Emisores de Lyman-alpha en volúmenes cosmológicos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Física de la Tierra y Astrofísica, leída el 09-07-2019Esta tesis estudia cómo los complejos procesos de transferencia radiativa que sufren los fotones Lyman-α dentro de nubes de hidrogeno neutro determinan la function de selección de muestras de galaxies detectadas por su flujo en Lyman-α.Primero, hacemos una introducción teórica a los procesos radiativos de Lyman-α. Es de gran importancia la descripción cuántica del átomo de hidrogeno. Este formalismo predice que el átomo de hidrogeno presenta una estructura discreta de nivele de energía, el cual explica las diferentes lineas de emisión encontradas en el espectro del hidrógeno, y en particular Lyman-α. La mecánica cuántica también predice que la probabilidad de interacción entre un fotón Lyman-α y un átomo de hidrógeno es muy elevada. Esto causa que cuando uno de estos fotones entra en una nube de hidrogeno neutro, este es absorbido y reemitido constantemente, cambiando su frecuencia y dirección en cada interacción. De esta manera, la longitud de la trayectoria de los fotones Lyman-α se incrementa, lo cual hace esta radiación muy sensible a mecanismos de destrucción,como el polvo...Depto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEunpu

Zelda: Fitting Lyman Alpha Line Profiles using Deep Learning

We present zELDA (redshift Estimator for Line profiles of Distant Lyman Alpha emitters), an open-source code to fit Lyman α (Ly α) line profiles. The main motivation is to provide the community with an easy to use and fast tool to analyse Ly α line profiles uniformly to improve the understating of Ly α emitting galaxies. zELDA is based online profiles of the commonly used \u27shell-model\u27 pre-computed with the full Monte Carlo radiative transfer code LyaRT. Via interpolation between these spectra and the addition of noise, we assemble a suite of realistic Ly α spectra which we use to train a deep neural network. We show that the neural network can predict the model parameters to high accuracy (e.g.≲ 0.34 dex H i column density for R ∼12 000) and thus allows for a significant speedup over existing fitting methods. As a proof of concept, we demonstrate the potential of zELDA by fitting 97 observed Ly α line profiles from the LASD data base. Comparing the fitted value with the measured systemic redshift of these sources, we find that Ly α determines their rest frame Ly α wavelength with a remarkable good accuracy of ∼0.3 Å (∼ 75 km, s-1). Comparing the predicted outflow properties and the observed Ly α luminosity and equivalent width, we find several possible trends. For example, we find an anticorrelation between the Ly α luminosity and the outflow neutral hydrogen column density, which might be explained by the radiative transfer process within galaxies

The miniJPAS & J-NEP surveys: Identification and characterization of the Lyα\alpha Emitter population and the Lyα\alpha Luminosity Function

We present the Lyman-$a$ (Lya) Luminosity Function (LF) at $2.05<z<3.75$, estimated from a sample of 67 Lya-emitter (LAE) candidates in the J-PAS Pathfinder surveys: miniJPAS and J-NEP. These two surveys cover a total effective area of $\sim 1.14$ deg$^2$ with 54 Narrow Band (NB) filters across the optical range, with typical limiting magnitudes of $\sim 23$. This set of NBs allows to probe Lya emission in a wide and continuous range of redshifts. We develop a method for detecting Lya emission for the estimation of the Lya LF using the whole J-PAS filter set. We test this method by applying it to the miniJPAS and J-NEP data. In order to compute the corrections needed to estimate the Lya LF and to test the performance of the candidates selection method, we build mock catalogs. These include representative populations of Lya Emitters at $1.9<z<4.5$ as well as their expected contaminants, namely low-$z$ galaxies and $z<2$ QSOs. We show that our method is able to provide the Lya LF at the intermediate-bright range of luminosity ($\rm 10^{43.5} erg\,s^{-1} \lesssim L_{Lya} \lesssim 10^{44.5} erg\,s^{-1}$). The photometric information provided by these surveys suggests that our samples are dominated by bright, Lya-emitting Active Galactic Nuclei. At $L_{{\rm Ly}a}<10^{44.5}$ erg\,s$^{-1}$, we fit our Lya LF to a power-law with slope $A=0.70\pm0.25$. We also fit a Schechter function to our data, obtaining: Log(\Phi^* / \text{Mpc^{-3}})=-6.30^{+0.48}_{-0.70}, Log$(L^*/ \rm erg\,s^{-1})=44.85^{+0.50}_{-0.32}$, $a=-1.65^{+0.29}_{-0.27}$. Overall, our results confirm the presence of an AGN component at the bright-end of the Lya LF. In particular, we find no significant contribution of star-forming LAEs to the Lya LF at Log$(L_{\rm Lya}$ / erg\,s$^{-1}$)>43.5. This work serves as a proof-of-concept for the results that can be obtained with the upcoming data releases of the J-PAS survey.Comment: 25 pages, 15 figures, submitted to A&

