351 research outputs found
Probabilistic Cross-Identification of Cosmic Events
We discuss a novel approach to identifying cosmic events in separate and
independent observations. In our focus are the true events, such as supernova
explosions, that happen once, hence, whose measurements are not repeatable.
Their classification and analysis have to make the best use of all the
available data. Bayesian hypothesis testing is used to associate streams of
events in space and time. Probabilities are assigned to the matches by studying
their rates of occurrence. A case study of Type Ia supernovae illustrates how
to use lightcurves in the cross-identification process. Constraints from
realistic lightcurves happen to be well-approximated by Gaussians in time,
which makes the matching process very efficient. Model-dependent associations
are computationally more demanding but can further boost our confidence.Comment: 5 pages, 2 figures, accepted to Ap
Catalog Matching with Astrometric Correction and its Application to the Hubble Legacy Archive
Object cross-identification in multiple observations is often complicated by
the uncertainties in their astrometric calibration. Due to the lack of standard
reference objects, an image with a small field of view can have significantly
larger errors in its absolute positioning than the relative precision of the
detected sources within. We present a new general solution for the relative
astrometry that quickly refines the World Coordinate System of overlapping
fields. The efficiency is obtained through the use of infinitesimal 3-D
rotations on the celestial sphere, which do not involve trigonometric
functions. They also enable an analytic solution to an important step in making
the astrometric corrections. In cases with many overlapping images, the correct
identification of detections that match together across different images is
difficult to determine. We describe a new greedy Bayesian approach for
selecting the best object matches across a large number of overlapping images.
The methods are developed and demonstrated on the Hubble Legacy Archive, one of
the most challenging data sets today. We describe a novel catalog compiled from
many Hubble Space Telescope observations, where the detections are combined
into a searchable collection of matches that link the individual detections.
The matches provide descriptions of astronomical objects involving multiple
wavelengths and epochs. High relative positional accuracy of objects is
achieved across the Hubble images, often sub-pixel precision in the order of
just a few milli-arcseconds. The result is a reliable set of high-quality
associations that are publicly available online.Comment: 9 pages, 9 figures, accepted for publication in the Astrophysical
Journa
A Unified Framework for Photometric Redshifts
We present a rigorous mathematical solution to photometric redshift
estimation and the more general inversion problem. The challenge we address is
to meaningfully constrain unknown properties of astronomical sources based on
given observables, usually multicolor photometry, with the help of a training
set that provides an empirical relation between the measurements and the
desired quantities. We establish a formalism that blurs the boundary between
the traditional empirical and template-fitting algorithms, as both are just
special cases that are discussed in detail to put them in context. The new
approach enables the development of more sophisticated methods that go beyond
the classic techniques to combine their advantages. We look at the directions
for further improvement in the methodology, and examine the technical aspects
of practical implementations. We show how training sets are to be constructed
and used consistently for reliable estimation.Comment: 9 pages, 2 figures, accepted to the Ap
Cross-Identification Performance from Simulated Detections: GALEX and SDSS
We investigate the quality of associations of astronomical sources from
multi-wavelength observations using simulated detections that are realistic in
terms of their astrometric accuracy, small-scale clustering properties and
selection functions. We present a general method to build such mock catalogs
for studying associations, and compare the statistics of cross-identifications
based on angular separation and Bayesian probability criteria. In particular,
we focus on the highly relevant problem of cross-correlating the ultraviolet
Galaxy Evolution Explorer (GALEX) and optical Sloan Digital Sky Survey (SDSS)
surveys. Using refined simulations of the relevant catalogs, we find that the
probability thresholds yield lower contamination of false associations, and are
more efficient than angular separation. Our study presents a set of recommended
criteria to construct reliable cross-match catalogs between SDSS and GALEX with
minimal artifacts.Comment: 7 pages, 9 figures; ApJ in pres
Cross-Identification of Stars with Unknown Proper Motions
The cross-identification of sources in separate catalogs is one of the most
basic tasks in observational astronomy. It is, however, surprisingly difficult
and generally ill-defined. Recently Budav\'ari & Szalay (2008) formulated the
problem in the realm of probability theory, and laid down the statistical
foundations of an extensible methodology. In this paper, we apply their
Bayesian approach to stars that, we know, can move measurably on the sky, with
detectable proper motion, and show how to associate their observations. We
study models on a sample of stars in the Sloan Digital Sky Survey, which allow
for an unknown proper motion per object, and demonstrate the improvements over
the analytic static model. Our models and conclusions are directly applicable
to upcoming surveys such as PanSTARRS, the Dark Energy Survey, Sky Mapper, and
the LSST, whose data sets will contain hundreds of millions of stars observed
multiple times over several years.Comment: 10 pages, 5 figure
More than just halo mass: Modelling how the red galaxy fraction depends on multiscale density in a HOD framework
The fraction of galaxies with red colours depends sensitively on environment,
and on the way in which environment is measured. To distinguish competing
theories for the quenching of star formation, a robust and complete description
of environment is required, to be applied to a large sample of galaxies. The
environment of galaxies can be described using the density field of neighbours
on multiple scales - the multiscale density field. We are using the Millennium
simulation and a simple HOD prescription which describes the multiscale density
field of Sloan Digital Sky Survey DR7 galaxies to investigate the dependence of
the fraction of red galaxies on the environment. Using a volume limited sample
where we have sufficient galaxies in narrow density bins, we have more dynamic
range in halo mass and density for satellite galaxies than for central
galaxies. Therefore we model the red fraction of central galaxies as a constant
while we use a functional form to describe the red fraction of satellites as a
function of halo mass which allows us to distinguish a sharp from a gradual
transition. While it is clear that the data can only be explained by a gradual
transition, an analysis of the multiscale density field on different scales
suggests that colour segregation within the haloes is needed to explain the
results. We also rule out a sharp transition for central galaxies, within the
halo mass range sampled.Comment: 24 pages, 21 figures, accepted for publication by MNRA
Reliable Eigenspectra for New Generation Surveys
We present a novel technique to overcome the limitations of the applicability
of Principal Component Analysis to typical real-life data sets, especially
astronomical spectra. Our new approach addresses the issues of outliers,
missing information, large number of dimensions and the vast amount of data by
combining elements of robust statistics and recursive algorithms that provide
improved eigensystem estimates step-by-step. We develop a generic mechanism for
deriving reliable eigenspectra without manual data censoring, while utilising
all the information contained in the observations. We demonstrate the power of
the methodology on the attractive collection of the VIMOS VLT Deep Survey
spectra that manifest most of the challenges today, and highlight the
improvements over previous workarounds, as well as the scalability of our
approach to collections with sizes of the Sloan Digital Sky Survey and beyond.Comment: 7 pages, 3 figures, accepted to MNRA
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