arXiv subjects

Jonás Chaves-Montero

Publications and source records attributed to Jonás Chaves-Montero.

32 records · Page 2Linked to original sources

arXiv2022

The miniJPAS survey: Identification and characterization of the emission line galaxies down to $z < 0.35$ in the AEGIS field

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is expected to map thousands of square degrees of the northern sky with 56 narrowband filters in the upcoming years. This will make J-PAS a very competitive and unbiased emission line survey compared to spectroscopic or narrowband surveys with fewer filters. The miniJPAS survey covered 1 deg$^2$, and it used the same photometric system as J-PAS, but the observations were carried out with the pathfinder J-PAS camera. In this work, we identify and characterize the sample of emission line galaxies (ELGs) from miniJPAS with a redshift lower than $0.35$. Using a method based on artificial neural networks, we detect the ELG population and measure the equivalent width and flux of the $Hα$, $Hβ$, [OIII], and [NII] emission lines. We explore the ionization mechanism using the diagrams [OIII]/H$β$ versus [NII]/H$α$ (BPT) and EW(H$α$) versus [NII]/H$α$ (WHAN). We identify 1787 ELGs ($83$%) from the parent sample (2154 galaxies) in the AEGIS field. For the galaxies with reliable EW values that can be placed in the WHAN diagram (2000 galaxies in total), we obtained that $72.8 \pm 0.4$%, $17.7 \pm 0.4$% , and $9.4 \pm 0.2$% are star-forming (SF), active galactic nucleus (Seyfert), and quiescent galaxies, respectively. Based on the flux of $Hα$ we find that the star formation main sequence is described as $\log$ SFR $[M_\mathrm{\odot} \mathrm{yr}^{-1}] = 0.90^{+ 0.02}_{-0.02} \log M_{\star} [M_\mathrm{\odot}] -8.85^{+ 0.19}_{-0.20}$ and has an intrinsic scatter of $0.20^{+ 0.01}_{-0.01}$. The cosmic evolution of the SFR density ($ρ_{\text{SFR}}$) is derived at three redshift bins: $0 < z \leq 0.15$, $0.15 < z \leq 0.25$, and $0.25 < z \leq 0.35$, which agrees with previous results that were based on measurements of the $Hα$ emission line.

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arXiv2022

Relativistic Angular Redshift Fluctuations embedded in Large Scale Varying Gravitational Potentials

We compute the linear order, general relativistic corrections to angular redshift fluctuations (ARF), a new cosmological observable built upon density-weighted two-dimensional (2D) maps of galaxy redshifts. We start with an existing approach for galaxy/source counts developed in the Newtonian gauge, and generalize it to ARF, modifying for this purpose a standard Boltzmann code. Our calculations allow us identifying the velocity terms as the leading corrections on large scales, emphasizing the sensitivity of ARF to peculiar, cosmological velocity fields. Just like for standard 2D clustering, the impact of gravitational lensing on ARF is dominant on small angular scales and for wide redshift shells, while the signatures associated to gravitational potentials are extremely small and hardly detectable. The ARF also present interesting correlation properties to anisotropies of the Cosmic Microwave Background (CMB): they are highly correlated to CMB lensing potential fluctuations, while also exhibiting a significant (S/N$\sim 4$-$5$) {\em anti-}correlation with the Integrated Sachs-Wolfe effect (ISW). This negative ARF$\times$ISW signal is quite complementary to the standard 2D clustering$\times$ISW correlation, since the former appears mostly at higher redshift ($z\sim 2$) than the latter ($z\lesssim 1)$, and the combination of the two observables significantly increases the $χ^2$ statistics testing the null (no ISW) hypothesis. We conclude that ARF constitute a novel, alternative, and potentially powerful tool to constrain the nature of Dark Energy component that gives rise to the ISW.

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arXiv2022

A Differentiable Model of the Assembly of Individual and Populations of Dark Matter Halos

We present a new empirical model for the mass assembly of dark matter halos. We approximate the growth of individual halos as a simple power-law function of time, where the power-law index smoothly decreases as the halo transitions from the fast-accretion regime at early times, to the slow-accretion regime at late times. Using large samples of halo merger trees taken from high-resolution cosmological simulations, we demonstrate that our 3-parameter model, Diffmah, can approximate halo growth with a typical accuracy of 0.1 dex for t > 1 Gyr for all halos of present-day mass greater than 10^11Msun, including subhalos and host halos in gravity-only simulations, as well as in the TNG hydrodynamical simulation. We additionally present a new model for the assembly of halo populations, DiffmahPop, which not only reproduces average mass growth across time, but also faithfully captures the diversity with which halos assemble their mass. Our python implementation is based on the autodiff library JAX, and so our model self-consistently captures the mean and variance of halo mass accretion rate across cosmic time. We show that the connection between halo assembly and the large-scale density field, known as halo assembly bias, is accurately captured by Diffmah, and that residual errors in our approximations to halo assembly history exhibit a negligible residual correlation with the density field. Our publicly available source code can be used to generate Monte Carlo realizations of cosmologically representative halo histories; our differentiable implementation facilitates the incorporation of our model into existing analytical halo model frameworks.

