Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers

Chad Hanna; Prathamesh Joshi; Rachael Huxford; Kipp Cannon; Sarah Caudill; Chiwai Chan; Bryce Cousins; Jolien D.E. Creighton; Becca Ewing; Miguel Fernandez; Heather Fong; Patrick Godwin; Ryan Magee; Duncan Meacher; Cody Messick; Soichiro Morisaki; Debnandini Mukherjee; Hiroaki Ohta; Alexander Pace; Stephen Privitera; Surabhi Sachdev; Shio Sakon; Divya Singh; Ron Tapia; Leo Tsukada; Daichi Tsuna; Takuya Tsutsui; Koh Ueno; Aaron Viets; Leslie Wade; Madeline Wade; Jonathan Wang

doi:10.1103/PhysRevD.106.084033

Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers

Chad Hanna, Prathamesh Joshi, Rachael Huxford, Kipp Cannon, Sarah Caudill, Chiwai Chan, Bryce Cousins, Jolien D.E. Creighton, Becca Ewing, Miguel Fernandez, Heather Fong, Patrick Godwin, Ryan Magee, Duncan Meacher, Cody Messick, Soichiro Morisaki, Debnandini Mukherjee, Hiroaki Ohta, Alexander Pace, Stephen PriviteraSurabhi Sachdev, Shio Sakon, Divya Singh, Ron Tapia, Leo Tsukada, Daichi Tsuna, Takuya Tsutsui, Koh Ueno, Aaron Viets, Leslie Wade, Madeline Wade, Jonathan Wang

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

1 Scopus citations

Abstract

We present a novel gravitational-wave detection algorithm that conducts a matched-filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler, allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC-Aug 25 22:00 2017 UTC and recover eight known confident gravitational-wave candidates. We also inject simulated binary black hole signals to demonstrate the sensitivity.

Original language	English (US)
Article number	084033
Journal	Physical Review D
Volume	106
Issue number	8
DOIs	https://doi.org/10.1103/PhysRevD.106.084033
State	Published - Oct 15 2022

All Science Journal Classification (ASJC) codes

Nuclear and High Energy Physics

Access to Document

10.1103/PhysRevD.106.084033

Cite this

Hanna, C., Joshi, P., Huxford, R., Cannon, K., Caudill, S., Chan, C., Cousins, B., Creighton, J. D. E., Ewing, B., Fernandez, M., Fong, H., Godwin, P., Magee, R., Meacher, D., Messick, C., Morisaki, S., Mukherjee, D., Ohta, H., Pace, A., ... Wang, J. (2022). Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers. Physical Review D, 106(8), Article 084033. https://doi.org/10.1103/PhysRevD.106.084033

@article{95fd2fb006f4462bacd7bf6e39648283,

title = "Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers",

abstract = "We present a novel gravitational-wave detection algorithm that conducts a matched-filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler, allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC-Aug 25 22:00 2017 UTC and recover eight known confident gravitational-wave candidates. We also inject simulated binary black hole signals to demonstrate the sensitivity.",

author = "Chad Hanna and Prathamesh Joshi and Rachael Huxford and Kipp Cannon and Sarah Caudill and Chiwai Chan and Bryce Cousins and Creighton, {Jolien D.E.} and Becca Ewing and Miguel Fernandez and Heather Fong and Patrick Godwin and Ryan Magee and Duncan Meacher and Cody Messick and Soichiro Morisaki and Debnandini Mukherjee and Hiroaki Ohta and Alexander Pace and Stephen Privitera and Surabhi Sachdev and Shio Sakon and Divya Singh and Ron Tapia and Leo Tsukada and Daichi Tsuna and Takuya Tsutsui and Koh Ueno and Aaron Viets and Leslie Wade and Madeline Wade and Jonathan Wang",

note = "Publisher Copyright: {\textcopyright} 2022 American Physical Society.",

year = "2022",

month = oct,

day = "15",

doi = "10.1103/PhysRevD.106.084033",

language = "English (US)",

volume = "106",

journal = "Physical Review D",

issn = "2470-0010",

publisher = "American Physical Society",

number = "8",

}

Hanna, C, Joshi, P, Huxford, R, Cannon, K, Caudill, S, Chan, C, Cousins, B, Creighton, JDE, Ewing, B, Fernandez, M, Fong, H, Godwin, P, Magee, R, Meacher, D, Messick, C, Morisaki, S, Mukherjee, D, Ohta, H, Pace, A, Privitera, S, Sachdev, S, Sakon, S, Singh, D, Tapia, R, Tsukada, L, Tsuna, D, Tsutsui, T, Ueno, K, Viets, A, Wade, L, Wade, M & Wang, J 2022, 'Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers', Physical Review D, vol. 106, no. 8, 084033. https://doi.org/10.1103/PhysRevD.106.084033

TY - JOUR

T1 - Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers

AU - Hanna, Chad

AU - Joshi, Prathamesh

AU - Huxford, Rachael

AU - Cannon, Kipp

AU - Caudill, Sarah

AU - Chan, Chiwai

AU - Cousins, Bryce

AU - Creighton, Jolien D.E.

AU - Ewing, Becca

AU - Fernandez, Miguel

AU - Fong, Heather

AU - Godwin, Patrick

AU - Magee, Ryan

AU - Meacher, Duncan

AU - Messick, Cody

AU - Morisaki, Soichiro

AU - Mukherjee, Debnandini

AU - Ohta, Hiroaki

AU - Pace, Alexander

AU - Privitera, Stephen

AU - Sachdev, Surabhi

AU - Sakon, Shio

AU - Singh, Divya

AU - Tapia, Ron

AU - Tsukada, Leo

AU - Tsuna, Daichi

AU - Tsutsui, Takuya

AU - Ueno, Koh

AU - Viets, Aaron

AU - Wade, Leslie

AU - Wade, Madeline

AU - Wang, Jonathan

PY - 2022/10/15

Y1 - 2022/10/15

N2 - We present a novel gravitational-wave detection algorithm that conducts a matched-filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler, allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC-Aug 25 22:00 2017 UTC and recover eight known confident gravitational-wave candidates. We also inject simulated binary black hole signals to demonstrate the sensitivity.

AB - We present a novel gravitational-wave detection algorithm that conducts a matched-filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler, allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC-Aug 25 22:00 2017 UTC and recover eight known confident gravitational-wave candidates. We also inject simulated binary black hole signals to demonstrate the sensitivity.

UR - http://www.scopus.com/inward/record.url?scp=85140262127&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85140262127&partnerID=8YFLogxK

U2 - 10.1103/PhysRevD.106.084033

DO - 10.1103/PhysRevD.106.084033

M3 - Article

AN - SCOPUS:85140262127

SN - 2470-0010

VL - 106

JO - Physical Review D

JF - Physical Review D

IS - 8

M1 - 084033

ER -

Metric assisted stochastic sampling search for gravitational waves from binary black hole mergers

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this