ly$α$ absorption and in its cross correlation with $341,468$ quasars with redshift $z_{q}>1.77$. Apart from the statistical gain from new quasars and deeper observations, the main improvements over previous work come from more accurate modeling of physical and instrumental correlations and the use of new sets of mock data. Combining the BAO measurement from the auto- and cross-correlation yields the constraints of the two ratios $D_{H}(z=2.33)/r_{d} = 8.99 \pm 0.19$ and $D_{M}(z=2.33)/r_{d} = 37.5 \pm 1.1$, where the error bars are statistical. These results are within $1.5σ$ of the prediction of the flat-$Λ$CDM cosmology of Planck~(2016). The analysis code, \texttt{picca}, the catalog of the flux-transmission field measurements, and the $Δχ^{2}$ surfaces are publicly available.

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arXiv2020

Spectroscopic QUasar Extractor and redshift (z) EstimatorSQUEzE II: Universality of the results

In this paper we study the universality of the results of SQUEzE, a software package to classify quasar spectra and estimate their redshifts. The code is presented in \cite{Perez-Rafols+2019}. We test the results against changes on signal-to-noise, spectral resolution, wavelength coverage, and quasar brightness. We find that SQUEzE levels of performance (quantified with purity and completeness) are stable to spectra that have a noise dispersion 4 times that of our standard test sample, BOSS. We also find that the performance remains unchanged if pixels of width 25Åare considered, and decreases by $\sim2\%$ for pixels of width 100Å. We see no effect when analyzing subsets of different quasar brightness, and we establish that the blue part (up to 7000Å) of the spectra is sufficient for the classification. Finally, we compare our suite of tests with samples of spectra expected from WEAVE-QSO and DESI, and narrow-band imaging from J-PAS. We conclude that SQUEzE will perform similarly when confronted with the demands of these future surveys as when applied to current BOSS (and eBOSS) data. {\it Keywords: cosmology: observations - quasar: emission lines - quasar: absorption lines}

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arXiv2019

Spectroscopic QUasar Extractor and redshift (z) EstimatorSQUEzE I: Methodology

We present SQUEzE, a software package to classify quasar spectra and estimate their redshifts. SQUEzE is a random forest classifier operating on the parameters of candidate emission peaks identified in the spectra. We test the performance of the algorithm using visually inspected data from BOSS as a truth table. Only 4\% of the sample ($\sim$6,800 quasars and $\sim$11,520 contaminants) is needed for converged training in recommended choices of the confidence threshold ($0.2<p_{\rm min}<0.7$). For an operational mode which balances purity and completeness ($p_{\rm min}=0.28$) we recover a purity of $96.81\pm0.39\%$ ($99.30\pm0.14\%$ for quasars with $z \geq 2.1$) and a completeness of $96.83\pm0.30\%$ ($98.42\pm0.15\%$ for quasars with $z \geq 2.1$). SQUEzE can be used to obtain a $\approx$100\% pure sample of $z \geq 2.1$. quasars (with $\approx$96\% completeness) by using a confidence threshold of $p_{\rm min}=0.7$. The estimated redshift error is $1,500{\rm \thinspace km/s}$ and we recommend that SQUEzE be used in conjunction with an additional step of redshift tuning to achieve maximum precision. We find that SQUEzE achieves the necessary performance to replace visual inspection in BOSS-like spectroscopic surveys of quasars with subsequent publications in this series exploring expectations for future surveys and alternative methods. Keywords: cosmology: observations - quasar: emission lines - quasar: absorption lines

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arXiv2019

Baryon acoustic oscillations at z = 2.34 from the correlations of Ly$α$ absorption in eBOSS DR14

We measure the imprint of primordial baryon acoustic oscillations (BAO) in the correlation function of Ly$α$ absorption in quasar spectra from the Baryon Oscillation Spectroscopic Survey (BOSS) and the extended BOSS (eBOSS) in Data Release 14 (DR14) of the Sloan Digital Sky Survey (SDSS)-IV. In addition to 179,965 spectra with absorption in the Lyman-$α$ (Ly$α$) region, we use, for the first time, Ly$α$ absorption in the Lyman-$β$ region of 56,154 spectra. We measure the Hubble distance, $D_H$, and the comoving angular diameter distance, $D_M$, relative to the sound horizon at the drag epoch $r_d$ at an effective redshift $z=2.34$. Using a physical model of the correlation function outside the BAO peak, we find $D_H(2.34)/r_d=8.86\pm 0.29$ and $D_M(2.34)/r_d=37.41\pm 1.86$, within 1$σ$ from the flat-$Λ$CDM model consistent with CMB anisotropy measurements. With the addition of polynomial "broadband" terms, the results remain within one standard deviation of the CMB-inspired model. Combined with the quasar-Ly$α$ cross-correlation measurement presented in a companion paper Blomqvist19, the BAO measurements at $z=2.35$ are within 1.7$σ$ of the predictions of this model.

