arXiv subjects

Pablo Renard

Publications and source records attributed to Pablo Renard.

14 recordsLinked to original sources

arXiv2026

Towards Bayesian Photometric Cosmic Chronometers: Application to VIPERS

The cosmic chronometer (CC) method provides a direct measurement of the expansion history, $H(z)$, from the differential ages of passively evolving galaxies. However, most CC analyses rely on high-quality spectroscopy to select passive galaxies, measure age-sensitive spectral features, and control stellar-population systematics. We build on existing works that use the D4000 spectral break as a proxy for measuring galaxy ages and apply it to a photometry-selected galaxy sample from VIPERS PDR2 in the range $0.5 \le z \le 0.8$. Our goal is to extend the scope of the standard CC framework to photometric surveys. To achieve this, we first select a massive and passive galaxy sample using rest-frame colors and mass. Second, we design a Bayesian framework to infer full galaxy age posteriors in fine redshift bins, using a D4000-age-metallicity grid from stellar population synthesis (SPS) models. We also marginalize over metallicity, using a Gaussian metallicity prior to break the D4000-age-metallicity degeneracy. Subsequently, we derive age-difference posteriors between redshift bins by convolving their age posteriors to propagate the non-Gaussian features correctly. Finally, using the median and errors extracted from the differential age posteriors, we calculate the weighted average $H(z)$ over our selected redshift range. We obtain $H(z=0.65)=93.68\pm28.27\,{\rm (stat.)}\pm10.67\,{\rm (syst.)}\ {\rm km\,s^{-1}\,Mpc^{-1}}$, which is consistent with existing spectroscopic CC measurements and with the Planck $\Lambda$CDM prediction at the same redshift. This result provides a proof of concept for extending direct $H(z)$ measurements from cosmic chronometers to photometric and spectro-photometric surveys, where larger samples can compensate for lower spectral resolution, provided that passive-galaxy selection, metallicity priors, and stellar-population systematics are carefully controlled.

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arXiv2026

Into the Gompverse: A robust Gompertzian reionization model for CMB analyses

Cosmic reionization is driven by the formation of sources of ultraviolet photons, and hence it is an intrinsically asymmetric process, where its earlier stages occur at a slower pace relative to its later stages. Yet most modern cosmic microwave background (CMB) analyses rely on a hyperbolic tangent template, i.e. a symmetric sigmoid, that is not well suited for joint fitting of CMB and reionization observations. In this work, we introduce a physically motivated Gompertzian reionization model with three astrophysical (nuisance) parameters, designed to enable joint analyses of CMB and reionization data and to be applicable to a wide range of datasets and cosmological models. This robust Gompertzian model leverages the connection between cosmology and reionization, typically ignored in standard CMB analyses, to demote the optical depth ($\tau_{\rm reio}$) to derived parameter, reducing its uncertainty by approximately a factor of three compared to the conventional $\tanh$ prescription. The $\tau_{\rm reio}$ improvement enables tighter constraints on the sum of the neutrino masses, revealing potential tension with neutrino oscillation experiments even after accounting for the known relaxation of neutrino mass bounds in $w_0w_a$CDM models -- a tension that is partially obscured by the conventional treatment of reionization. In addition, the inferred constraints on the astrophysical parameters governing reionization naturally synergize with current and upcoming 21 cm experiments, providing physically informed parameter ranges for future 21 cm studies.

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arXiv2025

Probing the influence of the protocluster environment on galaxy morphology at z = 2.23

As galaxies evolve in dense cluster and protocluster environments, they interact and quench their star formation, which gradually transforms the galaxy population from star-forming galaxies to quiescent galaxies. This transformation is identifiable by observing galaxy colors and can be seen in the morphological transformation of late-type galaxies into early-type galaxies, which creates the morphology-density relation seen when comparing populations in clusters to co-eval field galaxies. However, high-z (z > 2) galaxy morphology studies are hindered by the high angular resolution necessary to characterize morphology. We present a study of HST WFC3 F160W observations of protoclusters from the MAMMOTH survey (BOSS1244 and BOSS1542) at z ~ 2.23 with populations of previously identified HAEs. By measuring the Sersic index of 151 HAEs, we look for the early morphological transformation of star-forming galaxies in these well-studied, large, non-virialized protoclusters, which we believe are precursors of present-day clusters. We find the morphology of the populations of star-forming protocluster galaxies does not differ from the co-eval field. However, we identify a population of clumpy, potentially merging galaxies, which could lead to an increase in the population of early-type galaxies in these structures. Additionally, in BOSS1244, which has two previously identified massive quiescent galaxies including a BCG, we find an abundance of early-type galaxies near both the BCG and two co-eval high-z quasars. Although we find a strong similarity between the morphology of field and protocluster galaxies, the population of early-type star-forming galaxies surrounding the spectroscopically confirmed quiescent BCG in BOSS1244, something not seen in BOSS1542, may point to differences in the evolutionary state of these co-eval protoclusters and be a sign of an early forming cluster core in BOSS1244.

