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GPU-accelerated periodic source identification in large-scale surveys: measuring P and Ṗ

Katz, Michael L. and Cooper, Olivia R. and Coughlin, Michael W. and Burdge, Kevin B. and Breivik, Katelyn and Larson, Shane L. (2021) GPU-accelerated periodic source identification in large-scale surveys: measuring P and Ṗ. Monthly Notices of the Royal Astronomical Society, 503 (2). pp. 2665-2675. ISSN 0035-8711. doi:10.1093/mnras/stab504.

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Many inspiraling and merging stellar remnants emit both gravitational and electromagnetic radiation as they orbit or collide. These gravitational wave events together with their associated electromagnetic counterparts provide insight about the nature of the merger, allowing us to further constrain properties of the binary. With the future launch of the Laser Interferometer Space Antenna (LISA), follow-up observations and models are needed of ultracompact binary (UCB) systems. Current and upcoming long baseline time domain surveys will observe many of these UCBs. We present a new fast periodic object search tool capable of searching for generic periodic signals based on the conditional entropy algorithm. This new implementation allows for a grid search over both the period (P) and the time derivative of the period (⁠Ṗ). To demonstrate the usage of this tool, we use a small, hand-picked subset of a UCB population generated from the population synthesis code COSMIC , as well as a custom catalogue for varying periods at fixed intrinsic parameters. We simulate light curves as likely to be observed by future time domain surveys by using an existing eclipsing binary light-curve model accounting for the change in orbital period due to gravitational radiation. We find that a search with Ṗ values is necessary for detecting binaries at orbital periods less than ∼10 min. We also show it is useful in finding and characterizing binaries with longer periods, but at a higher computational cost. Our code is called GCE (GPU-accelerated Conditional Entropy). It is available on Github (

Item Type:Article
Related URLs:
URLURL TypeDescription Paper ItemCode
Katz, Michael L.0000-0002-7605-5767
Coughlin, Michael W.0000-0002-8262-2924
Burdge, Kevin B.0000-0002-7226-836X
Additional Information:© 2021 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Accepted 2021 February 15. Received 2021 January 25; in original form 2020 June 11. Published: 04 March 2021. MLK acknowledges support from the National Science Foundation under grant DGE-0948017 and the Chateaubriand Fellowship from the Office for Science & Technology of the Embassy of France in the United States. ORC gratefully acknowledges support from the LIGO Scientific Collaboration, the California Institute of Technology, and the National Science Foundation through the LIGO Summer Undergraduate Research Fellowships (LIGO SURF) Program hosted by Caltech Student-Faculty Programs. MWC acknowledges support from the National Science Foundation with grant number PHY-2010970. This research was supported in part through the computational resources and staff contributions provided for the Quest/Grail high performance computing facility at Northwestern University. ASTROPY, a community-developed core PYTHON package for Astronomy, was used in this research (Astropy Collaboration et al. 2013). This paper also employed use of SCIPY (Jones et al. 2018), NUMPY (Walt, Colbert & Varoquaux 2011), PANDAS (McKinney 2010; The pandas development team 2020), and MATPLOTLIB (Hunter 2007). Data Availability: The data underlying this paper are publicly available in the GCE code repository on Github.
Funding AgencyGrant Number
NSF Graduate Research FellowshipDGE-0948017
Embassy of FranceUNSPECIFIED
LIGO Scientific CollaborationUNSPECIFIED
Caltech Summer Undergraduate Research Fellowship (SURF)UNSPECIFIED
Subject Keywords:gravitational waves – software: data analysis – white dwarfs
Issue or Number:2
Record Number:CaltechAUTHORS:20210611-143842025
Persistent URL:
Official Citation:Michael L Katz, Olivia R Cooper, Michael W Coughlin, Kevin B Burdge, Katelyn Breivik, Shane L Larson, GPU-accelerated periodic source identification in large-scale surveys: measuring P and P, Monthly Notices of the Royal Astronomical Society, Volume 503, Issue 2, May 2021, Pages 2665–2675,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109488
Deposited By: Tony Diaz
Deposited On:11 Jun 2021 21:56
Last Modified:11 Jun 2021 21:56

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