150 research outputs found
Data Driven Discovery in Astrophysics
We review some aspects of the current state of data-intensive astronomy, its
methods, and some outstanding data analysis challenges. Astronomy is at the
forefront of "big data" science, with exponentially growing data volumes and
data rates, and an ever-increasing complexity, now entering the Petascale
regime. Telescopes and observatories from both ground and space, covering a
full range of wavelengths, feed the data via processing pipelines into
dedicated archives, where they can be accessed for scientific analysis. Most of
the large archives are connected through the Virtual Observatory framework,
that provides interoperability standards and services, and effectively
constitutes a global data grid of astronomy. Making discoveries in this
overabundance of data requires applications of novel, machine learning tools.
We describe some of the recent examples of such applications.Comment: Keynote talk in the proceedings of ESA-ESRIN Conference: Big Data
from Space 2014, Frascati, Italy, November 12-14, 2014, 8 pages, 2 figure
Exploring the Time Domain With Synoptic Sky Surveys
Synoptic sky surveys are becoming the largest data generators in astronomy,
and they are opening a new research frontier, that touches essentially every
field of astronomy. Opening of the time domain to a systematic exploration will
strengthen our understanding of a number of interesting known phenomena, and
may lead to the discoveries of as yet unknown ones. We describe some lessons
learned over the past decade, and offer some ideas that may guide strategic
considerations in planning and execution of the future synoptic sky surveys.Comment: Invited talk, to appear in proc. IAU SYmp. 285, "New Horizons in Time
Domain Astronomy", eds. E. Griffin et al., Cambridge Univ. Press (2012).
Latex file, 6 pages, style files include
Some Pattern Recognition Challenges in Data-Intensive Astronomy
We review some of the recent developments and challenges posed by the data
analysis in modern digital sky surveys, which are representative of the
information-rich astronomy in the context of Virtual Observatory. Illustrative
examples include the problems of an automated star-galaxy classification in
complex and heterogeneous panoramic imaging data sets, and an automated,
iterative, dynamical classification of transient events detected in synoptic
sky surveys. These problems offer good opportunities for productive
collaborations between astronomers and applied computer scientists and
statisticians, and are representative of the kind of challenges now present in
all data-intensive fields. We discuss briefly some emergent types of scalable
scientific data analysis systems with a broad applicability.Comment: 8 pages, compressed pdf file, figures downgraded in quality in order
to match the arXiv size limi
Astrophysics in S.Co.P.E
S.Co.P.E. is one of the four projects funded by the Italian Government in
order to provide Southern Italy with a distributed computing infrastructure for
fundamental science. Beside being aimed at building the infrastructure,
S.Co.P.E. is also actively pursuing research in several areas among which
astrophysics and observational cosmology. We shortly summarize the most
significant results obtained in the first two years of the project and related
to the development of middleware and Data Mining tools for the Virtual
Observatory
An analysis of feature relevance in the classification of astronomical transients with machine learning methods
The exploitation of present and future synoptic (multi-band and multi-epoch)
surveys requires an extensive use of automatic methods for data processing and
data interpretation. In this work, using data extracted from the Catalina Real
Time Transient Survey (CRTS), we investigate the classification performance of
some well tested methods: Random Forest, MLPQNA (Multi Layer Perceptron with
Quasi Newton Algorithm) and K-Nearest Neighbors, paying special attention to
the feature selection phase. In order to do so, several classification
experiments were performed. Namely: identification of cataclysmic variables,
separation between galactic and extra-galactic objects and identification of
supernovae.Comment: Accepted by MNRAS, 11 figures, 18 page
Connecting the time domain community with the Virtual Astronomical Observatory
The time domain has been identified as one of the most important areas of
astronomical research for the next decade. The Virtual Observatory is in the
vanguard with dedicated tools and services that enable and facilitate the
discovery, dissemination and analysis of time domain data. These range in scope
from rapid notifications of time-critical astronomical transients to annotating
long-term variables with the latest modeling results. In this paper, we will
review the prior art in these areas and focus on the capabilities that the VAO
is bringing to bear in support of time domain science. In particular, we will
focus on the issues involved with the heterogeneous collections of (ancillary)
data associated with astronomical transients, and the time series
characterization and classification tools required by the next generation of
sky surveys, such as LSST and SKA.Comment: Submitted to Proceedings of SPIE Observatory Operations: Strategies,
Processes and Systems IV, Amsterdam, 2012 July 2-
A systematic search for close supermassive black hole binaries in the Catalina Real-Time Transient Survey
Hierarchical assembly models predict a population of supermassive black hole
(SMBH) binaries. These are not resolvable by direct imaging but may be
detectable via periodic variability (or nanohertz frequency gravitational
waves). Following our detection of a 5.2 year periodic signal in the quasar PG
1302-102 (Graham et al. 2015), we present a novel analysis of the optical
variability of 243,500 known spectroscopically confirmed quasars using data
from the Catalina Real-time Transient Survey (CRTS) to look for close (< 0.1
pc) SMBH systems. Looking for a strong Keplerian periodic signal with at least
1.5 cycles over a baseline of nine years, we find a sample of 111 candidate
objects. This is in conservative agreement with theoretical predictions from
models of binary SMBH populations. Simulated data sets, assuming stochastic
variability, also produce no equivalent candidates implying a low likelihood of
spurious detections. The periodicity seen is likely attributable to either jet
precession, warped accretion disks or periodic accretion associated with a
close SMBH binary system. We also consider how other SMBH binary candidates in
the literature appear in CRTS data and show that none of these are equivalent
to the identified objects. Finally, the distribution of objects found is
consistent with that expected from a gravitational wave-driven population. This
implies that circumbinary gas is present at small orbital radii and is being
perturbed by the black holes. None of the sources is expected to merge within
at least the next century. This study opens a new unique window to study a
population of close SMBH binaries that must exist according to our current
understanding of galaxy and SMBH evolution.Comment: 29 pages, 10 figures, accepted for publication in MNRAS - this
version contains extended table and figur
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