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arXiv2025

Back to basics: Little Red Dots as galaxies and dust-obscured AGNs in a synthetic NIRCam sky simulated with L-GalaxiesBH

The enigmatic Little Red Dots (LRDs) discovered by the James Webb Space Telescope (JWST) exhibit properties challenging their interpretation as common galaxies or Active Galactic Nuclei (AGN). Understanding their nature is key to placing them within our picture of early galaxy and massive black hole (MBH) evolution. To this aim, we build a realistic comparison between LRD observations with photometric properties of galaxies and AGN simulated by the L-GalaxiesBH model in a NIRCam mock sky. We model stellar continua and emission lines, the MBH emission from accretion disk, infrared radiation from dusty torus, and lines from narrow and broad line regions, accounting for dust attenuation and obscuration. Using realistic photometric cuts, we select a population of LRDs including both AGN and galaxies. The LRD fraction peaks at 40% ($\sim10^{-4}\rm Mpc^{-3}$) at $z\sim4$. Our LRDs are central galaxies spanning $M_*=10^8-10^{10.5}\rm M_\odot$. A population of galaxies with $M_*<10^9\rm M_\odot$ appear as LRDs due to older stellar populations. At higher masses, LRDs dominate the halo and stellar mass functions ($M_{\rm vir} > 10^{11.5}\rm M_\odot$, $M_* > 10^{9.5}\rm M_\odot$), and the interplay between AGN and galaxy emission drives the LRD selection. AGN dominate rest-frame UV-optical emission, while dust obscuration is secondary. LRDs host lighter MBHs ($\sim 10^{6.5}\rm M_\odot$) than non-LRDs ($\sim 10^{7.5}\rm M_\odot$), with fainter emission unable to balance their hosts Balmer breaks. We find no evidence for dominant heavy-seed origin of MBHs. LRD Galaxies (97% hosting MBHs) and LRD AGNs are disk-dominated, with LRD AGNs showing larger bulges formed mainly via disk instabilities.

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arXiv2024

MUltiplexed Survey Telescope (MUST) Science White Paper I: Overview of Large-Scale Structure Cosmology in the Era of Stage-V Spectroscopic Surveys

The MUltiplexed Survey Telescope (MUST) is a 6.5-meter telescope under development. Dedicated to highly-multiplexed, wide-field spectroscopic surveys, MUST observes over 20,000 targets simultaneously using 6.2-mm pitch positioning robots within a ~5 deg$^2$ field of view. MUST aims to conduct the first Stage-V spectroscopic survey in the 2030s, mapping the 3D Universe with over 100 million galaxies and quasars, spanning from the nearby Universe to a redshift of z ~ 5.5, corresponding to approximately 1 billion years after the Big Bang. To cover this extensive redshift range, we present an initial conceptual target selection algorithm for different types of galaxies, ranging from local bright galaxies and luminous red galaxies to emission-line galaxies, and high-redshift (2 < z < 5.5) Lyman-break galaxies. Using Fisher forecasts, we demonstrate that MUST can address fundamental questions in cosmology, including the nature of dark energy, tests of gravity theories, and investigations into primordial physics. This is the first paper in the series of science white papers for MUST, with subsequent developments focusing on additional scientific cases such as galaxy and quasar evolution, Milky Way physics, and dynamic phenomena in the time-domain Universe.

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arXiv2024

ANNZ+: an enhanced photometric redshift estimation algorithm with applications on the PAU Survey

ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift estimation decades ago. We enhanced the algorithm by introducing new activation functions like tanh, softplus, SiLU, Mish and ReLU variants; its new performance is then vigorously tested on legacy samples like the Luminous Red Galaxy (LRG) and Stripe-82 samples from SDSS, as well as modern galaxy samples like the Physics of the Accelerating Universe Survey (PAUS). This work focuses on testing the robustness of activation functions with respect to the choice of ANN architectures, particularly on its depth and width, in the context of galaxy photometric redshift estimation. Our upgraded algorithm, which we named ANNZ+, shows that the tanh and Leaky ReLU activation functions provide more consistent and stable results across deeper and wider architectures with > 1 per cent improvement in root-mean-square error ($\sigma_{\textrm{RMS}}$) and 68th percentile error ($\sigma_{68}$) when tested on SDSS data sets. While assessing its capabilities in handling high dimensional inputs, we achieved an improvement of 11 per cent in $\sigma_{\textrm{RMS}}$ and 6 per cent in $\sigma_{68}$ with the tanh activation function when tested on the 40-narrowband PAUS dataset; it even outperformed ANNZ2, its supposed successor, by 44 per cent in $\sigma_{\textrm{RMS}}$. This justifies the effort to upgrade the 20-year-old ANNZ, allowing it to remain viable and competitive within the photo-z community today. The updated algorithm ANNZ+ is publicly available at https://github.com/imdadmpt/ANNzPlus.

astro-ph.IM↗

arXiv2024

The PAU Survey: The quasar UV and Ly$\alpha$ luminosity functions at $2.7<z<5.3$

We present the Lyman-$\alpha$ (Ly$\alpha$) and ultraviolet (UV) luminosity function (LF), in bins of redshift, of quasars selected in the Physics of the Accelerating Universe Survey (PAUS). A sample of 915 objects was selected at $2.7 10^{44}$ ${\rm erg\,s}$$^{-1}$. In order to obtain corrections for the LF estimation, and assess the accuracy of our selection method, we produced mock catalogs of $0<z<4.3$ quasars and galaxies that mimic our target population and their main contaminants. Our results show a clear evolution of the Ly$\alpha$ and UV LFs, with a declining tendency in the number density of quasars towards increasing redshifts. In addition, the faint-end power-law slope of the Ly$\alpha$ LF becomes steeper with redshift, suggesting that the number density of Ly$\alpha$-bright quasars declines faster than that of fainter emitters. By integrating the Ly$\alpha$ LF we find that the total Ly$\alpha$ emitted by bright quasars per unit volume rapidly declines with increasing redshift, being sub-dominant to that of star-forming galaxies by several orders of magnitude by $z\sim 4$. Finally, we stack the NB pseudo-spectra of a visually selected "golden sample" of 591 quasars to obtain photometric composite SEDs in bins of redshift, enabling to measure the mean IGM absorption by the Lyman-$\alpha$ forest as a function of redshift.

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arXiv2024

Probing the cosmic web in Ly$\alpha$ emission over large scales: an Intensity Mapping forecast for DECaLS/BASS and DESI

Being the most prominent HI line, Ly$\alpha$ permeates the cosmic web in emission. Despite its potential as a cosmological probe, its detection on large scales remains elusive. We present a new methodology to perform Ly$\alpha$ intensity mapping with broad-band optical images, by cross-correlating them with Ly$\alpha$ forest data using a custom one-parameter estimator. We also develop an analytical large-scale Ly$\alpha$ emission model with two parameters (average luminosity $\langle L_{\rm Ly\alpha} \rangle$ and bias $b_{\rm e}$) that respects observational constraints from QSO luminosity functions. We compute a forecast for DECaLS/BASS $g$-band images cross-correlated with DESI Ly$\alpha$ forest data, setting guidelines for reducing images into Ly$\alpha$ intensity maps. Given the transversal scales of our cross-correlation (26.4 arcmin, $\sim$33 cMpc/h), our study effectively integrates Ly$\alpha$ emission over all the cosmic volume inside the DESI footprint at $2.2 < z < 3.4$ (the $g$-band Ly$\alpha$ redshift range). Over the parameter space ($\langle L_{\rm Ly\alpha} \rangle$, $b_{\rm e}$) sampled by our forecast, we find a 3$\sigma$ of large-scale structure in Ly$\alpha$ likely, with a probability of detection of 23.95\% for DESI-DECaLS/BASS, and 54.93\% for a hypothetical DESI phase II with twice as much Ly$\alpha$ QSOs. Without a detection, we derive upper bounds on $\langle L_{\rm Ly\alpha} \rangle$ competitive with optimistic literature estimates ($2.3 \pm 1 \cdot 10^{\rm 41}$ erg/s/cMpc$^3$ for DESI, and $\sim$35\% lower for its hypothetical phase II). Extrapolation to the DESI-Rubin overlap shows that a detection of large-scale structure with Ly$\alpha$ intensity mapping using next-generation imaging surveys is certain. [abridged]

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arXiv2024

The PAU Survey: galaxy stellar population properties estimates with narrowband data

