M. Cerviño

The stochastic nature of stellar population modelling

Abstract Since the early 1970s, stellar population modelling has been one of the basic tools for understanding the physics of unresolved systems from observation of their integrated light. Models allow us to relate the integrated spectra (or colours) of a system with the evolutionary status of the stars of which it is composed and hence to infer how the system has evolved from its formation to its present stage. On average, observational data follow model predictions, but with some scatter, so that systems with the same physical parameters (age, metallicity, total mass) produce a variety of integrated spectra. The fewer the stars in a system, the larger is the scatter. Such scatter is sometimes much larger than the observational errors, reflecting its physical nature. This situation has led to the development in recent years (especially since 2010) of Monte Carlo models of stellar populations. Some authors have proposed that such models are more realistic than state-of-the-art standard synthesis codes that produce the mean of the distribution of Monte Carlo models. In this review, I show that these two modelling strategies are actually equivalent, and that they are not in opposition to each other. They are just different ways of describing the probability distributions intrinsic in the very modelling of stellar populations. I show the advantages and limitations of each strategy and how they complement each other. I also show the implications of the probabilistic description of stellar populations in the application of models to observational data obtained with high-resolution observational facilities. Finally, I outline some possible developments that could be realized in stellar population modelling in the near future.

Stellar populations of galaxies in the ALHAMBRA survey up to z ~ 1 - I. MUFFIT: A multi-filter fitting code for stellar population diagnostics

Aims. We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and check its reliability and feasibility with real galaxy data from the ALHAMBRA survey. Methods. Making use of an error-weighted χ 2 -test, we compare the multi-filter fluxes of galaxies with the synthetic photometry of mixtures of two single stellar populations at different redshifts and extinctions, to provide the most likely range of stellar population parameters (mainly ages and metallicities), extinctions, redshifts, and stellar masses. To improve the diagnostic reliability, MUFFIT identifies and removes from the analysis those bands that are significantly affected by emission lines. The final parameters and their uncertainties are derived by a Monte Carlo method, using the individual photometric uncertainties in each band. Finally, we discuss the accuracies, degeneracies, and reliability of MUFFIT using both simulated and real galaxies from ALHAMBRA, comparing with results from the literature. Results. MUFFIT is a precise and reliable code to derive stellar population parameters of galaxies in ALHAMBRA. Using the results from photometric-redshift codes as input, MUFFIT improves the photometric-redshift accuracy by ∼10–20%. MUFFIT also detects nebular emissions in galaxies, providing physical information about their strengths. The stellar masses derived from MUFFIT show excellent agreement with the COSMOS and SDSS values. In addition, the retrieved age-metallicity locus for a sample of z ≤ 0.22 early-type galaxies in ALHAMBRA at different stellar mass bins are in very good agreement with the ones from SDSS spectroscopic diagnostics. Moreover, a one-to-one comparison between the redshifts, ages, metallicities, and stellar masses derived spectroscopically for SDSS and by MUFFIT for ALHAMBRA reveals good qualitative agreements in all the parameters, hence reinforcing the strengths of multi-filter galaxy data and optimized analysis techniques, like MUFFIT, to conduct reliable stellar population studies.

The ALHAMBRA Survey : Evolution of Galaxy Spectral Segregation

We study the clustering of galaxies as a function of spectral type and redshift in the range

High redshift galaxies in the ALHAMBRA survey - I. Selection method and number counts based on redshift PDFs

0.35 < z < 1.1

The ALHAMBRA survey: Estimation of the clustering signal encoded in the cosmic variance

using data from the Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) survey. The data cover 2.381 deg

A Ks-band-selected catalogue of objects in the ALHAMBRA survey

^2

The ALHAMBRA survey: B-band luminosity function of quiescent and star-forming galaxies at 0.2 ≤ z < 1 by PDF analysis

in 7 fields, after applying a detailed angular selection mask, with accurate photometric redshifts [

The ALHAMBRA survey: 2D analysis of the stellar populations in massive early-type galaxies at z < 0.3

sigma_z < 0.014(1+z)

Evolution of Balmer jump selected galaxies in the ALHAMBRA survey

] down to

High redshift galaxies in the ALHAMBRA survey. II. Strengthening the evidence of bright-end excess in UV luminosity functions at 2.5 < z < 4.5 by PDF analysis

I_{AB} < 24