Clustering-based Redshift Estimation: Comparison to Spectroscopic Redshifts

We investigate the potential and accuracy of clustering-based redshift estimation using the method proposed by M\'enard et al. (2013). This technique enables the inference of redshift distributions from measurements of the spatial clustering of arbitrary sources, using a set of reference objects for which redshifts are known. We apply it to a sample of spectroscopic galaxies from the Sloan Digital Sky Survey and show that, after carefully controlling the sampling efficiency over the sky, we can estimate redshift distributions with high accuracy. Probing the full colour space of the SDSS galaxies, we show that we can recover the corresponding mean redshifts with an accuracy ranging from $\delta$z=0.001 to 0.01. We indicate that this mapping can be used to infer the redshift probability distribution of a single galaxy. We show how the lack of information on the galaxy bias limits the accuracy of the inference and show comparisons between clustering redshifts and photometric redshifts for this dataset. This analysis demonstrates, using real data, that clustering-based redshift inference provides a powerful data-driven technique to explore the redshift distribution of arbitrary datasets, without any prior knowledge on the spectral energy distribution of the sources.Comment: 13 pages. Submitted to MNRAS. Comments welcom

La dificultad de medir

El análisis de redes se ha popularizado porque ha facilitado abordar relaciones estructurales que otros métodos ignoraban, sin embargo todavía quedan pendientes algunos problemas metodológicos que conviene abordar para buscar explicaciones más complejas, como por ejemplo la generación de índices de centralidad donde se manejen conexiones con peso y atributos diferenciados. En este artículo se apuntan algunas de las problemáticas encontradas en nuestro análisis de la red de poder mexicana para mostrar la centralidad de los actores y la dificultad de generar un índice de poder.Network analysis has popularized because it has facilitated approaching structural relationships which other methods ignored, however, still some methodological problems remain to be solved in the search of more complex explanations, such as the generation of centrality indexes in which connections with weight and attributes. In this article we indicate some of the problems we found in our centrality analysis of the Mexican network of power and the difficulty to generate an index of power

El movimiento de los grupos políticos (cliques) en tres perídos presidenciales en México

En este artículo se analizan los cliques de tres presidentes mexicanos. El clique es una estructura en la que los actores están fuertemente conectados entre si, y sirve para entender la configuración de los grupos, como se mantienen a lo largo del tiempoIn this article we analyze the cliques of three Mexican presidential administrations. A clique is a structure where actors are strongly connected among themselves and it helps understand the configuration of groups, how they are maintained over time and

Cosmic shear results from the deep lens survey - I: Joint constraints on omega_m and sigma_8 with a two-dimensional analysis

We present a cosmic shear study from the Deep Lens Survey (DLS), a deep BVRz multi-band imaging survey of five 4 sq. degree fields with two National Optical Astronomy Observatory (NOAO) 4-meter telescopes at Kitt Peak and Cerro Tololo. For both telescopes, the change of the point-spread-function (PSF) shape across the focal plane is complicated, and the exposure-to-exposure variation of this position-dependent PSF change is significant. We overcome this challenge by modeling the PSF separately for individual exposures and CCDs with principal component analysis (PCA). We find that stacking these PSFs reproduces the final PSF pattern on the mosaic image with high fidelity, and the method successfully separates PSF-induced systematics from gravitational lensing effects. We calibrate our shears and estimate the errors, utilizing an image simulator, which generates sheared ground-based galaxy images from deep Hubble Space Telescope archival data with a realistic atmospheric turbulence model. For cosmological parameter constraints, we marginalize over shear calibration error, photometric redshift uncertainty, and the Hubble constant. We use cosmology-dependent covariances for the Markov Chain Monte Carlo analysis and find that the role of this varying covariance is critical in our parameter estimation. Our current non-tomographic analysis alone constrains the Omega_M-sigma_8 likelihood contour tightly, providing a joint constraint of Omega_M=0.262+-0.051 and sigma_8=0.868+-0.071. We expect that a future DLS weak-lensing tomographic study will further tighten these constraints because explicit treatment of the redshift dependence of cosmic shear more efficiently breaks the Omega_M-sigma_8 degeneracy. Combining the current results with the Wilkinson Microwave Anisotropy Probe 7-year (WMAP7) likelihood data, we obtain Omega_M=0.278+-0.018 and sigma_8=0.815+-0.020.Comment: Accepted to ApJ. Replaced with the accepted versio