Narrowband galaxy surveys have recently gained interest as a promising method to achieve the necessary accuracy on the photometric redshift estimate of individual galaxies for stage-IV cosmological surveys. One key advantage is the ability to provide higher spectral resolution information about galaxies that should allow a more accurate and precise estimation of galaxy stellar population properties. However, the impact of adding narrow-band photometry on the stellar population properties estimate is largely unexplored. The scope of this work is two-fold: on one side, leveraging the predictive power of broad-band and narrow-band data to infer galaxy physical properties such as stellar masses, ages, star formation rates and metallicities. On the other hand, evaluating the improvement of performance in estimating galaxy properties when we use narrow-band data instead of broad-band. In this work we measure the stellar population properties of a sample of galaxies in the COSMOS field for which both narrowband and broadband data are available. In particular, we employ narrowband data from PAUS and broad-band data from CFHTLS. We use two different spectral energy distribution fitting codes to measure galaxy properties, namely CIGALE and Prospector. We find that the increased spectral resolution of narrow-band photometry does not yield a substantial improvement on constraining galaxy properties using spectral energy distribution fitting. Still we find that we obtain a more diverse distribution of metallicities and dust optical depths with cigale when employing the narrowband data. The effect is not as prominent as expected, which we relate this to the low narrowband SNR of a majority of the galaxies, the respective drawbacks of both codes as well as the coverage only in the optical regime. The measured properties are afterwards compared to the COSMOS2020 catalogue, showing good agreement.

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arXiv2023

Neutral Hydrogen content of dwarf galaxies in different environments

Environments play an important role in galaxy formation and evolution, particularly in regulating the content of neutral gas. However, current HI surveys have limitations in their depth, which prevents them from adequately studying low HI content galaxies in high-density regions. In this study, we address this issue by employing the Five-hundred-meter Aperture Spherical radio Telescope (FAST) with extensive integration times to complement the relatively shallow Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) HI survey. This approach allows us to explore the gas content of dwarf galaxies across various environments. We observe a positive relationship between HI mass and stellar mass in dwarf galaxies, with a well-defined upper boundary for HI mass that holds true in both observations and simulations. Furthermore, we find a decrease in the HI-to-stellar mass ratio ($\rm M_{\rm HI}/M_*$) as the density of the environment increases, irrespective of whether it is determined by the proximity to the nearest group or the projected number density. Comparing our observations to simulations, we note a steeper slope in the relationship, indicating a gradual gas-stripping process in the observational data. Additionally, we find that the scaling relation between the $\rm M_{\rm HI}/M_*$ and optical properties can be improved by incorporating galaxy environments.

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arXiv2022

The PAU Survey: Measurements of the 4000 {\AA} spectral break with narrow-band photometry

The D4000 spectral break index is one of the most important features in the visible spectrum, as it is a proxy for stellar ages and is also used in galaxy classification. However, its direct measurement has always been reserved to spectroscopy. Here, we present a general method to directly measure the D4000 with narrow-band (NB) photometry; it has been validated using realistic simulations, and then evaluated with PAUS NBs, cross-matched with VIPERS spectra ($i_{\rm AB} < 22.5$, $0.562 < z < 0.967$). We also reconstruct the D4000 with the SED-fitting code CIGALE; the use of PAUS NBs instead of broad bands significantly improves the SED fitting results. For D4000$_{\rm n}$, the direct measurement has $\rm \langle SNR \rangle \sim 4$, but we find that for $i_{\rm AB}<21$ all direct D4000 measurements have $\rm SNR>3$. The CIGALE D4000$_{\rm n}$ has $\rm \langle SNR \rangle \sim 20$, but underestimates the error by $>$50\%. Furthermore, the direct method recreates well the D4000-SFR relation, as well as the D4000-mass relation for blue galaxies (for red galaxies, selection effects impact the results). On the other hand, CIGALE accurately classifies galaxies into red and blue populations. We conclude that the direct measurement of D4000 with narrow-band photometry is a promising tool to determine average properties of galaxy samples, with results compatible with spectroscopy.

