Numerical Recovery of Source Singularities via the Radiative Transfer Equation with Partial Data

Abstract

The inverse source problem for the radiative transfer equation is considered, with partial data. Here we demonstrate numerical computation of the normal operator $X_V^{\ast }{X}_V$ where $X_V$ is the partial data solution operator to the radiative transfer equation. The numerical scheme is based in part on a forward solver designed by F. Monard and G. Bal. We will see that one can detect quite well the visible singularities of an internal optical source $f$ for generic anisotropic $k$ and $\sigma$, with or without noise added to the accessible data $X_{V}f$. In particular, we use a truncated Neumann series to estimate $X_V$ and $X_V^{\ast }$, which provides a good approximation of $X_V^{\ast }{X}_V$ with an error of higher Sobolev regularity. This paper provides a visual demonstration of the authors' previous work in recovering the microlocally visible singularities of an unknown source from partial data. We also give the theoretical analysis necessary to justify the smoothness of the remainder when approximating the normal operator.

25 pages, 8 figures, Accepted to SIAM Journal on Imaging Sciences

References in corpus (1)

• An Inverse Source Problem in Radiative Transfer with Partial Data