In mathematics, the **Hermite polynomials** are a classical orthogonal polynomial sequence.

The polynomials arise in:

- probability, such as the Edgeworth series;
- in combinatorics, as an example of an Appell sequence, obeying the umbral calculus;
- in numerical analysis as Gaussian quadrature;
- in physics, where they give rise to the eigenstates of the quantum harmonic oscillator;
- in systems theory in connection with nonlinear operations on Gaussian noise.
- in random matrix theory in Wigner–Dyson ensembles.

Hermite polynomials were defined by Pierre-Simon Laplace in 1810,^{[1]}^{[2]} though in scarcely recognizable form, and studied in detail by Pafnuty Chebyshev in 1859.^{[3]} Chebyshev's work was overlooked, and they were named later after Charles Hermite, who wrote on the polynomials in 1864, describing them as new.^{[4]} They were consequently not new, although Hermite was the first to define the multidimensional polynomials in his later 1865 publications.

## Contents

## DefinitionEdit

There are two different ways of standardizing the Hermite polynomials:

- The
**"probabilists' Hermite polynomials"**are given by

- while the
**"physicists' Hermite polynomials"**are given by

These two definitions are not exactly identical; each is a rescaling of the other:

These are Hermite polynomial sequences of different variances; see the material on variances below.

The notation He and H is that used in the standard references.^{[5]}
The polynomials He_{n} are sometimes denoted by H_{n}, especially in probability theory, because

is the probability density function for the normal distribution with expected value 0 and standard deviation 1.

- The first eleven probabilists' Hermite polynomials are:

- The first eleven physicists' Hermite polynomials are:

## PropertiesEdit

The nth-order Hermite polynomial is a polynomial of degree n. The probabilists' version He_{n} has leading coefficient 1, while the physicists' version H_{n} has leading coefficient 2^{n}.

### OrthogonalityEdit

*H _{n}*(

*x*) and

*He*(

_{n}*x*) are nth-degree polynomials for

*n*= 0, 1, 2, 3,.... These polynomials are orthogonal with respect to the

*weight function*(measure)

or

i.e., we have

Furthermore,

or

where is the Kronecker delta.

The probabilist polynomials are thus orthogonal with respect to the standard normal probability density function.

### CompletenessEdit

The Hermite polynomials (probabilists' or physicists') form an orthogonal basis of the Hilbert space of functions satisfying

in which the inner product is given by the integral

including the Gaussian weight function *w*(*x*) defined in the preceding section

An orthogonal basis for *L*^{2}(**R**, *w*(*x*) *dx*) is a *complete* orthogonal system. For an orthogonal system, *completeness* is equivalent to the fact that the 0 function is the only function *f* ∈ *L*^{2}(**R**, *w*(*x*) *dx*) orthogonal to *all* functions in the system.

Since the linear span of Hermite polynomials is the space of all polynomials, one has to show (in physicist case) that if f satisfies

for every *n* ≥ 0, then *f* = 0.

One possible way to do this is to appreciate that the entire function

vanishes identically. The fact then that *F*(*it*) = 0 for every real t means that the Fourier transform of *f*(*x*)*e*^{−x2} is 0, hence f is 0 almost everywhere. Variants of the above completeness proof apply to other weights with exponential decay.

In the Hermite case, it is also possible to prove an explicit identity that implies completeness (see section on the Completeness relation below).

An equivalent formulation of the fact that Hermite polynomials are an orthogonal basis for *L*^{2}(**R**, *w*(*x*) *dx*) consists in introducing Hermite *functions* (see below), and in saying that the Hermite functions are an orthonormal basis for *L*^{2}(**R**).

### Hermite's differential equationEdit

The probabilists' Hermite polynomials are solutions of the differential equation

where λ is a constant, with the boundary conditions that u should be polynomially bounded at infinity. With these boundary conditions, the equation has solutions only if λ is a non-negative integer, and up to an overall scaling, the solution is uniquely given by *u*(*x*) = *He _{λ}*(

*x*).

