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The function is real-valued, positive-homogeneous of degree 1, and infinitely differentiable away from {=}. Also, we assume that does not have any critical points on the support of . Such a function, is usually called a phase function. In some contexts more general functions are considered and still referred to as phase functions.
The pseudocode below performs the GS algorithm to obtain a phase distribution for the plane "Source", such that its Fourier transform would have the amplitude distribution of the plane "Target". The Gerchberg-Saxton algorithm is one of the most prevalent methods used to create computer-generated holograms .
Consider a continuous-time Markov process with m + 1 states, where m ≥ 1, such that the states 1,...,m are transient states and state 0 is an absorbing state. Further, let the process have an initial probability of starting in any of the m + 1 phases given by the probability vector (α 0,α) where α 0 is a scalar and α is a 1 × m vector.
Otherwise it is called unwrapped phase, which is a continuous function of argument t, assuming s a (t) is a continuous function of t. Unless otherwise indicated, the continuous form should be inferred. Instantaneous phase vs time. The function has two true discontinuities of 180° at times 21 and 59, indicative of amplitude zero-crossings.
Using phase retrieval algorithms, it is possible to characterize complex optical systems and their aberrations. [6] For example, phase retrieval was used to diagnose and repair the flawed optics of the Hubble Space Telescope. [7] [8] Other applications of phase retrieval include X-ray crystallography [9] and transmission electron microscopy.
Phase-field models are usually constructed in order to reproduce a given interfacial dynamics. For instance, in solidification problems the front dynamics is given by a diffusion equation for either concentration or temperature in the bulk and some boundary conditions at the interface (a local equilibrium condition and a conservation law), [14] which constitutes the sharp interface model.
The equation is given by ¨ + ˙ + + = (), where the (unknown) function = is the displacement at time t, ˙ is the first derivative of with respect to time, i.e. velocity, and ¨ is the second time-derivative of , i.e. acceleration.
In mathematics, the stationary phase approximation is a basic principle of asymptotic analysis, applying to functions given by integration against a rapidly-varying complex exponential. This method originates from the 19th century, and is due to George Gabriel Stokes and Lord Kelvin . [ 1 ]