885 research outputs found
Search for unusual objects in the WISE Survey
Automatic source detection and classification tools based on machine learning
(ML) algorithms are growing in popularity due to their efficiency when dealing
with large amounts of data simultaneously and their ability to work in
multidimensional parameter spaces. In this work, we present a new, automated
method of outlier selection based on support vector machine (SVM) algorithm
called one-class SVM (OCSVM), which uses the training data as one class to
construct a model of 'normality' in order to recognize novel points. We test
the performance of OCSVM algorithm on \textit{Wide-field Infrared Survey
Explorer (WISE)} data trained on the Sloan Digital Sky Survey (SDSS) sources.
Among others, we find sources with abnormal patterns which can be
associated with obscured and unobscured active galactic nuclei (AGN) source
candidates. We present the preliminary estimation of the clustering properties
of these objects and find that the unobscured AGN candidates are preferentially
found in less massive dark matter haloes () than the
obscured candidates (). This result contradicts the
unification theory of AGN sources and indicates that the obscured and
unobscured phases of AGN activity take place in different evolutionary paths
defined by different environments.Comment: 4 figures, 6 page
The usability of the optical parametric amplification of light for high-angular-resolution imaging and fast astrometry
High-angular-resolution imaging is crucial for many applications in modern
astronomy and astrophysics. The fundamental diffraction limit constrains the
resolving power of both ground-based and spaceborne telescopes. The recent idea
of a quantum telescope based on the optical parametric amplification (OPA) of
light aims to bypass this limit for the imaging of extended sources by an order
of magnitude or more. We present an updated scheme of an OPA-based device and a
more accurate model of the signal amplification by such a device. The
semiclassical model that we present predicts that the noise in such a system
will form so-called light speckles as a result of light interference in the
optical path. Based on this model, we analysed the efficiency of OPA in
increasing the angular resolution of the imaging of extended targets and the
precise localization of a distant point source. According to our new model, OPA
offers a gain in resolved imaging in comparison to classical optics. For a
given time-span, we found that OPA can be more efficient in localizing a single
distant point source than classical telescopes.Comment: Received: 11 November 2017, revision received: 31 January 2018,
accepted: 31 January 201
Beyond the current noise limit in imaging through turbulent medium
Shift-and-add is an approach employed to mitigate the phenomenon of
resolution degradation in images acquired through a turbulent medium. Using
this technique, a large number of consecutive short exposures is registered
below the coherence time of the atmosphere or other blurring medium. The
acquired images are shifted to the position of the brightest speckle and
stacked together to obtain high-resolution and high signal-to-noise frame. In
this paper we present a highly efficient method for determination of frames
shifts, even if in a single frame the object cannot be distinguished from the
background noise. The technique utilizes our custom genetic algorithm, which
iteratively evolves a set of image shifts. We used the maximal energy of
stacked images as an objective function for shifts estimation and validate the
efficiency of the method on simulated and real images of simple and complex
sources. Obtained results confirmed, that our proposed method allows for the
recovery of spatial distribution of objects even only 2% brighter than their
background. The presented approach extends significantly current limits of
image reconstruction with the use of shift-and-add method. The applications of
our algorithm include both the optical and the infrared imaging. Our method may
be also employed as a digital image stabilizer in extremely low light level
conditions in professional and consumer applications.Comment: 8 pages, 4 figure
Quantum Telescopes: feasibility and constrains
Quantum Telescope is a recent idea aimed at beating the diffraction limit of
spaceborne telescopes and possibly also other distant target imaging systems.
There is no agreement yet on the best setup of such devices, but some
configurations have been already proposed. In this Letter we characterize the
predicted performance of Quantum Telescopes and their possible limitations. Our
extensive simulations confirm that the presented model of such instruments is
feasible and the device can provide considerable gains in the angular
resolution of imaging in the UV, optical and infrared bands. We argue that it
is generally possible to construct and manufacture such instruments using the
latest or soon to be available technology. We refer to the latest literature to
discuss the feasibility of the proposed QT system design.Comment: Optics Letters - published after major revisio
Automated novelty detection in the WISE survey with one-class support vector machines
Wide-angle photometric surveys of previously uncharted sky areas or
wavelength regimes will always bring in unexpected sources whose existence and
properties cannot be easily predicted from earlier observations: novelties or
even anomalies. Such objects can be efficiently sought for with novelty
detection algorithms. Here we present an application of such a method, called
one-class support vector machines (OCSVM), to search for anomalous patterns
among sources preselected from the mid-infrared AllWISE catalogue covering the
whole sky. To create a model of expected data we train the algorithm on a set
of objects with spectroscopic identifications from the SDSS DR13 database,
present also in AllWISE. OCSVM detects as anomalous those sources whose
patterns - WISE photometric measurements in this case - are inconsistent with
the model. Among the detected anomalies we find artefacts, such as objects with
spurious photometry due to blending, but most importantly also real sources of
genuine astrophysical interest. Among the latter, OCSVM has identified a sample
of heavily reddened AGN/quasar candidates distributed uniformly over the sky
and in a large part absent from other WISE-based AGN catalogues. It also
allowed us to find a specific group of sources of mixed types, mostly stars and
compact galaxies. By combining the semi-supervised OCSVM algorithm with
