Overview of the blocknormal event trigger generator

J. W.C. McNabb; M. Ashley; L. S. Finn; E. Rotthoff; A. Stuver; T. Summerscales; P. Sutton; M. Tibbits; K. Thorne; K. Zaleski

doi:10.1088/0264-9381/21/20/013

Overview of the blocknormal event trigger generator

J. W.C. McNabb, M. Ashley, L. S. Finn, E. Rotthoff, A. Stuver, T. Summerscales, P. Sutton, M. Tibbits, K. Thorne, K. Zaleski

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

In the search for unmodelled gravitational wave bursts, there are a variety of methods that have been proposed to generate candidate events from time series data. BlockNormal is a method of identifying candidate events by searching for places in the data stream where the characteristic statistics of the data change. These change points divide the data into blocks in which the characteristics of the block are stationary. Blocks in which these characteristics are inconsistent with the long term characteristic statistics are marked as event triggers, which can then be investigated by a more computationally demanding multi-detector analysis.

Original language	English (US)
Pages (from-to)	S1705-S1710
Journal	Classical and Quantum Gravity
Volume	21
Issue number	20 SPEC. ISS.
DOIs	https://doi.org/10.1088/0264-9381/21/20/013
State	Published - Oct 21 2004

All Science Journal Classification (ASJC) codes

Physics and Astronomy (miscellaneous)

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10.1088/0264-9381/21/20/013

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AU - McNabb, J. W.C.

AU - Ashley, M.

AU - Finn, L. S.

AU - Rotthoff, E.

AU - Stuver, A.

AU - Summerscales, T.

AU - Sutton, P.

AU - Tibbits, M.

AU - Thorne, K.

AU - Zaleski, K.

PY - 2004/10/21

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N2 - In the search for unmodelled gravitational wave bursts, there are a variety of methods that have been proposed to generate candidate events from time series data. BlockNormal is a method of identifying candidate events by searching for places in the data stream where the characteristic statistics of the data change. These change points divide the data into blocks in which the characteristics of the block are stationary. Blocks in which these characteristics are inconsistent with the long term characteristic statistics are marked as event triggers, which can then be investigated by a more computationally demanding multi-detector analysis.

AB - In the search for unmodelled gravitational wave bursts, there are a variety of methods that have been proposed to generate candidate events from time series data. BlockNormal is a method of identifying candidate events by searching for places in the data stream where the characteristic statistics of the data change. These change points divide the data into blocks in which the characteristics of the block are stationary. Blocks in which these characteristics are inconsistent with the long term characteristic statistics are marked as event triggers, which can then be investigated by a more computationally demanding multi-detector analysis.

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Overview of the blocknormal event trigger generator

Abstract

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