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Simulating binary black hole mergers using discontinuous Galerkin methods

delete2025-01-07
delete0
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OA
AI
G
Geoffrey Lovelace *
K
Kyle C. Nelli *
N
Nils Deppe
N
Nils L. Vu
W
William Throwe
M
M. S. Bonilla
A
Alexander Carpenter
L
Larry Kidder
A
Alexandra Lorandi Macedo
M
Mark Scheel
A
Azer Afram
M
Michael Boyle
A
A. Ceja
M
Matthew Giesler
S
Sarah Habib
K
Ken Z. Jones
P
P. Kumar
G
Guillermo Lara
D
D. A. Melchor
I
Iago B. Mendes
K
Keefe Mitman
M
Marlo Morales
J
Jordan Moxon
E
E. O’Shea
P
Pannone, Kyle
H
Harald Pfeiffer
R
Ramirez-Aguilar, Teresita
J
Jennifer Hincapié Sánchez
D
Daniel Tellez
S
Saul A. Teukolsky
N
Nikolas A. Wittek
DOI:10.1088/1361-6382/ad9f19delete
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摘要

摘要

En 中文
Binary black holes are the most abundant source of gravitational-wave observations. Gravitational-wave observatories in the next decade will require tremendous increases in the accuracy of numerical waveforms modeling binary black holes, compared to today's state of the art. One approach to achieving the required accuracy is using spectral-type methods that scale to many processors. Using the SpECTRE numerical-relativity (NR) code, we present the first simulations of a binary black hole inspiral, merger, and ringdown using discontinuous Galerkin (DG) methods. The efficiency of DG methods allows us to evolve the binary through similar to 18 orbits at reasonable computational cost. We then use SpECTRE's Cauchy Characteristic Evolution (CCE) code to extract the gravitational waves at future null infinity. The open-source nature of SpECTRE means this is the first time a spectral-type method for simulating binary black hole evolutions is available to the entire NR community.
Keyword:
discontinuous Galerkin
binary black holes
numerical relativity

期刊

Classical and Quantum Gravity 封面图
Classical and Quantum Gravity
IF:
3.7
论文数:
1.3W
被引数:
3.0W

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California State University, Fullerton 封面图
California State University, Fullerton
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1.4K
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被引数: 1.9K
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California Institute of Technology
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2.9W
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被引数: 4.9W
California State University System 封面图
California State University System
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2.8W
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Cornell University
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6.3W
论文数: 5.4W
被引数: 10.9W
N
Northwestern University
学者数:
6.2W
论文数: 5.3W
被引数: 3.9K
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