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arXiv2022

Black hole virial masses from single-epoch photometry: the miniJPAS test case

Precise measurements of black hole masses are essential to understanding the coevolution of these sources and their host galaxies. We develop a novel approach for computing black hole virial masses using measurements of continuum luminosities and emission line widths from partially overlapping, narrow-band observations of quasars; we refer to this technique as single-epoch photometry. This novel method relies on forward-modelling quasar observations for estimating emission line widths, which enables unbiased measurements even for lines coarsely resolved by narrow-band data. We assess the performance of this technique using quasars from the Sloan Digital Sky Survey (SDSS) observed by the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering $\simeq1\,\mathrm{deg}^2$ of the northern sky using the 56 J-PAS narrow-band filters. We find remarkable agreement between black hole masses from single-epoch SDSS spectra and single-epoch miniJPAS photometry, with no systematic difference between these and a scatter ranging from 0.4 to 0.07 dex for masses from $\log(M_\mathrm{BH})\simeq8$ to 9.75, respectively. Reverberation mapping studies show that single-epoch masses present approximately 0.4 dex precision, letting us conclude that our novel technique delivers black hole masses with only mildly lower precision than single-epoch spectroscopy. The J-PAS survey will soon start observing thousands of square degrees without any source preselection other than the photometric depth in the detection band, and thus single-epoch photometry has the potential to provide details on the physical properties of quasar populations that do not satisfy the preselection criteria of previous spectroscopic surveys.

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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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arXiv2021

Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z

Photometric redshift estimation algorithms are often based on representative data from observational campaigns. Data-driven methods of this type are subject to a number of potential deficiencies, such as sample bias and incompleteness. Motivated by these considerations, we propose using physically motivated synthetic spectral energy distributions in redshift estimation. In addition, the synthetic data would have to span a domain in colour-redshift space concordant with that of the targeted observational surveys. With a matched distribution and realistically modelled synthetic data in hand, a suitable regression algorithm can be appropriately trained; we use a mixture density network for this purpose. We also perform a zero-point re-calibration to reduce the systematic differences between noise-free synthetic data and the (unavoidably) noisy observational data sets. This new redshift estimation framework, SYTH-Z, demonstrates superior accuracy over a wide range of redshifts compared to baseline models trained on observational data alone. Approaches using realistic synthetic data sets can therefore greatly mitigate the reliance on expensive spectroscopic follow-up for the next generation of photometric surveys.

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arXiv2021

The cosmological dependence of halo and galaxy assembly bias

One of the main predictions of excursion set theory is that the clustering of dark matter haloes only depends on halo mass. However, it has been long established that the clustering of haloes also depends on other properties, including formation time, concentration, and spin; this effect is commonly known as halo assembly bias. We use a suite of gravity-only simulations to study the dependence of halo assembly bias on cosmology; these simulations cover cosmological parameters spanning 10$σ$ around state-of-the-art best-fitting values, including standard extensions of the $Λ$CDM paradigm such as neutrino mass and dynamical dark energy. We find that the strength of halo assembly bias presents variations smaller than 0.05 dex across all cosmologies studied for concentration and spin selected haloes, letting us conclude that the dependence of halo assembly bias upon cosmology is negligible. We then study the dependence of galaxy assembly bias (i.e. the manifestation of halo assembly bias in galaxy clustering) on cosmology using subhalo abundance matching. We find that galaxy assembly bias also presents very small dependence upon cosmology ($\sim$ 2$\%$-4$\%$ of the total clustering); on the other hand, we find that the dependence of this signal on the galaxy formation parameters of our galaxy model is much stronger. Taken together, these results let us conclude that the dependence of halo and galaxy assembly bias on cosmology is practically negligible.

