(mathematics) Orthogonal polynomials are various families of polynomials, which arise as solutions to differential equations related to the hypergeometric equation, and which are mutually orthogonal as functions.
For more information on orthogonal polynomials, visit Britannica.com.
A special case of orthogonal functions that arise in many physical problems (often as the solutions of differential equations), in the study of distribution functions, and in certain other situations where one approximates fairly general functions by polynomials. See also Probability.
Each set of orthogonal polynomials is defined with respect to a particular averaging procedure. The average value of a suitable function ƒ is denoted by E(ƒ). An example is shown in Eq. (1). In general an averaging procedure has the form shown
1. 
in Eq. (2), a Stieltjes integral, where σ is a distribution function, that is, an increasing function with σ(−∞) = 0 and σ(+∞) = 1.
2. 
Two functions ƒ and g are said to be orthogonal with respect to a given averaging procedure if E{ƒ[ba]g} = 0 where the bar denotes complex conjugation. By the system of orthogonal polynomials associated with the averaging procedure is meant a sequence P0, P1, P2 … of polynomials Pn haying exact degree n, which are mutually orthogonal, that is,
for m ≠ n. This last condition is equivalent to the statement that each Pn is orthogonal to all polynomials of degree less than n. Thus Pnn has the form Pn(x) = a0 + a1x + a2x2 + ··· + anxn where an ≠ 0 and is subject to the n conditions Exk Pn = 0 for k = 0, 1, …, n − 1. This gives n linear equations in the n + 1 coefficients of Pn, leaving one more condition, called a normalization, to be imposed. The method of normalization differs in different references. See also Polynomial systems of equations.
In mathematics, an orthogonal polynomial sequence is a family of polynomials such that any two different polynomials in the sequence are orthogonal to each other under some inner product.
The most widely used orthogonal polynomials are the classical orthogonal polynomials, consisting of the Hermite polynomials, the Laguerre polynomials, the Jacobi polynomials together with their special cases the Gegenbauer polynomials, the Chebyshev polynomials, and the Legendre polynomials.
The field of orthogonal polynomials developed in the late 19th century from a study of continued fractions by P. L. Chebyshev and was pursued by A.A. Markov and T.J. Stieltjes. Some of the mathematicians who have worked on orthogonal polynomials include Gábor Szegő, Sergei Bernstein, Naum Akhiezer, Arthur Erdélyi, Yakov Geronimus, Wolfgang Hahn, Theodore Seio Chihara, Mourad Ismail, Waleed Al-Salam, and Richard Askey.
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Given any non-decreasing function α on the real numbers, we can define the Lebesgue–Stieltjes integral

of a function f. If this integral is finite for all polynomials f, we can define an inner product on pairs of polynomials f and g by

This operation is a positive semidefinite inner product on the vector space of all polynomials, and is positive definite if the function α has an infinite number of points of growth. It induces a notion of orthogonality in the usual way, namely that two polynomials are orthogonal if their inner product is zero.
Then the sequence (Pn)n=0∞ of orthogonal polynomials is defined by the relations

In other words, obtained from the sequence of monomials 1, x, x2, ... by the Gram–Schmidt process.
Usually the sequence is required to be orthonormal, namely,

however, other normalisations are sometimes used.
Sometimes we have

where
![W : [x_1, x_2] \to \mathbb{R}](http://wpcontent.answcdn.com/wikipedia/en/math/0/9/6/096ea355506bca024766848d7161c1eb.png)
is a non-negative function with support on some interval
in the real line (where
and
are allowed). Such a W is called a weight function. Then the inner product is given by

However there are many examples of orthogonal polynomials where the measure dα(x) has points with non-zero measure where the function α is discontinuous, so cannot be given by a weight function W as above.
The most commonly used orthogonal polynomials are orthogonal for a measure with support in a real interval. This includes:
Discrete orthogonal polynomials are orthogonal with respect to some discrete measure. Sometimes the measure has finite support, in which case the family of orthogonal polynomials is finite, rather than an infinite sequence. The Racah polynomials are examples of discrete orthogonal polynomials, and include as special cases the Hahn polynomials and dual Hahn polynomials, which in turn include as special cases the Meixner polynomials, Krawtchouk polynomials, and Charlier polynomials.
Sieved orthogonal polynomials, such as the sieved ultraspherical polynomials, sieved Jacobi polynomials, and sieved Pollaczek polynomials, have modified recurrence relations.
One can also consider orthogonal polynomials for some curve in the complex plane. The most important case (other than real intervals) is when the curve is the unit circle, giving orthogonal polynomials on the unit circle, such as the Rogers–Szegő polynomials.
There are some families of orthogonal polynomials that are orthogonal on plane regions such as triangles or disks. They can sometimes be written in terms of Jacobi polynomials. For example, Zernike polynomials are orthogonal on the unit disk.
Orthogonal polynomials of one variable defined by a non-negative measure on the real line have the following properties.
The orthogonal polynomials Pn can be expressed in terms of the moments

as follows:

where the constants cn are arbitrary (depend on the normalisation of Pn).
The polynomials Pn satisfy a recurrent relation of the form

See Favard's theorem for a converse result.
If the measure dα is supported on an interval [a, b], all the zeros of Pn lie in [a, b]. Moreover, the zeros have the following interlacing property: if m>n, there is a zero of Pm between any two zeros of Pn.
The Macdonald polynomials are orthogonal polynomials in several variables, depending on the choice of an affine root system. They include many other families of multivariable orthogonal polynomials as special cases, including the Jack polynomials, the Hall–Littlewood polynomials, the Heckman–Opdam polynomials, and the Koornwinder polynomials. The Askey–Wilson polynomials are the special case of Macdonald polynomials for a certain non-reduced root system of rank 1.
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