Lyα emitters in a cosmological volume I: the impact of radiative transfer

Lyman-α emitters (LAEs) are a promising target to probe the large scale structure of the Universe at high redshifts, z ≳ 2. However, their detection is sensitive to radiative transfer effects that depend on local astrophysical conditions. Thus, modeling the bulk properties of this galaxy population remains challenging for theoretical models. Here we develop a physically-motivated scheme to predict LAEs in cosmological simulations. The escape of Lyα photons is computed using a Monte Carlo radiative transfer code which outputs a Lyα escape fraction. To speed-up the process of assigning escape fractions to individual galaxies, we employ fitting formulae that approximate the full Monte Carlo results within an accuracy of 10% for a broad range of column densities, gas metallicities and gas bulk velocities. We apply our methodology to the semi-analytical model GALFORM on a large N-body simulation. The Lyα photons escape through an outflowing neutral gas medium, implemented assuming different geometries. This results in different predictions for the typical column density and outflow velocities of the LAE population. To understand the impact of radiative transfer on our predictions, we contrast our models against a simple abundance matching assignment. Our full models populate LAEs in less massive haloes than what is obtained with abundance matching. Overall, radiative transfer effects result in better agreement when confronting the properties of LAEs against observational measurements. This suggest that incorporating the effects of Lyα radiative transfer in the analysis of this galaxy population, including their clustering, can be important for obtaining an unbiased interpretation of future datasets

Are Lyα emitters segregated in protoclusters regions?

The presence of neutral hydrogen in the inter-stellar medium (ISM) and inter-galactic medium (IGM) induces radiative transfer (RT) effects on Lyα photons which affect the observability of Lyα emitters (LAEs). We use the GALFORM semi-analytic model of galaxy formation and evolution to analyse how these effects shape the spatial distribution of LAEs with respect to Hα emitters (HAEs) around high density regions at high redshift. We find that when a large sample of protoclusters is considered, HAEs showing also Lyα emission (HAEs+LAEs) populate the same regions as those that do not display the Lyα line at z = 2.2. We compare against the protocluster USS1558-003, one of the most massive protoclusters located at z = 2.53. Our results indicate that the strong depletion of HAEs+LAEs present in the high density regions of USS1558-003 may be due to cosmic variance. We find that at z = 2.2 and z = 3.0, RT of the ISM produces a strong decline (30-50 per cent) of the clustering amplitude of HAEs+LAEs with respect to HAEs towards the protoclusters centre. At z = 5.7, given the early evolutionary state of protoclusters and galaxies, the clustering of HAEs+LAEs has a smaller variation (10-20 per cent) towards the protoclusters centre. Depending on the equivalent width and luminosity criteria of the emission-line galaxy sample, the IGM can have a mild or a null effect on galaxy properties and clustering in high density regions

Determining the systemic redshift of Lyman α emitters with neural networks and improving the measured large-scale clustering

We explore how to mitigate the clustering distortions in Lyman α emitter (LAE) samples caused by the misidentification of the Lyman α (⁠Lyα⁠) wavelength in their Lyα line profiles. We use the Lyα line profiles from our previous LAE theoretical model that includes radiative transfer in the interstellar and intergalactic mediums. We introduce a novel approach to measure the systemic redshift of LAEs from their Lyα line using neural networks. In detail, we assume that for a fraction of the whole LAE population their systemic redshift is determined precisely through other spectral features. We then use this subset to train a neural network that predicts the Lyα wavelength given an Lyα line profile. We test two different training sets: (i) the LAEs are selected homogeneously and (ii) only the brightest LAE is selected. In comparison with previous approaches in the literature, our methodology improves significantly the accuracy in determining the Lyα wavelength. In fact, after applying our algorithm in ideal Lyα line profiles, we recover the clustering unperturbed down to 1cMpch−1⁠. Then, we test the performance of our methodology in realistic Lyα line profiles by downgrading their quality. The machine learning technique using the uniform sampling works well even if the Lyα line profile quality is decreased considerably. We conclude that LAE surveys such as HETDEX would benefit from determining with high accuracy the systemic redshift of a subpopulation and applying our methodology to estimate the systemic redshift of the rest of the galaxy sample

Lyα emitters in a cosmological volume II: the impact of the intergalactic medium

In the near future galaxy surveys will target Lyman alpha emitting galaxies (LAEs) to unveil the nature of dark energy. It has been suggested that the observability of LAEs is coupled to the large scale properties of the intergalactic medium. Such coupling could introduce distortions into the observed clustering of LAEs, adding a new potential difficulty to the interpretation of upcoming surveys. We present a model of LAEs that incorporates Lyα radiative transfer processes in the interstellar and intergalactic medium. The model is implemented in the GALFORM semi-analytic model of galaxy of formation and evolution. We find that the radiative transfer inside galaxies produces selection effects over galaxy properties. In particular, observed LAEs tend to have low metallicities and intermediate star formation rates. At low redshift we find no evidence of a correlation between the spatial distribution of LAEs and the intergalactic medium properties. However, at high redshift the LAEs are linked to the line of sight velocity and density gradient of the intergalactic medium. The strength of the coupling depends on the outflow properties of the galaxies and redshift. This effect modifies the clustering of LAEs on large scales, adding non linear features. In particular, our model predicts modifications to the shape and position of the baryon acoustic oscillation peak. This work highlights the importance of including radiative transfer physics in the cosmological analysis of LAEs