arXiv subjects

L. Sodre

Publications and source records attributed to L. Sodre.

6 recordsLinked to original sources

arXiv2021

The Fornax Cluster through S-PLUS

The Southern Photometric Local Universe Survey (S-PLUS) aims to map $\approx$ 9300 deg$^2$ of the Southern sky using the Javalambre filter system of 12 optical bands, 5 Sloan-like filters and 7 narrow-band filters centered on several prominent stellar features ([OII], Ca H+K, D4000, H$_δ$, Mgb, H$_α$ and CaT). S-PLUS is carried out with the T80-South, a new robotic 0.826-m telescope located on CTIO, equipped with a wide FoV camera (2 deg$^2$). In this poster we introduce project #59 of the S-PLUS collaboration aimed at studying the Fornax galaxy cluster covering an sky area of $\approx$ 11 $\times$ 7 deg$^2$, and with homogeneous photometry in the 12 optical bands of S-PLUS (Coordinator: A. Smith Castelli).

astro-ph.GA↗

arXiv2014

J-PAS: The Javalambre-Physics of the Accelerated Universe Astrophysical Survey

The Javalambre-Physics of the Accelerated Universe Astrophysical Survey (J-PAS) is a narrow band, very wide field Cosmological Survey to be carried out from the Javalambre Observatory in Spain with a purpose-built, dedicated 2.5m telescope and a 4.7 sq.deg. camera with 1.2Gpix. Starting in late 2015, J-PAS will observe 8500sq.deg. of Northern Sky and measure $0.003(1+z)$ photo-z for $9\times10^7$ LRG and ELG galaxies plus several million QSOs, sampling an effective volume of $\sim 14$ Gpc$^3$ up to $z=1.3$ and becoming the first radial BAO experiment to reach Stage IV. J-PAS will detect $7\times 10^5$ galaxy clusters and groups, setting constrains on Dark Energy which rival those obtained from its BAO measurements. Thanks to the superb characteristics of the site (seeing ~0.7 arcsec), J-PAS is expected to obtain a deep, sub-arcsec image of the Northern sky, which combined with its unique photo-z precision will produce one of the most powerful cosmological lensing surveys before the arrival of Euclid. J-PAS unprecedented spectral time domain information will enable a self-contained SN survey that, without the need for external spectroscopic follow-up, will detect, classify and measure $σ_z\sim 0.5\%$ redshifts for $\sim 4000$ SNeIa and $\sim 900$ core-collapse SNe. The key to the J-PAS potential is its innovative approach: a contiguous system of 54 filters with $145Å$ width, placed $100Å$ apart over a multi-degree FoV is a powerful "redshift machine", with the survey speed of a 4000 multiplexing low resolution spectrograph, but many times cheaper and much faster to build. The J-PAS camera is equivalent to a 4.7 sq.deg. "IFU" and it will produce a time-resolved, 3D image of the Northern Sky with a very wide range of Astrophysical applications in Galaxy Evolution, the nearby Universe and the study of resolved stellar populations.

astro-ph.CO↗

arXiv2009

Signature of the interaction between dark energy and dark matter in galaxy clusters

We investigate the influence of an interaction between dark energy and dark matter upon the dynamics of galaxy clusters. We obtain the general Layser-Irvine equation in the presence of interactions, and find how, in that case, the virial theorem stands corrected. Using optical, X-ray and weak lensing data from 33 relaxed galaxy clusters, we put constraints on the strength of the coupling in the dark sector. We find that this coupling is small but positive, indicating that dark energy can be decaying into dark matter.

astro-ph↗

arXiv2008

The Star Formation Histories of galaxies: A tour through the STARLIGHT-SDSS database

Retrieving the Star Formation History (SFH) of a galaxy out of its integrated spectrum is the central goal of stellar population synthesis. Recent advances in evolutionary synthesis models have given new breath to this old field of research. Modern spectral synthesis techniques incorporating these advances now allow the fitting of galaxy spectra on an angstrom-by-angstrom basis. These detailed fits are useful for a number of studies, like emission line, stellar kinematics, and specially galaxy evolution. Applications of this semi-empirical approach to mega data sets are teaching us a lot about the lives of galaxies. The STARLIGHT spectral synthesis code is one of the tools which allows one to harness this favorable combination of plentifulness of data and models. To illustrate this, we show how SFHs vary across classical emission line diagnostic diagrams. Systematic trends are present along both the star-forming and active-galaxy sequences. We also briefly describe experiments with new versions of evolutionary synthesis models. Last but not least, we announce the public availability of both STARLIGHT and a database of detailed spectral fits and related products for over half a million galaxies from the SDSS. This facility allows more physically inspired explorations of the parameter space than is possible in terms of raw observed properties, offering new ways to navigate through the realm of galaxies.

astro-ph↗

arXiv2004

Semi-empirical analysis of SDSS galaxies: I. Spectral synthesis method

In this paper we investigate the power of spectral synthesis as a mean to estimate physical properties of galaxies. Spectral synthesis is nothing more than the decomposition of an observed spectrum in terms of a superposition of a base of simple stellar populations of various ages and metallicities, producing as output the star-formation and chemical histories of a galaxy, its extinction and velocity dispersion. Our implementation of this method uses the Bruzual & Charlot (2003) models and observed spectra in the 3650--8000 Årange. The reliability of this approach is studied by three different means: (1) simulations, (2) comparison with previous work based on a different technique, and (3) analysis of the consistency of results obtained for a sample of galaxies from the SDSS. We find that spectral synthesis provides reliable physical parameters as long as one does not attempt a very detailed description of the star-formation and chemical histories. We show that besides providing excellent fits to observed galaxy spectra, this method is able to recover useful information on the distributions of stellar ages and, more importantly, stellar metallicities. Stellar masses, velocity dispersion and extinction are also found to be accurately retrieved for realistic signal-to-noise ratios. We apply this synthesis method to a volume limited sample of 50362 galaxies from the SDSS DR2, producing a catalog of stellar population properties. A comparison with recent estimates of both observed and physical properties of these galaxies obtained by other groups shows good qualitative and quantitative agreement. The confidence in the method is further strengthened by several empirical and astrophysically reasonable correlations between synthesis results and independent quantities.

astro-ph↗

arXiv1995

Neural computation as a tool for galaxy classification : methods and examples

We apply and compare various Artificial Neural Network (ANN) and other algorithms for automatic morphological classification of galaxies. The ANNs are presented here mathematically, as non-linear extensions of conventional statistical methods in Astronomy. The methods are illustrated using different subsets Artificial Neural Network (ANN) and other algorithms for automatic morphological classification of galaxies. The ANNs are presented here mathematically, as non-linear extensions of conventional statistical methods in Astronomy. The methods are illustrated using different subsets from the ESO-LV catalogue, for which both machine parameters and human classification are available. The main methods we explore are: (i) Principal Component Analysis (PCA) which tells how independent and informative the input parameters are. (ii) Encoder Neural Network which allows us to find both linear (PCA-like) and non-linear combinations of the input, illustrating an example of unsupervised ANN. (iii) Supervised ANN (using the Backpropagation or Quasi-Newton algorithms) based on a training set for which the human classification is known. Here the output for previously unclassified galaxies can be interpreted as either a continuous (analog) output (e.g. $T$-type) or a Bayesian {\it a posteriori} probability for each class. Although the ESO-LV parameters are sub-optimal, the success of the ANN in reproducing the human classification is 2 $T$-type units, similar to the degree of agreement between two human experts who classify the same galaxy images on plate material. We also examine the aspects of ANN configurations, reproducibility, scaling of input parameters and redshift information.

astro-ph↗