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Orthogonal polynomials are classes of polynomials defined over a range that obey an orthogonalityrelation
(1)
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where is a weighting function and is the Kronecker delta. If , then the polynomials are not only orthogonal, but orthonormal.
Orthogonal polynomials have very useful properties in the solution of mathematical and physical problems. Just as Fourier series provide a convenient method of expanding a periodic function in a series of linearly independent terms, orthogonal polynomials provide a natural way to solve, expand, and interpret solutions to many types of important differential equations. Orthogonal polynomials are especially easy to generate using Gram-Schmidt orthonormalization.
A table of common orthogonal polynomials is given below, where is the weighting function and
(2)
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(Abramowitz and Stegun 1972, pp. 774-775).
polynomial | interval | ||
Chebyshev polynomial of the first kind | |||
Chebyshev polynomial of the second kind | |||
Gegenbauer polynomial | |||
Hermite polynomial | |||
Jacobi polynomial | |||
Laguerre polynomial | 1 | ||
generalized Laguerre polynomial | |||
Legendre polynomial | 1 |
In the above table,
(3)
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where is a gamma function.
The roots of orthogonal polynomials possess many rather surprising and useful properties. For instance, let be the roots of the with and . Then each interval for , 1, ..., contains exactly one root of . Between two roots of there is at least one root of for .
Let be an arbitrary real constant, then the polynomial
(4)
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has distinct real roots. If (), these roots lie in the interior of , with the exception of the greatest (least) root which lies in only for
(5)
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The following decomposition into partial fractions holds
(6)
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where are the roots of and
(7)
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|||
(8)
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Another interesting property is obtained by letting be the orthonormal set of polynomials associated with the distribution on . Then the convergents of the continued fraction
(9)
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are given by
(10)
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|||
(11)
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|||
(12)
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where , 1, ... and
(13)
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Furthermore, the roots of the orthogonal polynomials associated with the distribution on the interval are real and distinct and are located in the interior of the interval .
REFERENCES:
Abramowitz, M. and Stegun, I. A. (Eds.). "Orthogonal Polynomials." Ch. 22 in Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 9th printing. New York: Dover, pp. 771-802, 1972.
Arfken, G. "Orthogonal Polynomials." Mathematical Methods for Physicists, 3rd ed. Orlando, FL: Academic Press, pp. 520-521, 1985.
Chihara, T. S. An Introduction to Orthogonal Polynomials. New York: Gordon and Breach, 1978.
Gautschi, W.; Golub, G. H.; and Opfer, G. (Eds.) Applications and Computation of Orthogonal Polynomials, Conference at the Mathematical Research Institute Oberwolfach, Germany, March 22-28, 1998. Basel, Switzerland: Birkhäuser, 1999.
Iyanaga, S. and Kawada, Y. (Eds.). "Systems of Orthogonal Functions." Appendix A, Table 20 in Encyclopedic Dictionary of Mathematics. Cambridge, MA: MIT Press, p. 1477, 1980.
Koekoek, R. and Swarttouw, R. F. The Askey-Scheme of Hypergeometric Orthogonal Polynomials and its -Analogue. Delft, Netherlands: Technische Universiteit Delft, Faculty of Technical Mathematics and Informatics Report 98-17, 1-168, 1998.
Nikiforov, A. F.; Uvarov, V. B.; and Suslov, S. S. Classical Orthogonal Polynomials of a Discrete Variable. New York: Springer-Verlag, 1992.
Sansone, G. Orthogonal Functions. New York: Dover, 1991.
Szegö, G. Orthogonal Polynomials, 4th ed. Providence, RI: Amer. Math. Soc., pp. 44-47 and 54-55, 1975.
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