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

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 the object is static, the data are often acquired over a time interval during which the object may change significantly. This problem can 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 hydrodynamic simulation from its line-integral projections are presented. In these examples standard reconstructions based on the static assumption are poor, while good quality reconstructions are obtained from a regularized Kalman estimate. Implications for various astrophysical applications, including tomography of the solar corona and radio aperture synthesis, are discussed.

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