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A novel method for transient detection in high-cadence optical surveys Its application for a systematic search for novae in M31

Soraisam, Monika D. and Gilfanov, Marat and Kupfer, Thomas and Masci, Frank and Shafter, Allen W. and Prince, Thomas A. and Kulkarni, Shrinivas R. and Ofek, Eran O. and Bellm, Eric (2017) A novel method for transient detection in high-cadence optical surveys Its application for a systematic search for novae in M31. Astronomy & Astrophysics, 599 . Art. No. A48. ISSN 0004-6361. https://resolver.caltech.edu/CaltechAUTHORS:20170417-142352019

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Abstract

Context. In the present era of large-scale surveys in the time domain, the processing of data, from procurement up to the detection of sources, is generally automated. One of the main challenges in the astrophysical analysis of their output is contamination by artifacts, especially in the regions of high surface brightness of unresolved emission. Aims. We present a novel method for identifying candidates for variable and transient sources from the outputs of optical time-domain survey data pipelines. We use the method to conduct a systematic search for novae in the intermediate Palomar Transient Factory (iPTF) observations of the bulge part of M 31 during the second half of 2013. Methods. We demonstrate that a significant fraction of artifacts produced by the iPTF pipeline form a locally uniform background of false detections approximately obeying Poissonian statistics, whereas genuine variable and transient sources, as well as artifacts associated with bright stars, result in clusters of detections whose spread is determined by the source localization accuracy. This makes the problem analogous to source detection on images produced by grazing incidence X-ray telescopes, enabling one to utilize the arsenal of powerful tools developed in X-ray astronomy. In particular, we use a wavelet-based source detection algorithm from the Chandra data analysis package CIAO. Results. Starting from ~2.5 × 10^5 raw detections made by the iPTF data pipeline, we obtain approximately 4000 unique source candidates. Cross-matching these candidates with the source-catalog of a deep reference image of the same field, we find counterparts for ~90% of the candidates. These sources are either artifacts due to imperfect PSF matching or genuine variable sources. The remaining approximately 400 detections are transient sources. We identify novae among these candidates by applying selection cuts to their lightcurves based on the expected properties of novae. Thus, we recovered all 12 known novae (not counting one that erupted toward the end of the survey) registered during the time span of the survey and discovered three nova candidates. Our method is generic and can be applied to mining any target out of the artifacts in optical time-domain data. As it is fully automated, its incompleteness can be accurately computed and corrected for.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1051/0004-6361/201629368DOIArticle
http://www.aanda.org/articles/aa/pdf/forth/aa29368-16.pdfPublisherArticle
https://arxiv.org/abs/1612.00116arXivDiscussion Paper
ORCID:
AuthorORCID
Kupfer, Thomas0000-0002-6540-1484
Masci, Frank0000-0002-8532-9395
Prince, Thomas A.0000-0002-8850-3627
Kulkarni, Shrinivas R.0000-0001-5390-8563
Ofek, Eran O.0000-0002-6786-8774
Bellm, Eric0000-0001-8018-5348
Additional Information:© 2017 ESO. Received: 21 July 2016. Accepted: 28 November 2016. M.D.S. is grateful to Niels Oppermann (CITA) for helpful discussions on the Bayesian treatment of obtaining the probability distribution of false matches. M.D.S. thanks the California Institute of Technology, where a portion of this work was completed, for its hospitality. M.D.S. was supported, in part, by the GROWTH internship program funded by the National Science Foundation under Grant No. 1545949. A.W.S. is grateful to the NSF for financial support through grant AST-1009566. M.G. acknowledges partial support by Russian Scientific Foundation (RSF), project 14-22-00271.
Group:Infrared Processing and Analysis Center (IPAC), Palomar Transient Factory, Astronomy Department
Funders:
Funding AgencyGrant Number
NSF1545949
NSFAST-1009566
Russian Science Foundation14-22-00271
Subject Keywords:methods: data analysis, surveys, novae, cataclysmic variables, galaxies: individual: M 31
Record Number:CaltechAUTHORS:20170417-142352019
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170417-142352019
Official Citation:A novel method for transient detection in high-cadence optical surveys - Its application for a systematic search for novae in M 31 Monika D. Soraisam, Marat Gilfanov, Thomas Kupfer, Frank Masci, Allen W. Shafter, Thomas A. Prince, Shrinivas R. Kulkarni, Eran O. Ofek and Eric Bellm A&A, 599 (2017) A48 DOI: https://doi.org/10.1051/0004-6361/201629368
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76615
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:17 Apr 2017 21:44
Last Modified:03 Oct 2019 17:03

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