standard classification methods it will be possible to improve the latter by
accounting for sources which are not present in the training sample but are
otherwise well-represented in the target set. Anomaly detection adds
flexibility to automated source separation procedures and helps verify the
reliability and representativeness of the training samples. It should be thus
considered as an essential step in supervised classification schemes to ensure
completeness and purity of produced catalogues.Comment: 14 pages, 15 figure
Clustering of Far-Infrared Galaxies in the AKARI All-Sky Survey
We present the first measurement of the angular two-point correlation
function for AKARI 90-m point sources, detected outside of the Milky Way
plane and other regions characterized by high Galactic extinction, and
categorized as extragalactic sources according to our far-infrared-color based
criterion (Pollo et al. 2010). This is the first measurement of the large-scale
angular clustering of galaxies selected in the far-infrared after IRAS
measurements. Although a full description of clustering properties of these
galaxies will be obtained by more detailed studies, using either spatial
correlation function, or better information about properties and at least
photometric redshifts of these galaxies, the angular correlation function
remains the first diagnostics to establish the clustering properties of the
catalog and observed galaxy population. We find a non-zero clustering signal in
both hemispheres extending up to degrees, without any significant
fluctuations at larger scales. The observed correlation function is well fitted
by a power law function. The notable differences between a northern and
southern hemisphere are found, which can be probably attributed to the
photometry problems and point out to a necessity of performing a better
calibration in the data from southern hemisphere.Comment: 6 pages, 6 figures, accepted for publication in Earth, Planets, and
Spac
Machine-learning identification of galaxies in the WISExSuperCOSMOS all-sky catalogue
The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS,
were cross-matched by Bilicki et al. (2016) (B16) to construct a novel
photometric redshift catalogue on 70% of the sky. Galaxies were therein
separated from stars and quasars through colour cuts, which may leave
imperfections because of mixing different source types which overlap in colour
space. The aim of the present work is to identify galaxies in the
WISExSuperCOSMOS catalogue through an alternative approach of machine learning.
This allows us to define more complex separations in the multi-colour space
than possible with simple colour cuts, and should provide more reliable source
classification. For the automatised classification we use the support vector
machines learning algorithm, employing SDSS spectroscopic sources cross-matched
with WISExSuperCOSMOS as the training and verification set. We perform a number
of tests to examine the behaviour of the classifier (completeness, purity and
accuracy) as a function of source apparent magnitude and Galactic latitude. We
then apply the classifier to the full-sky data and analyse the resulting
catalogue of candidate galaxies. We also compare thus produced dataset with the
one presented in B16. The tests indicate very high accuracy, completeness and
purity (>95%) of the classifier at the bright end, deteriorating for the
faintest sources, but still retaining acceptable levels of 85%. No significant
variation of classification quality with Galactic latitude is observed.
Application of the classifier to all-sky WISExSuperCOSMOS data gives 15 million
galaxies after masking problematic areas. The resulting sample is purer than
the one in B16, at a price of lower completeness over the sky. The automatic
classification gives a successful alternative approach to defining a reliable
galaxy sample as compared to colour cuts.Comment: 12 pages, 15 figures, accepted for publication in A&A. Obtained
catalogue will be included in the public release of the WISExSuperCOSMOS
galaxy catalogue available from http://ssa.roe.ac.uk/WISExSCO
Projection and Galaxy Clustering Fourier Spectra
Second order perturbation theory predicts a specific dependence of the
bispectrum, or three-point correlation function in the Fourier transform
domain, on the shape of the configuration of its three wave vector arguments,
which can be taken as a signature of structure formed by gravitational
instability. Comparing this known dependence on configuration shape with the
weak shape dependence of the galaxy bispectrum has been suggested as an
indication of bias in the galaxy distribution. However, to interpret results
obtained from projected catalogs, we must first understand the effects of
projection on this shape dependence. We present expressions for the projected
power spectrum and bispectrum in both Cartesian and spherical geometries, and
we examine the effects of projection on the predicted bispectrum with
particular attention to the dependence on configuration shape. Except for an
overall numerical factor, for Cartesian projection with characteristic depth
\Dstar there is little effect on the shape dependence of the bispectrum for
wavelengths small compared to \Dstar or projected wavenumbers q \Dstar
\gg 1 . For angular projection, a scaling law is found for spherical harmonic
index , but there is always a mixing of scales over the range of
the selection function. For large it is sufficient to examine a small
portion of the sky.Comment: aastex, 7 figure
Radio-Infrared Correlation for Local Dusty Galaxies and Dusty AGNs from the AKARI All Sky Survey
We use the new release of the AKARI Far-Infrared all sky Survey matched with
the NVSS radio database to investigate the local () far infrared-radio
correlation (FIRC) of different types of extragalactic sources. To obtain the
redshift information for the AKARI FIS sources we crossmatch the catalogue with
the SDSS DR8. This also allows us to use emission line properties to divide
sources into four categories: i) star-forming galaxies (SFGs), ii) composite
galaxies (displaying both star-formation and active nucleus components), iii)
Seyfert galaxies, and iv) low-ionization nuclear emission-line region (LINER)
galaxies.
We find that the Seyfert galaxies have the lowest FIR/radio flux ratios and
display excess radio emission when compared to the SFGs. We conclude that FIRC
can be used to separate SFGs and AGNs only for the most radio-loud objects.Comment: 9 pages, accepted to PAS
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