1 Introduction
In many physical and engineering applications, it is sometimes necessary
to reconstruct the radiation filed from experimental data on a part of the
boundary. This so-called inverse scattering problems leads to the Cauchy
problem for Helmholtz equation[1,3,4,5,6,7,9]. After been studied by many
authors a number of numerical methods for stabilizing this problem are de-
veloped. However,these numerical methods are short of stability theory and
convergence proofs. In [7]the applications for a model of Helmholtz equation
are introduced, a method by cutting off high frequency directly is applied for
solving a Cauchy problem for Helmholtz equation, some error estimates are
also obtained. Recently in[9], some spectra methods and a revised Tikhonov
regularization method which are different from the method used in [7] are
discussed, the Holder-type stability estimate for z ∈ (0, d) is aslo obtained.
However their method is woking only for the Hilb ert space L
2
. Note that
the results available in the literatures are mainly devoted to two or three-
dimensional cases and the convergence proofs on the boundary couldn’t been
found in most papers.
The aim of this paper is to consider a Cauchy problem for the Helmholtz
equation in multiple dimensions, especially give the convergence proofs on
the boundary z = 0 by using the Tikhonov regularization method. It is
organized as follows: in Section 2, the formulation of solution of problem (1.1)
is given and the ill-posedness is discussed; Section 3 is devoted to proving
some auxiliary lemmas; in section 4, a Tikhonov regularization method with
error estimate is provided; the last section present some numerical results.
We consider a Cauchy problem for the Helmholtz equation in multiple
dimensions as follows:
∆u(y, z) + k
2
u(y, z) = 0, y ∈ R
n
, z ∈ [0, 1]
u( y, 1) = g(y), y ∈ R
n
,
u
z
( y, 1) = 0, y ∈ R
n
,
(1.1)
where ∆ is the Laplace operator in n+1(n ∈ N) dimensions, g(·) ∈ L
2
(R
n
), u( ·, z) ∈
L
2
(R
n+1
).Here we want to obtain the solution u( y, 0) form the Cauchy
data u( y, 1) := g(y), y ∈ R
n
. In the next section we analyze the ill-posedness
of problems(1.1).
2
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