A maximum-likelihood method to improve faint source flux and color estimates
نویسندگان
چکیده
Flux estimates for faint sources or transients are systematically biased high because there are far more truly faint sources than bright. Corrections which account for this effect are presented as a function of signal-to-noise ratio and the (true) slope of the faint-source number-flux relation. The corrections depend on the source being originally identified in the image in which it is being photometered. If a source has been identified in other data, the corrections are different; a prescription for calculating the corrections is presented. Implications of these corrections for analyses of surveys are discussed; the most important is that sources identified at signal-to-noise ratios of three or less are practically useless.
منابع مشابه
Multiwavelength characterization of faint ultra steep spectrum radio sources: A search for high-redshift radio galaxies ⋆
Context. Ultra steep spectrum (USS) radio sources are one of the efficient tracers of powerful high-z radio galaxies (HzRGs). In contrast to searches for powerful HzRGs from radio surveys of moderate depths, fainter USS samples derived from deeper radio surveys can be useful in finding HzRGs at even higher redshifts and in unveiling a population of obscured weaker radio-loud AGN at moderate red...
متن کاملDASTWAR: a tool for completeness estimation in magnitude-size plane
Today, great observatories around the world, devote a substantial amount of observing time to sky surveys. The resulted images are inputs of source finder modules. These modules search for the target objects and provide us with source catalogues. We sought to quantify the ability of detection tools in recovering faint galaxies regularly encountered in deep surveys. Our approach was based on com...
متن کاملComparison of Maximum Likelihood Estimation and Bayesian with Generalized Gibbs Sampling for Ordinal Regression Analysis of Ovarian Hyperstimulation Syndrome
Background and Objectives: Analysis of ordinal data outcomes could lead to bias estimates and large variance in sparse one. The objective of this study is to compare parameter estimates of an ordinal regression model under maximum likelihood and Bayesian framework with generalized Gibbs sampling. The models were used to analyze ovarian hyperstimulation syndrome data. Methods: This study use...
متن کاملStatistical constraints on the IR galaxy number counts and cosmic IR background from the Spitzer GOODS survey
We perform fluctuation analyses on the data from the Spitzer GOODS survey (epoch one) in the Hubble Deep Field North (HDF-N). We fit a parameterised power-law number count model of the form dN dS = NoS −δ to data from each of the four Spitzer IRAC bands (3.6, 4.5, 5.8, 8 microns), using Markov Chain Monte Carlo (MCMC) sampling to explore the posterior probability distribution in each case. From...
متن کاملA Comprehensive Maximum Likelihood Analysis of the Structural Properties of Faint Milky Way Satellites
We derive the structural parameters of the recently discovered very low luminosity Milky Way satellites through a Maximum Likelihood algorithm applied to SDSS data. For each satellite, even when only a few tens of stars are available down to the SDSS flux limit, the algorithm yields robust estimates and errors for the centroid, position angle, ellipticity, exponential half-light radius and numb...
متن کامل