Rewriting the differential equation as an eigenvalue problem

solutions are the eigenfunctions of the differential operator L. This eigenvalue problem is called the **Hermite equation**, although the term is also used for the closely related equation

whose solutions are the physicists' Hermite polynomials.

With more general boundary conditions, the Hermite polynomials can be generalized to obtain more general analytic functions *He*_{λ}(*z*) for λ a complex index. An explicit formula can be given in terms of a contour integral (Courant & Hilbert 1953).

### Recursion relationEdit

The sequence of probabilists' Hermite polynomials also satisfies the recurrence relation

Individual coefficients are related by the following recursion formula:

and *a*_{0,0} = 1, *a*_{1,0} = 0, *a*_{1,1} = 1.

For the physicists' polynomials, assuming

we have

Individual coefficients are related by the following recursion formula:

and *a*_{0,0} = 1, *a*_{1,0} = 0, *a*_{1,1} = 2.

The Hermite polynomials constitute an Appell sequence, i.e., they are a polynomial sequence satisfying the identity

Equivalently, by Taylor-expanding,

These umbral identities are self-evident and included in the differential operator representation detailed below,

In consequence, for the mth derivatives the following relations hold:

It follows that the Hermite polynomials also satisfy the recurrence relation

These last relations, together with the initial polynomials *H*_{0}(*x*) and *H*_{1}(*x*), can be used in practice to compute the polynomials quickly.

Moreover, the following multiplication theorem holds:

### Explicit expressionEdit

The physicists' Hermite polynomials can be written explicitly as

These two equations may be combined into one using the floor function:

The probabilists' Hermite polynomials He have similar formulas, which may be obtained from these by replacing the power of 2*x* with the corresponding power of √2 *x* and multiplying the entire sum by 2^{−n/2}:

### Inverse explicit expressionEdit

The inverse of the above explicit expressions, that is, those for monomials in terms of probabilists’ Hermite polynomials He are

The corresponding expressions for the physicists’ Hermite polynomials H follow directly by properly scaling this:^{[6]}

### Generating functionEdit

The Hermite polynomials are given by the exponential generating function

This equality is valid for all complex values of x and t, and can be obtained by writing the Taylor expansion at x of the entire function *z* → *e*^{−z2} (in the physicists' case). One can also derive the (physicists') generating function by using Cauchy's integral formula to write the Hermite polynomials as

Using this in the sum

one can evaluate the remaining integral using the calculus of residues and arrive at the desired generating function.

### Expected valuesEdit

If X is a random variable with a normal distribution with standard deviation 1 and expected value μ, then

The moments of the standard normal (with expected value zero) may be read off directly from the relation for even indices:

where (2*n* − 1)!! is the double factorial. Note that the above expression is a special case of the representation of the probabilists' Hermite polynomials as moments:

### Asymptotic expansionEdit

Asymptotically, as *n* → ∞, the expansion^{[7]}

holds true. For certain cases concerning a wider range of evaluation, it is necessary to include a factor for changing amplitude:

which, using Stirling's approximation, can be further simplified, in the limit, to

This expansion is needed to resolve the wavefunction of a quantum harmonic oscillator such that it agrees with the classical approximation in the limit of the correspondence principle.

A better approximation, which accounts for the variation in frequency, is given by

A finer approximation,^{[8]} which takes into account the uneven spacing of the zeros near the edges, makes use of the substitution

with which one has the uniform approximation

Similar approximations hold for the monotonic and transition regions. Specifically, if

then

while for

with t complex and bounded, the approximation is

where Ai is the Airy function of the first kind.

### Special valuesEdit

The physicists' Hermite polynomials evaluated at zero argument *H _{n}*(0) are called Hermite numbers.

which satisfy the recursion relation *H _{n}*(0) = −2(

*n*− 1)

*H*

_{n − 2}(0).

