Further, all computations can be condensed to the normal Eq. (5), requiring essentially only a matrix P of 1,000 9 1,000 numbers to be operated on, which even as double-precision data type requires less than 8 MB, trivial by current standards on any platform. Once condensed to the form of Eq. (5), our SV problem is far smaller (often several orders of magnitude) than common problems of analogous mathematical structure, for example, in astronomical image analysis (Narayan and Nityananda 1986) . For the data shown in Fig. 1 , in the implementation in SEDFIT (which does not optimize memory allocation), *20 MB of RAM are used.