Acoustic inverse source problem 2026-10-06
Recover a compactly supported acoustic source from measurements of its outgoing field, such as its far-field pattern. The Helmholtz equation forward problem is specified with the Sommerfeld radiation condition. At a single frequency, the source-to-far-field operator at fixed frequency has invisible fixed-frequency nonradiating sources, and its compactness makes recovery of the visible component unstable.
Adjoint source-to-far-field operator 2026-10-06
With complex inner products linear in the first argument, the adjoint operator of the source-to-far-field operator at fixed frequency isIt is a normalized Herglotz wave function. Complex conjugation reverses the phase sign, while retaining the real factor .
Fixed-frequency nonradiating source 2026-10-06
A source is nonradiating at frequency if its outgoing field has zero far-field pattern. For every , the source has outgoing field and is invisible outside . Integration by parts shows that its Fourier transform vanishes on , so it belongs to the kernel of a linear map defined by the source-to-far-field operator at fixed frequency. This family proves nonuniqueness independently of the instability of the inverse.
The adjoint source-to-far-field operator composed with the source-to-far-field operator at fixed frequency has volume kernel , where and . This follows from . Its smoothing action helps explain the unstable normal equation for a linear inverse problem.
Past exam of the mathematics course of the University of Cambridge 2016 iii Paper 335 2 b Solution Created 2026-10-03 Updated 2026-10-06
Write , . Uniformly for in the source ball,For fixed and , the outgoing Green function for the three-dimensional Helmholtz equation therefore has the far-field approximation for an outgoing sourceSubstitution into the source integral yieldsThus the source-to-far-field operator at fixed frequency isIt samples the Fourier transform of the source on the sphere of radius . Its square-integrable kernel makes it a Hilbert-Schmidt operator, hence a compact operator. In factUse complex inner products linear in the first argument: . Interchanging the volume and surface integrals givesHence the adjoint source-to-far-field operator isThis is a normalized Herglotz wave function; the change in exponential sign comes from the complex conjugation in the adjoint operator.
Past exam of the mathematics course of the University of Cambridge 2016 iii Paper 335 2 c Solution Created 2026-10-03 Updated 2026-10-06
Seeking a least-squares solution of a linear inverse problem for the acoustic inverse source problem means minimizing . Its normal equation for a linear inverse problem isFor compatible data, the formal minimum-norm solution can be written with the Moore–Penrose inverse of an operator:The inverse in this expression is defined on the range of the restricted operator, not as a bounded everywhere-defined inverse. The unrestricted expression is only formal because has a nontrivial kernel of a linear map.
The normal kernel of the source-to-far-field operator can be computed explicitly:The quotient is at coincidence. This smooth kernel already exhibits the loss of information.
There are two distinct causes of ill-posedness. First, a fixed-frequency nonradiating source gives exact nonuniqueness. For any , putThe outgoing solution is , which vanishes outside , so . Equivalently, integration by parts in the source-to-far-field operator at fixed frequency givessince the exponential solves the homogeneous Helmholtz equation and the boundary terms vanish. This provides an infinite-dimensional family of invisible sources. Single-frequency data determine only the spherical restriction of a three-dimensional Fourier transform.
Second, the compact operator has arbitrarily small nonzero singular values. To see that its rank is infinite, choose a source , with a spherical harmonic . The plane-wave angular integral givesThe Spherical Bessel function is not identically zero, so choose to obtain a nonzero far-field coefficient for every . The mutually orthogonal angular modes prove infinite rank. The inverse on is therefore unbounded, and division by these small singular values amplifies noise. Its range is not closed; arbitrary noisy data need not be the far-field pattern of a source, and a least-squares solution need not exist without regularization of an inverse problem. For example, Tikhonov regularization gives . It stabilizes the recovered visible component but cannot identify the missing fixed-frequency nonradiating source component.