Time-dependent Reconstruction of Nonstationary Objects with Tomographic or Interferometric Measurements

Abstract

In a number of astrophysical applications one tries to determine the two-dimensional or three-dimensional structure of an object from a time series of measurements. While most methods used for reconstruction assume that object is static, the data are often acquired over a time interval during which the object may change significantly. This problem may be addressed with time-dependent reconstruction methods such as Kalman filtering which models the temporal evolution of the unknown object as a random walk that may or may not have a deterministic component. Time-dependent reconstructions of a hydrodynamical simulation from its line-integral projections are presented. In these examples standard reconstructions based on the static assumption are poor while the Kalman based reconstructions are of good quality. Implications for various astrophysical applications, including tomography of the solar corona and radio aperture synthesis, are discussed.