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arXiv2021

On the influence of halo mass accretion history on galaxy properties and assembly bias

Halo assembly bias is the secondary dependence of the clustering of dark-matter haloes on their assembly histories at fixed halo mass. This established dependence is expected to manifest itself on the clustering of the galaxy population, a potential effect commonly known as galaxy assembly bias. Using the IllustrisTNG300 magnetohydrodynamical simulation, we analyse the dependence of the properties and clustering of galaxies on the shape of the specific mass accretion history of their hosting haloes (sMAH). We first show that several halo and galaxy properties strongly correlate with the slope of the sMAH ($β$) at fixed halo mass. Namely, haloes with increasingly steeper $β$ increment their halo masses faster at early times, and their hosted galaxies present larger stellar-to-halo mass ratios, lose their gas faster, reach the peak of their star formation histories at higher redshift, and become quenched earlier. We also demonstrate that $β$ is more directly connected to these key galaxy formation properties than other broadly employed halo proxies, such as formation time. Finally, we measure the secondary dependence of galaxy clustering on $β$ at fixed halo mass as a function of redshift. By tracing back the evolution of individual haloes, we show that the amplitude of the galaxy assembly bias signal for the progenitors of $z=0$ galaxies increases with redshift, reaching a factor of 2 at $z = 1$ for haloes of $M_\mathrm{halo}=10^{11.5}-10^{12}$ $h^{-1}\mathrm{M}_\odot$. The measurement of the evolution of assembly bias along the merger tree provides a new theoretical perspective to the study of secondary bias. Our findings, which show a tight relationship between halo accretion and both the clustering and the observational properties of the galaxy population, have also important implications for the generation of mock catalogues for upcoming cosmological surveys.

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arXiv2021

Tomographic Constraints on Gravity from Angular Redshift Fluctuations in the Late Universe

Fluctuations in sky maps of the galaxy redshifts, dubbed as angular redshift fluctuations (ARF), contain precise information about the growth rate of structures and the nature of gravity in the Universe. Specifically, ARF constrain the combination of cosmological parameters $H/H_0\,fσ_8(z)$, while being an intrinsically tomographic probe and largely insensitive to many observational systematic errors, all this without requiring the assumption of any redshift-to-distance relation under a given fiducial cosmology. We present the first cosmological constraints derived from ARF by using BOSS LOWZ+CMASS DR12 galaxy samples, obtaining 7\%-accurate constraints on $H/H_0 fσ_8(z)$ at more than 20 redshifts over the range $z \in [0.26,0.72]$. Our best-fitting value is $10\%$ larger, but compatible at the $1.4σ$ level, than the $Λ$CDM expectation set by {\it Planck} observations of the Cosmic Microwave Background (CMB) radiation. Our tomographic measurements, combined with these CMB data, provides one of the strongest constraints on the gravity index $γ$, $γ=0.44^{+0.09}_{-0.07}$, which lies within $2σ$ from the prediction of General Relativity ($γ_{\rm GR}\simeq 0.55$).

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arXiv2019

Inflation and Dark Energy from spectroscopy at $z > 2$

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at $z < 1$, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. The large cosmological volume at $2 < z < 5$, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $σ(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space.

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arXiv2018

Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey II: Report of a Community Workshop on the Scientific Synergies Between the SPHEREx Survey and Other Astronomy Observatories

SPHEREx is a proposed NASA MIDEX mission selected for Phase A study. SPHEREx would carry out the first all-sky spectral survey in the near infrared. At the end of its two-year mission, SPHEREx would obtain 0.75-to-5$μ$m spectra of every 6.2 arcsec pixel on the sky, with spectral resolution R>35 and a 5-$σ$ sensitivity AB$>$19 per spectral/spatial resolution element. More details concerning SPHEREx are available at http://spherex.caltech.edu. The SPHEREx team has proposed three specific science investigations to be carried out with this unique data set: cosmic inflation, interstellar and circumstellar ices, and the extra-galactic background light. Though these three themes are undoubtedly compelling, they are far from exhausting the scientific output of SPHEREx. Indeed, SPHEREx would create a unique all-sky spectral database including spectra of very large numbers of astronomical and solar system targets, including both extended and diffuse sources. These spectra would enable a wide variety of investigations, and the SPHEREx team is dedicated to making the data available to the community to enable these investigations, which we refer to as Legacy Science. To that end, we have sponsored two workshops for the general scientific community to identify the most interesting Legacy Science themes and to ensure that the SPHEREx data products are responsive to their needs. In February of 2016, some 50 scientists from all fields met in Pasadena to develop these themes and to understand their implications for the SPHEREx mission. The 2016 workshop highlighted many synergies between SPHEREx and other contemporaneous astronomical missions, facilities, and databases. Consequently, in January 2018 we convened a second workshop at the Center for Astrophysics in Cambridge to focus specifically on these synergies. This white paper reports on the results of the 2018 SPHEREx workshop.

