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Article type: Research Article
Authors: Lin, Ching-Lunga | Lin, Lirena | Nakamura, Genb; *
Affiliations: [a] Department of Mathematics, Cheng Kung University, Tainan 701, Taiwan. E-mails: cllin2@mail.ncku.edu.tw, lirenlin2017@gmail.com | [b] Department of Mathematics, Hokkaido University, Sapporo 060-0810, Japan. E-mail: gnaka@math.sci.hokudai.ac.jp
Correspondence: [*] Corresponding author. E-mail: gnaka@math.sci.hokudai.ac.jp.
Abstract: The Born approximation and the Born sequence are considered for hyperbolic equations when we perturb their leading parts. The Born approximation is a finite successive approximation such as the finite terms Neumann series for the solution of a hyperbolic equation in terms of the smallness of the perturbation and if the successive approximation is infinitely many times, then we have the Born series. Due to the so called regularity loss for solutions of hyperbolic equations, we need to assume that data such as the inhomogeneous term of the equation, Cauchy datum and boundary datum are C∞, and also they satisfy the compatibility condition of any order in order to define the Born series. Otherwise we need to smooth each term of the Born series. The convergence of the Born series and the Born series with smoothing are very natural questions to be asked. Also giving an estimate of approximating the solution for finite terms Born series is also an important question in practice. The aims of this paper are to discuss about these questions. We would like to emphasize that we found a small improvement in the usual energy estimate for solutions of an initial value problem for a hyperbolic equation, which is very useful for our aims. Since the estimate of approximation is only giving the worst estimate for the approximation, we also provide some numerical studies on these questions which are very suggestive for further theoretical studies on the Born approximation for hyperbolic equations.
Keywords: Born approximation, Born sequence, smoothing, hyperbolic equation
DOI: 10.3233/ASY-201596
Journal: Asymptotic Analysis, vol. 121, no. 2, pp. 101-123, 2021
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