2018
DOI: 10.1137/18m1171072
|View full text |Cite
|
Sign up to set email alerts
|

Hermite Methods for the Scalar Wave Equation

Abstract: Arbitrary order dissipative and conservative Hermite methods for the scalar wave equation are presented. Both methods use (m + 1) d degrees of freedom per node for the displacement in d-dimensions; the dissipative and conservative methods achieve orders of accuracy (2m − 1) and 2m, respectively. Stability and error analyses as well as implementation strategies for accelerators are also given.1. Introduction. We construct, analyze, and test arbitrary order dissipative and conservative Hermite methods for the sc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
27
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
4
2

Relationship

3
3

Authors

Journals

citations
Cited by 12 publications
(27 citation statements)
references
References 18 publications
0
27
0
Order By: Relevance
“…To introduce the method, we consider the following one-dimensional wave system ∂p ∂t = c ∂v ∂x , ∂v ∂t = c ∂p ∂x (1) p(x, t 0 ) = f (x), v(x, t 0 + ∆t/2) = g(x).…”
Section: Description Of the Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…To introduce the method, we consider the following one-dimensional wave system ∂p ∂t = c ∂v ∂x , ∂v ∂t = c ∂p ∂x (1) p(x, t 0 ) = f (x), v(x, t 0 + ∆t/2) = g(x).…”
Section: Description Of the Methodsmentioning
confidence: 99%
“…Here c j are the coefficients from the Taylor series expansion. Drawing from the work of Appelö and co-authors in [1], we construct a time-stepping scheme by subtracting expansions 4a and 4b leading to…”
Section: A Note On Improving Rates Of Convergencementioning
confidence: 99%
See 1 more Smart Citation
“…In what follows we present a Bayesian framework based on an exponential likelihood function driven by a quadratic Wasserstein metric. Unlike conventional Bayesian analysis, this framework does not rely on the likelihood of the measurement noise and hence can treat complicated noise structures as in (1). Moreover, since the Wasserstein metric has better optimization and fitting properties than the least-squares norm (see e.g.…”
Section: Likelihood and Noise Structurementioning
confidence: 99%
“…skr , ε (1) skr ∼ Gamma(1000, 1000), ε (2) skr ∼ Unif(−0.05, 0.05). Let g sr ∈ R N and f sr (θ) ∈ R N denote the vectors of recorded and simulated discrete-time signals due to a single source F s , s = 1, .…”
Section: A Two-dimensional Materials Inversion Problemmentioning
confidence: 99%