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arXiv2018

The effect of photometric redshift uncertainties on galaxy clustering and baryonic acoustic oscillations

In the upcoming era of high-precision galaxy surveys, it becomes necessary to understand the impact of redshift uncertainties on cosmological observables. In this paper we explore the effect of sub-percent photometric redshift errors (photo-$z$ errors) on galaxy clustering and baryonic acoustic oscillations (BAO). Using analytic expressions and results from $1\,000$ $N$-body simulations, we show how photo-$z$ errors modify the amplitude of moments of the 2D power spectrum, their variances, the amplitude of BAO, and the cosmological information in them. We find that: a) photo-$z$ errors suppress the clustering on small scales, increasing the relative importance of shot noise, and thus reducing the interval of scales available for BAO analyses; b) photo-$z$ errors decrease the smearing of BAO due to non-linear redshift-space distortions (RSD) by giving less weight to line-of-sight modes; and c) photo-$z$ errors (and small-scale RSD) induce a scale dependence on the information encoded in the BAO scale, and that reduces the constraining power on the Hubble parameter. Using these findings, we propose a template that extracts unbiased cosmological information from samples with photo-$z$ errors with respect to cases without them. Finally, we provide analytic expressions to forecast the precision in measuring the BAO scale, showing that spectro-photometric surveys will measure the expansion history of the Universe with a precision competitive to that of spectroscopic surveys.

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arXiv2017

ELDAR, a new method to identify AGN in multi-filter surveys: the ALHAMBRA test-case

We present ELDAR, a new method that exploits the potential of medium- and narrow-band filter surveys to securely identify active galactic nuclei (AGN) and determine their redshifts. Our methodology improves on traditional approaches by looking for AGN emission lines expected to be identified against the continuum, thanks to the width of the filters. To assess its performance, we apply ELDAR to the data of the ALHAMBRA survey, which covered an effective area of $2.38\,{\rm deg}^2$ with 20 contiguous medium-band optical filters down to F814W$\simeq 24.5$. Using two different configurations of ELDAR in which we require the detection of at least 2 and 3 emission lines, respectively, we extract two catalogues of type-I AGN. The first is composed of 585 sources ($79\,\%$ of them spectroscopically-unknown) down to F814W$=22.5$ at $z_{\rm phot}>1$, which corresponds to a surface density of $209\,{\rm deg}^{-2}$. In the second, the 494 selected sources ($83\,\%$ of them spectroscopically-unknown) reach F814W$=23$ at $z_{\rm phot}>1.5$, for a corresponding number density of $176\,{\rm deg}^{-2}$. Then, using samples of spectroscopically-known AGN in the ALHAMBRA fields, for the two catalogues we estimate a completeness of $73\,\%$ and $67\,\%$, and a redshift precision of $1.01\,\%$ and $0.86\,\%$ (with outliers fractions of $8.1\,\%$ and $5.8\,\%$). At $z>2$, where our selection performs best, we reach $85\,\%$ and $77\,\%$ completeness and we find no contamination from galaxies.

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arXiv2016

Subhalo abundance matching and assembly bias in the EAGLE simulation

Subhalo abundance matching (SHAM) is a widely-used method to connect galaxies with dark matter structures in numerical simulations. SHAM predictions agree remarkably well with observations, yet they still lack strong theoretical support. We examine the performance, implementation, and assumptions of SHAM using the EAGLE project simulations. We find that $V_{\rm relax}$, the highest value of the circular velocity attained by a subhalo while it satisfies a relaxation criterion, is the subhalo property that correlates most strongly with galaxy stellar mass ($M_{\rm star}$). Using this parameter in SHAM, we retrieve the real-space clustering of EAGLE to within our statistical uncertainties on scales greater than $2$ Mpc for galaxies with $8.77<\log_{10}(M_{\rm star}[M_\odot])<10.77$. Conversely, clustering is overestimated by $30\%$ on scales below $2$ Mpc for galaxies with $8.77<\log_{10}(M_{\rm star}[M_\odot])<9.77$ because SHAM slightly overpredicts the fraction of satellites in massive haloes compared to EAGLE. The agreement is even better in redshift-space, where the clustering is recovered to within our statistical uncertainties for all masses and separations. Additionally, we analyse the dependence of galaxy clustering on properties other than halo mass, i.e. the assembly bias. We demonstrate assembly bias alters the clustering in EAGLE by $20\%$ and that $V_{\rm relax}$ captures its effect to within $15\%$. We trace small differences in the clustering to the failure of SHAM as typically implemented, i.e. the $M_{\rm star}$ assigned to a subhalo does not depend on i) its host halo mass, ii) whether it is a central or a satellite. In EAGLE we find that these assumptions are not completely satisfied.

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