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Variability Search Toolkit (VaST) is a software package designed to find variable objects in a series of sky images. It can be run from a script or interactively using its graphical interface. VaST relies on source list matching as opposed to image subtraction. SExtractor is used to generate source lists and perform aperture or PSF-fitting photometry (with PSFEx). Variability indices that characterize scatter and smoothness of a lightcurve are computed for all objects. Candidate variables are identified as objects having high variability index values compared to other objects of similar brightness. The two distinguishing features of VaST are its ability to perform accurate aperture photometry of images obtained with non-linear detectors and handle complex image distortions. The software has been successfully applied to images obtained with telescopes ranging from 0.08 to 2.5m in diameter equipped with a variety of detectors including CCD, CMOS, MIC and photographic plates. About 1800 variable stars have been discovered with VaST. It is used as a transient detection engine in the New Milky Way (NMW) nova patrol. The code is written in C and can be easily compiled on the majority of UNIX-like systems. VaST is free software available at http://scan.sai.msu.ru/vast/
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The Australian Square Kilometre Array Pathfinder (ASKAP) will give us an unprecedented opportunity to investigate the transient sky at radio wavelengths. In this paper we present VAST, an ASKAP survey for Variables and Slow Transients. VAST will exploit the wide-field survey capabilities of ASKAP to enable the discovery and investigation of variable and transient phenomena from the local to the cosmological, including flare stars, intermittent pulsars, X-ray binaries, magnetars, extreme scattering events, interstellar scintillation, radio supernovae and orphan afterglows of gamma ray bursts. In addition, it will allow us to probe unexplored regions of parameter space where new classes of transient sources may be detected. In this paper we review the known radio transient and variable populations and the current results from blind radio surveys. We outline a comprehensive program based on a multi-tiered survey strategy to characterise the radio transient sky through detection and monitoring of transient and variable sources on the ASKAP imaging timescales of five seconds and greater. We also present an analysis of the expected source populations that we will be able to detect with VAST.
We present a photometric $J$-band variability study of GU Psc b, a T3.5 co-moving planetary-mass companion (9-13$M_{rm{Jup}}$) to a young ($sim$150 Myr) M3 member of the AB Doradus Moving Group. The large separation between GU Psc b and its host star (42) provides a rare opportunity to study the photometric variability of a planetary-mass companion. The study presented here is based on observations obtained from 2013 to 2014 over three nights with durations of 5-6 hr each with the WIRCam imager at Canada-France-Hawaii Telescope. Photometric variability with a peak-to-peak amplitude of $4pm1$% at a timescale of $sim$6 hr was marginally detected on 2014 October 11. No high-significance variability was detected on 2013 December 22 and 2014 October 10. The amplitude and timescale of the variability seen here, as well as its evolving nature, is comparable to what was observed for a variety of field T dwarfs and suggests that mechanisms invoked to explain brown dwarf variability may be applicable to low-gravity objects such as GU Psc b. Rotation-induced photometric variability due to the formation and dissipation of atmospheric features such as clouds is a plausible hypothesis for the tentative variation detected here. Additional photometric measurements, particularly on longer timescales, will be required to confirm and characterize the variability of GU Psc b, determine its periodicity and to potentially measure its rotation period.
The Australian Square Kilometre Array Pathfinder (ASKAP) collects images of the sky at radio wavelengths with an unprecedented field of view, combined with a high angular resolution and sub-millijansky sensitivities. The large quantity of data produced is used by the ASKAP Variables and Slow Transients (VAST) survey science project to study the dynamic radio sky. Efficient pipelines are vital in such research, where searches often form a `needle in a haystack type of problem to solve. However, the existing pipelines developed among the radio-transient community are not suitable for the scale of ASKAP datasets. In this paper we provide a technical overview of the new VAST Pipeline: a modern and scalable Python-based data pipeline for transient searches, using up-to-date dependencies and methods. The pipeline allows source association to be performed at scale using the Pandas DataFrame interface and the well-known Astropy crossmatch functions. The Dask Python framework is used to parallelise operations as well as scale them both vertically and horizontally, by means of a cluster of workers. A modern web interface for data exploration and querying has also been developed using the latest Django web framework combined with Bootstrap.
HiPERCAM is a high-speed camera for the study of rapid variability in the Universe. The project is funded by a 3.5MEuro European Research Council Advanced Grant. HiPERCAM builds on the success of our previous instrument, ULTRACAM, with very significant improvements in performance thanks to the use of the latest technologies. HiPERCAM will use 4 dichroic beamsplitters to image simultaneously in 5 optical channels covering the ugriz bands. Frame rates of over 1000 per second will be achievable using an ESO CCD controller (NGC), with every frame GPS timestamped. The detectors are custom-made, frame-transfer CCDs from e2v, with 4 low-noise (2.5e-) outputs, mounted in small thermoelectrically-cooled heads operated at 180 K, resulting in virtually no dark current. The two reddest CCDs will be deep-depletion devices with anti-etaloning, providing high quantum efficiencies across the red part of the spectrum with no fringing. The instrument will also incorporate scintillation noise correction via the conjugate-plane photometry technique. The opto-mechanical chassis will make use of additive manufacturing techniques in metal to make a light-weight, rigid and temperature-invariant structure. First light is expected on the 4.2m William Herschel Telescope on La Palma in 2017 (on which the field of view will be 10 with a 0.3/pixel scale), with subsequent use planned on the 10.4m Gran Telescopio Canarias on La Palma (on which the field of view will be 4 with a 0.11/pixel scale) and the 3.5m New Technology Telescope in Chile.
By now, tens of gravitational-wave (GW) events have been detected by the LIGO and Virgo detectors. These GWs have all been emitted by compact binary coalescence, for which we have excellent predictive models. However, there might be other sources for which we do not have reliable models. Some are expected to exist but to be very rare (e.g., supernovae), while others may be totally unanticipated. So far, no unmodeled sources have been discovered, but the lack of models makes the search for such sources much more difficult and less sensitive. We present here a search for unmodeled GW signals using semi-supervised machine learning. We apply deep learning and outlier detection algorithms to labeled spectrograms of GW strain data, and then search for spectrograms with anomalous patterns in public LIGO data. We searched $sim 13%$ of the coincident data from the first two observing runs. No candidates of GW signals were detected in the data analyzed. We evaluate the sensitivity of the search using simulated signals, we show that this search can detect spectrograms containing unusual or unexpected GW patterns, and we report the waveforms and amplitudes for which a $50%$ detection rate is achieved.
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