Tests of Statistical Methods for Estimating Galaxy Luminosity Function and Applications to the Hubble Deep Field

We studied the statistical methods for the estimation of the luminosity function (LF) of galaxies. We focused on four nonparametric estimators: $1/V_{\rm max}$ estimator, maximum-likelihood estimator of Efstathiou et al. (1988), Cho{\l}oniewski's estimator, and improved Lynden-Bell's estimator. The performance of the $1/V_{\rm max}$ estimator has been recently questioned, especially for the faint-end estimation of the LF. We improved these estimators for the studies of the distant Universe, and examined their performances for various classes of functional forms by Monte Carlo simulations. We also applied these estimation methods to the mock 2dF redshift survey catalog prepared by Cole et al. (1998). We found that $1/V_{\rm max}$ estimator yields a completely unbiased result if there is no inhomogeneity, but is not robust against clusters or voids. This is consistent with the well-known results, and we did not confirm the bias trend of $1/V_{\rm max}$ estimator claimed by Willmer (1997) in the case of homogeneous sample. We also found that the other three maximum-likelihood type estimators are quite robust and give consistent results with each other. In practice we recommend Cho{\l}oniewski's estimator for two reasons: 1. it simultaneously provides the shape and normalization of the LF; 2. it is the fastest among these four estimators, because of the algorithmic simplicity. Then, we analyzed the photometric redshift data of the Hubble Deep Field prepared by Fern\'{a}ndez-Soto et al. (1999) using the above four methods. We also derived luminosity density $\rho_{\rm L}$ at $B$- and $I$-band. Our $B$-band estimation is roughly consistent with that of Sawicki, Lin, & Yee (1997), but a few times lower at $2.0 < z < 3.0$. The evolution of $\rho_{\rm L}(I)$ is found to be less prominent.Comment: To appear in ApJS July 2000 issue. 36 page

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

Changes in the characteristics and skills of British youth

Changes in the characteristics and skills of British youths between the mid-1980s and mid-2000s are evaluated using a method recently developed by Altonji et al. The main finding is that skills have increased over time in successive cohorts of young people. The improvement is, however, uneven, and those at the bottom end of the skills distribution have benefitted less than others. This implies, other things being equal, that the distribution of earnings will widen over the coming years