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In his article, [1] Milne-Thomson considers the problem of finding () when 1. u ( x , y ) {\displaystyle u(x,y)} and v ( x , y ) {\displaystyle v(x,y)} are given, 2. u ( x , y ) {\displaystyle u(x,y)} is given and f ( z ) {\displaystyle f(z)} is real on the real axis, 3. only u ( x , y ) {\displaystyle u(x,y)} is given, 4. only v ( x , y ...
Laplace solved this problem for the case of rational functions, as he showed that the indefinite integral of a rational function is a rational function and a finite number of constant multiples of logarithms of rational functions [citation needed]. The algorithm suggested by Laplace is usually described in calculus textbooks; as a computer ...
Technically, a point z 0 is a pole of a function f if it is a zero of the function 1/f and 1/f is holomorphic (i.e. complex differentiable) in some neighbourhood of z 0. A function f is meromorphic in an open set U if for every point z of U there is a neighborhood of z in which at least one of f and 1/f is holomorphic.
In numerical analysis, a root-finding algorithm is an algorithm for finding zeros, also called "roots", of continuous functions. A zero of a function f is a number x such that f ( x ) = 0 . As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form , root-finding algorithms provide approximations to zeros.
One important consequence of the theorem is that path integrals of holomorphic functions on simply connected domains can be computed in a manner familiar from the fundamental theorem of calculus: let be a simply connected open subset of , let : be a holomorphic function, and let be a piecewise continuously differentiable path in with start ...
For example, if 2 pigeons are randomly assigned to 4 pigeonholes, there is a 25% chance that at least one pigeonhole will hold more than one pigeon; for 5 pigeons and 10 holes, that probability is 69.76%; and for 10 pigeons and 20 holes it is about 93.45%.
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