In terms of the probabilists' polynomials this translates to

## Relations to other functionsEdit

### Laguerre polynomialsEdit

The Hermite polynomials can be expressed as a special case of the Laguerre polynomials:

### Relation to confluent hypergeometric functionsEdit

The physicists' Hermite polynomials can be expressed as a special case of the parabolic cylinder functions:

in the right half-plane, where *U*(*a*, *b*, *z*) is Tricomi's confluent hypergeometric function. Similarly,

where _{1}*F*_{1}(*a*, *b*; *z*) = *M*(*a*, *b*; *z*) is Kummer's confluent hypergeometric function.

## Differential-operator representationEdit

The probabilists' Hermite polynomials satisfy the identity

where D represents differentiation with respect to x, and the exponential is interpreted by expanding it as a power series. There are no delicate questions of convergence of this series when it operates on polynomials, since all but finitely many terms vanish.

Since the power-series coefficients of the exponential are well known, and higher-order derivatives of the monomial *x*^{n} can be written down explicitly, this differential-operator representation gives rise to a concrete formula for the coefficients of *H _{n}* that can be used to quickly compute these polynomials.

Since the formal expression for the Weierstrass transform W is *e*^{D2}, we see that the Weierstrass transform of (√2)^{n}*He _{n}*(

*x*/√2) is

*x*. Essentially the Weierstrass transform thus turns a series of Hermite polynomials into a corresponding Maclaurin series.

^{n}The existence of some formal power series *g*(*D*) with nonzero constant coefficient, such that *He _{n}*(

*x*) =

*g*(

*D*)

*x*, is another equivalent to the statement that these polynomials form an Appell sequence. Since they are an Appell sequence, they are

^{n}*a fortiori*a Sheffer sequence.

## Contour-integral representationEdit

From the generating-function representation above, we see that the Hermite polynomials have a representation in terms of a contour integral, as

with the contour encircling the origin.

## GeneralizationsEdit

The probabilists' Hermite polynomials defined above are orthogonal with respect to the standard normal probability distribution, whose density function is

which has expected value 0 and variance 1.

Scaling, one may analogously speak of **generalized Hermite polynomials**^{[9]}

of variance α, where α is any positive number. These are then orthogonal with respect to the normal probability distribution whose density function is

They are given by

Now, if

then the polynomial sequence whose nth term is

is called the umbral composition of the two polynomial sequences. It can be shown to satisfy the identities

and

The last identity is expressed by saying that this parameterized family of polynomial sequences is known as a cross-sequence. (See the above section on Appell sequences and on the differential-operator representation, which leads to a ready derivation of it. This binomial type identity, for *α* = *β* = 1/2, has already been encountered in the above section on #Recursion relations.)

### "Negative variance"Edit

Since polynomial sequences form a group under the operation of umbral composition, one may denote by

the sequence that is inverse to the one similarly denoted, but without the minus sign, and thus speak of Hermite polynomials of negative variance. For α > 0, the coefficients of are just the absolute values of the corresponding coefficients of .

These arise as moments of normal probability distributions: The nth moment of the normal distribution with expected value μ and variance *σ*^{2} is

where X is a random variable with the specified normal distribution. A special case of the cross-sequence identity then says that

## ApplicationsEdit

### Hermite functionsEdit

One can define the **Hermite functions** from the physicists' polynomials:

Since these functions contain the square root of the weight function and have been scaled appropriately, they are orthonormal:

and they form an orthonormal basis of *L*^{2}(**R**). This fact is equivalent to the corresponding statement for Hermite polynomials (see above).

The Hermite functions are closely related to the Whittaker function (Whittaker and Watson, 1962) *D*_{n}(*z*):

and thereby to other parabolic cylinder functions.

The Hermite functions satisfy the differential equation

This equation is equivalent to the Schrödinger equation for a harmonic oscillator in quantum mechanics, so these functions are the eigenfunctions.

### Recursion relationEdit

Following recursion relations of Hermite polynomials, the Hermite functions obey

and

Extending the first relation to the arbitrary mth derivatives for any positive integer m leads to

This formula can be used in connection with the recurrence relations for *He _{n}* and

*ψ*

_{n}to calculate any derivative of the Hermite functions efficiently.

