iffraction theory and are solved using the method of stationary phase [63]. Asymptotically (i.e., increasing the distance between source and observation domains), the integral does not vanish only for in values close to the stationary point of the argument of the exponential function. As a relevant consequence, if there are no stationary points, AG is (asymptotically) zero, i.e., Gw(s,r') G(s,r'), and the approximation error tends to zero. The presence of stationary points depends on the w' value. For any s, there is a minimum value w' of w' that assures the absence of stationary points. Any bandwidth value not smaller than w' assures an approximation error tending to zero. As noted above, the value of w' that assures the absence of stationary points depends on s. The function w'(s) is consequently the "local bandwidth" around si while its maximum, W' = maxg w (E), is = called the "effective bandwidth" of the field [22]. Since the local bandwidth changes along the observation curve, the Nyquist step also changes. To simplify the representation, and to have a constant Nyquist step, it is advantageous to choose the su function such that the local bandwidth has a constant value, f.i. W', along the observation curve, imposing [22]: (2.12) 2 w' is bandwidth in the angular spatial frequency. The angular spatial frequency is defined in this chapter as 2 times the spatial frequency. The relationship between these two quantities is the same relationship that exists between angular frequency and frequency in time domain signals. In electromagnetic theory the natural choice is the angular spatial frequency, which is directly related to the physical concept of wave number, while in Information Theory the frequency is usually preferred. 2 Information Flows at the DPL Level wherein (see Fig. 2.6): (2.13) i is the unit vector tangent to the curve in the point P(s), and S is the curvilinear abscissa in the P point. This choice gives a constant sampling step along the observation curve equal to: (2.14) The expression of su and y 