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arXiv2019

Baryon acoustic oscillations from the cross-correlation of Ly$α$ absorption and quasars in eBOSS DR14

We present a measurement of the baryon acoustic oscillation (BAO) scale at redshift $z=2.35$ from the three-dimensional correlation of Lyman-$α$ (Ly$α$) forest absorption and quasars. The study uses 266,590 quasars in the redshift range $1.77<z<3.5$ from the Sloan Digital Sky Survey (SDSS) Data Release 14 (DR14). The sample includes the first two years of observations by the SDSS-IV extended Baryon Oscillation Spectroscopic Survey (eBOSS), providing new quasars and re-observations of BOSS quasars for improved statistical precision. Statistics are further improved by including Ly$α$ absorption occurring in the Ly$β$ wavelength band of the spectra. From the measured BAO peak position along and across the line of sight, we determined the Hubble distance $D_{H}$ and the comoving angular diameter distance $D_{M}$ relative to the sound horizon at the drag epoch $r_{d}$: $D_{H}(z=2.35)/r_{d}=9.20\pm 0.36$ and $D_{M}(z=2.35)/r_{d}=36.3\pm 1.8$. These results are consistent at $1.5σ$ with the prediction of the best-fit spatially-flat cosmological model with the cosmological constant reported for the Planck (2016) analysis of cosmic microwave background anisotropies. Combined with the Ly$α$ auto-correlation measurement presented in a companion paper, the BAO measurements at $z=2.34$ are within $1.7σ$ of the predictions of this model.

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arXiv2019

The extended Baryon Oscillation Spectroscopic Survey: measuring the cross-correlation between the MgII flux transmission field and quasars and galaxies at $z=0.59$

We present the first attempt at measuring the baryonic acoustic oscillations (BAO) in the large scale cross-correlation between the magnesium-II doublet (MgII) flux transmission field and the position of quasar and galaxy tracers. The MgII flux transmission continuous field at $0.3 < z < 1.6$ is measured from 500,589 quasar spectra obtained in the Baryonic Oscillation Spectroscopic Survey (BOSS) and the extended BOSS (eBOSS). The position of 246,697 quasar tracers and 1,346,776 galaxy tracers are extracted from the Sloan Digital Sky Survey (SDSS) I, II, BOSS and eBOSS catalogs. In addition to measuring the cosmological BAO scale and the biased matter density correlation, this study allows tests and improvements to cosmological Lyman-$α$ analyses. A feature consistent with that of the BAO is detected at a significance of $Δχ^{2} = 7.25$. The measured MgII linear transmission bias parameters are $b_{\mathrm{MgII(2796)}} (z = 0.59) = (-6.82 \pm 0.54) \, \times 10^{-4}$ and $b_{\mathrm{MgII(2804)}} (z = 0.59) = (-5.55 \pm 0.46) \, \times 10^{-4}$, and the MgI bias is $b_{\mathrm{MgI(2853)}} (z = 0.59) = (-1.48 \pm 0.24) \, \times 10^{-4}$. Their redshift evolution is characterized by the power-law index: $γ_{\mathrm{Mg}} = 3.36 \pm 0.46$. These measurements open a new window towards using BAO from flux transmission at $z < 1$ in the final eBOSS sample and in the upcoming sample from the Dark Energy Spectroscopic Instrument.

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arXiv2018

The Cosmological Bias Factor of Damped Lyman Alpha systems: Dependence on Metal Line Strength

We measure the cosmological bias factor of DLAs from their cross-correlation with the Ly$α$ forest absorption, as a function of the DLA metal strength, defined from an average of equivalent widths of the strongest detectable low-ionization metal lines. A clear increase of the bias factor with metal strength is detected, as expected from a relation of metallicity and velocity dispersion with host halo mass. The relation is stronger after the metal strength is corrected for the HI column density, to make it more related to metallicity instead of metal column density. After correcting for the effects of measurement errors of the metal strength parameter, we find that the bias factor of DLAs with the weakest metal lines is close to unity, consistent with an origin in dwarf galaxies with host halo masses $\sim10^{10} M_{\odot}$, whereas the most metal rich DLAs have a bias factor as large as $b_{\rm DLA} \sim 3$, indicative of massive galaxies or galaxy groups in host halos with masses $\sim 10^{12} M_{\odot}$. Our result confirms the physical origin of the relation of bias factors measured from cross-correlation studies to the host halos of the absorbers.

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