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arXiv2021

The PAU Survey: Measurement of Narrow-band galaxy properties with Approximate Bayesian Computation

Narrow-band imaging surveys allow the study of the spectral characteristics of galaxies without the need of performing their spectroscopic follow-up. In this work, we forward-model the Physics of the Accelerating Universe Survey (PAUS) narrow-band data. The aim is to improve the constraints on the spectral coefficients used to create the galaxy spectral energy distributions (SED) of the galaxy population model in Tortorelli et al. 2020. In that work, the model parameters were inferred from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) data using Approximate Bayesian Computation (ABC). This led to stringent constraints on the B-band galaxy luminosity function parameters, but left the spectral coefficients only broadly constrained. To address that, we perform an ABC inference using CFHTLS and PAUS data. This is the first time our approach combining forward-modelling and ABC is applied simultaneously to multiple datasets. We test the results of the ABC inference by comparing the narrow-band magnitudes of the observed and simulated galaxies using Principal Component Analysis, finding a very good agreement. Furthermore, we prove the scientific potential of the constrained galaxy population model to provide realistic stellar population properties by measuring them with the SED fitting code \textsc{CIGALE}. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited ($\mathrm{i}<22.5$) sample of galaxies up to redshift $\mathrm{z \sim 0.8}$. We find that properties like stellar masses, star-formation rates, mass-weighted stellar ages and metallicities are in agreement within errors between observations and simulations. Overall, this work shows the ability of our galaxy population model to correctly forward-model a complex dataset such as PAUS and the ability to reproduce the diversity of galaxy properties at the redshift range spanned by CFHTLS and PAUS.

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arXiv2021

The PAU survey: Ly$α$ intensity mapping forecast

In this work, we explore the application of intensity mapping to detect extended Ly$α$ emission from the IGM via cross-correlation of PAUS images with Ly$α$ forest data from eBOSS and DESI. Seven narrow-band (FWHM=13nm) PAUS filters have been considered, ranging from 455 to 515 nm in steps of 10 nm, which allows the observation of Ly$α$ emission in a range $2.7<z<3.3$. The cross-correlation is simulated first in an area of 100 deg$^2$ (PAUS projected coverage), and second in two hypothetical scenarios: a deeper PAUS (complete up to $i_{\rm AB}<24$ instead of $i_{\rm AB}<23$, observation time x6), and an extended PAUS coverage of 225 deg$^2$ (observation time x2.25). A hydrodynamic simulation of size 400 Mpc/h is used to simulate both extended Ly$α$ emission and absorption, while the foregrounds in PAUS images have been simulated using a lightcone mock catalogue. Using an optimistic estimation of uncorrelated PAUS noise, the total probability of a non-spurious detection is estimated to be 1.8\% and 4.5\% for PAUS-eBOSS and PAUS-DESI , from a run of 1000 simulated cross-correlations with different realisations of instrumental noise and quasar positions. The hypothetical PAUS scenarios increase this probability to 15.3\% (deeper PAUS) and 9.0\% (extended PAUS). With realistic correlated noise directly measured from PAUS images, these probabilities become negligible. Despite these negative results, some evidences suggest that this methodology may be more suitable to broad-band surveys.

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arXiv2020

The PAU Survey: An improved photo-$z$ sample in the COSMOS field

We present -- and make publicly available -- accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with $i_{\mathrm{AB}}\leq 23$. The redshifts are computed using a combination of narrow band photometry from PAUS, a survey with 40 narrow bands spaced at $100Å$ intervals covering the range from $4500Å$ to $8500Å$, and 26 broad, intermediate, and narrow bands covering the UV, visible and near infrared spectrum from the COSMOS2015 catalogue. We introduce a new method that models the spectral energy distributions (SEDs) as a linear combination of continuum and emission line templates and computes its Bayes evidence, integrating over the linear combinations. The correlation between the UV luminosity and the OII line is measured using the 66 available bands with the zCOSMOS spectroscopic sample, and used as a prior which constrains the relative flux between continuum and emission line templates. The flux ratios between the OII line and $\mathrm{H}_α$, $\mathrm{H}_β$ and $\mathrm{OIII}$ are similarly measured and used to generate the emission line templates. Comparing to public spectroscopic surveys via the quantity $Δ_z\equiv(z_{\mathrm{photo}}-z_{\mathrm{spec}})/(1+z_{\mathrm{spec}})$, we find the photometric redshifts to be more precise than previous estimates, with $σ_{68}(Δ_z) \approx (0.003, 0.009)$ for galaxies at magnitude $i_{\mathrm{AB}}\sim18$ and $i_{\mathrm{AB}}\sim23$, respectively, which is $3\times$ and $1.66\times$ tighter than COSMOS2015. Additionally, we find the redshifts to be very accurate on average, yielding a median of the $Δ_z$ distribution compatible with $|\mathrm{median}(Δ_z)|\leq0.001$ at all redshifts and magnitudes considered. Both the added PAUS data and new methodology contribute significantly to the improved results.

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