arXiv subjects

Andrew J. Drake

Publications and source records attributed to Andrew J. Drake.

59 records · Page 4Linked to original sources

arXiv2013

Machine-assisted discovery of relationships in astronomy

High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focussing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the fundamental plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as LSST. We find that comparable results to more familiar techniques, such as decision trees, are achievable. Finally, we consider the reality of the relationships discovered and how this can be used for feature selection and extraction.

astro-ph.IM↗

arXiv2012

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.

astro-ph.IM↗

arXiv2011

Optical discovery of probable stellar tidal disruption flares

Using archival SDSS multi-epoch imaging data (Stripe 82), we have searched for the tidal disruption of stars by super-massive black holes in non-active galaxies. Two candidate tidal disruption events (TDEs) are identified. They have optical black-body temperatures 2 10^4 K and observed peak luminosities M_g=-18.3 and -20.4; their cooling rates are very low, qualitatively consistent with expectations for tidal disruption flares. Their properties are examined using i) SDSS imaging to compare them to other flares observed in the search, ii) UV emission measured by GALEX and iii) spectra of the hosts and of one of the flares. Our pipeline excludes optically identifiable AGN hosts, and our variability monitoring over 9 years provides strong evidence that these are not flares in hidden AGNs. The spectra and color evolution of the flares are unlike any SN observed to date, their strong late-time UV emission is particularly distinctive, and they are nuclear at high resolution, arguing against their being first cases of a previously-unobserved class of SNe or more extreme examples of known SN types. Taken together, the observed properties are difficult to reconcile with a SN or AGN-flare explanation, although an entirely new process specific to the inner few-hundred parsecs of non-active galaxies cannot be excluded. Our observed rate and method show the feasibility of obtaining a candidate TDE sample of hundreds of events and O(1) purity, using geometric resolution and host and flare color alone. A by-product of this work is quantification of the power-spectrum of extreme flares in AGNs.

astro-ph.CO↗

arXiv2009

Data Mining for Dwarf Novae in SDSS, GALEX and Astrometric Catalogues

By cross matching blue objects from SDSS with GALEX and the astrometric catalogues USNO-B1.0, GSC2.3 and CMC14, 64 new dwarf nova candidates with one or more observed outbursts have been identified. 14 of these systems are confirmed as cataclysmic variables through existing and follow-up spectroscopy. A study of the amplitude distribution and an estimate of the outburst frequency of these new dwarf novae and those discovered by the Catalina Real-time Transient Survey (CRTS) indicates that besides systems that are faint because they are farther away, there also exists a population of intrinsically faint dwarf novae with rare outbursts.

astro-ph.SR↗

arXiv2009

Exploring the Optical Transient Sky with the Palomar Transient Factory

The Palomar Transient Factory (PTF) is a wide-field experiment designed to investigate the optical transient and variable sky on time scales from minutes to years. PTF uses the CFH12k mosaic camera, with a field of view of 7.9 deg^2 and a plate scale of 1 asec/pixel, mounted on the the Palomar Observatory 48-inch Samuel Oschin Telescope. The PTF operation strategy is devised to probe the existing gaps in the transient phase space and to search for theoretically predicted, but not yet detected, phenomena, such as fallback supernovae, macronovae, .Ia supernovae and the orphan afterglows of gamma-ray bursts. PTF will also discover many new members of known source classes, from cataclysmic variables in their various avatars to supernovae and active galactic nuclei, and will provide important insights into understanding galactic dynamics (through RR Lyrae stars) and the Solar system (asteroids and near-Earth objects). The lessons that can be learned from PTF will be essential for the preparation of future large synoptic sky surveys like the Large Synoptic Survey Telescope. In this paper we present the scientific motivation for PTF and describe in detail the goals and expectations for this experiment.

astro-ph.CO↗