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Register a new userTowards a BRICS Optical Transient Network (BRICS-OTN)
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David A.H. Buckley
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This paper is based on a proposal submitted for a BRICS astronomy flagship program, which was presented at the 2019 meeting of the BRICS Astronomy Working Group, held in Rio de Janeiro from 29 September to 2 October 2019. The future prospects for the detection and study of transient phenomena in the Universe heralds a new era in time domain astronomy. The case is presented for a dedicated BRICS-wide flagship program to develop a network of ground-based optical telescopes for an all-sky survey to detect short lived optical transients and to allow follow-up of multi-wavelength and multi-messenger transient objects. This will leverage existing and planned new facilities within the BRICS countries and will also draw on the opportunities presented by other multi-wavelength space- and ground-based facilities that exist within the BRICS group. The proposed optical network would initially perform followup observations on new transients using existing telescopes. This would later expand to include a new global network of $sim$70 wide-field 1-m telescopes which will cover the entire sky, simultaneously, with a cadence of less than a few hours. This realization would represent a ground-breaking and unique global capability, presenting many scientific opportunities and associated spin-off benefits to all BRICS countries.
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The almost universal availability of electronic connectivity, portable devices, and the web is bringing about a major revolution: information of all kinds is rapidly becoming accessible to everyone, transforming social, economic and cultural life practically everywhere in the world. Internet technologies represent an unprecedented and extraordinary two-way channel of communication between producers and users of data. Open Universe is an initiative proposed to the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) and currently in implementation under the leadership of the United Nations Office for Outer Space Affairs (UN-OOSA). Its primary objective is to stimulate a dramatic increase in the availability and usability of space science data, extending the potential of scientific discovery to new participants in all parts of the world. This paper describes the initiative in general, some of the activities carried out to demonstrate its feasibility, and its use in the context of the BRICS Astronomy Programme.
The observation of the transient sky through a multitude of astrophysical messengers hasled to several scientific breakthroughs these last two decades thanks to the fast evolution ofthe observational techniques and strategies employed by the astronomers. Now, it requiresto be able to coordinate multi-wavelength and multi-messenger follow-up campaign withinstruments both in space and on ground jointly capable of scanning a large fraction of thesky with a high imaging cadency and duty cycle. In the optical domain, the key challengeof the wide field of view telescopes covering tens to hundreds of square degrees is to dealwith the detection, the identification and the classification of hundreds to thousands of opticaltransient (OT) candidates every night in a reasonable amount of time. In the last decade, newautomated tools based on machine learning approaches have been developed to perform thosetasks with a low computing time and a high classification efficiency. In this paper, we presentan efficient classification method using Convolutional Neural Networks (CNN) to discard anybogus falsely detected in astrophysical images in the optical domain. We designed this toolto improve the performances of the OT detection pipeline of the Ground Wide field AngleCameras (GWAC) telescopes, a network of robotic telescopes aiming at monitoring the opticaltransient sky down to R=16 with a 15 seconds imaging cadency. We applied our trainedCNN classifier on a sample of 1472 GWAC OT candidates detected by the real-time detectionpipeline. It yields a good classification performance with 94% of well classified event and afalse positive rate of 4%.
We obtain analytical approximations for the expectation and variance of the Spectral Kurtosis estimator in the case of Gaussian and coherent transient time domain signals mixed with a quasi-stationary Gaussian background, which are suitable for practical estimations of their signal-to-noise ratio and duty-cycle relative to the instrumental integration time. We validate these analytical approximations by means of numerical simulations and demonstrate that such estimates are affected by statistical uncertainties that, for a suitable choice of the integration time, may not exceed a few percent. Based on these analytical results, we suggest a multiscale Spectral Kurtosis spectrometer design optimized for real-time detection of transient signals, automatic discrimination based on their statistical signature, and measurement of their properties.
We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of 3 stages: feature extraction, search of outliers with machine learning algorithms and anomaly identification with followup by human experts. Our analysis concentrates in three ZTF fields, comprising more than 2.25 million objects. A set of 4 automatic learning algorithms was used to identify 277 outliers, which were subsequently scrutinised by an expert. From these, 188 (68%) were found to be bogus light curves -- including effects from the image subtraction pipeline as well as overlapping between a star and a known asteroid, 66 (24%) were previously reported sources whereas 23 (8%) correspond to non-catalogued objects, with the two latter cases of potential scientific interest (e. g. 1 spectroscopically confirmed RS Canum Venaticorum star, 4 supernovae candidates, 1 red dwarf flare). Moreover, using results from the expert analysis, we were able to identify a simple bi-dimensional relation which can be used to aid filtering potentially bogus light curves in future studies. We provide a complete list of objects with potential scientific application so they can be further scrutinised by the community. These results confirm the importance of combining automatic machine learning algorithms with domain knowledge in the construction of recommendation systems for astronomy. Our code is publicly available at https://github.com/snad-space/zwad
The Transient Optical Sky Survey (TOSS) is an automated, ground-based telescope system dedicated to searching for optical transient events. Small telescope tubes are mounted on a tracking, semi-equatorial frame with a single polar axis. Each fixed declination telescope records successive exposures which overlap in right ascension. Nightly observations produce time-series images of fixed fields within each declination band. We describe the TOSS data pipeline, including automated routines used for image calibration, object detection and identification, astrometry, and differential photometry. Time series of nightly observations are accumulated in a database for each declination band. Despite the modest cost of the mechanical system, results from the 2009-2010 observing campaign confirm the systems capability for producing light curves of satisfactory accuracy. Transients can be extracted from the individual time-series by identifying deviations from baseline variability.
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