### Cramér's inequalityEdit

The Hermite functions satisfy the following bound due to Harald Cramér:^{[10]}^{[11]}

for real x, where the constant K is less than 435. 1.086

### Hermite functions as eigenfunctions of the Fourier transformEdit

The Hermite functions *ψ*_{n}(*x*) are a set of eigenfunctions of the continuous Fourier transform F. To see this, take the physicists' version of the generating function and multiply by *e*^{−1/2x2}. This gives

The Fourier transform of the left side is given by

The Fourier transform of the right side is given by

Equating like powers of t in the transformed versions of the left and right sides finally yields

The Hermite functions *ψ _{n}*(

*x*) are thus an orthonormal basis of

*L*

^{2}(

**R**), which

*diagonalizes the Fourier transform operator*.

^{[12]}

### Wigner distributions of Hermite functionsEdit

The Wigner distribution function of the nth-order Hermite function is related to the nth-order Laguerre polynomial. The Laguerre polynomials are

leading to the oscillator Laguerre functions

For all natural integers n, it is straightforward to see^{[13]} that

where the Wigner distribution of a function *x* ∈ *L*^{2}(**R**, **C**) is defined as

This is a fundamental result for the quantum harmonic oscillator discovered by Hip Groenewold in 1946 in his PhD thesis.^{[14]} It is the standard paradigm of quantum mechanics in phase space.

There are further relations between the two families of polynomials.

### Combinatorial interpretation of coefficientsEdit

In the Hermite polynomial *He*_{n}(*x*) of variance 1, the absolute value of the coefficient of *x*^{k} is the number of (unordered) partitions of an n-member set into k singletons and *n* − *k*/2 (unordered) pairs. The sum of the absolute values of the coefficients gives the total number of partitions into singletons and pairs, the so-called telephone numbers

This combinatorial interpretation can be related to complete exponential Bell polynomials as

where *x*_{i} = 0 for all *i* > 2.

These numbers may also be expressed as a special value of the Hermite polynomials:^{[15]}

### Completeness relationEdit

The Christoffel–Darboux formula for Hermite polynomials reads

Moreover, the following completeness identity for the above Hermite functions holds in the sense of distributions:

where δ is the Dirac delta function, *ψ*_{n} the Hermite functions, and *δ*(*x* − *y*) represents the Lebesgue measure on the line *y* = *x* in **R**^{2}, normalized so that its projection on the horizontal axis is the usual Lebesgue measure.

This distributional identity follows Wiener (1958) by taking *u* → 1 in Mehler's formula, valid when −1 < *u* < 1:

which is often stated equivalently as a separable kernel,^{[16]}^{[17]}

The function (*x*, *y*) → *E*(*x*, *y*; *u*) is the bivariate Gaussian probability density on **R**^{2}, which is, when u is close to 1, very concentrated around the line *y* = *x*, and very spread out on that line. It follows that

when *f* and *g* are continuous and compactly supported.

This yields that f can be expressed in Hermite functions as the sum of a series of vectors in *L*^{2}(**R**), namely,

In order to prove the above equality for *E*(*x*,*y*;*u*), the Fourier transform of Gaussian functions is used repeatedly:

The Hermite polynomial is then represented as

With this representation for *H _{n}*(

*x*) and

*H*(

_{n}*y*), it is evident that

and this yields the desired resolution of the identity result, using again the Fourier transform of Gaussian kernels under the substitution

## See alsoEdit

## NotesEdit

**^**Laplace 1810 (online).**^**Laplace, P.-S. (1812).*Théorie analytique des probabilités*[*Analytic Probability Theory*].**2**. pp. 194–203. Collected in*Œuvres***VII**.**^**Chebyshev, P. L. (1859). "Sur le développement des fonctions à une seule variable" [On the development of single-variable functions].*Bull. Acad. Sci. St. Petersb*.**1**: 193–200. Collected in*Œuvres***I**, 501–508.**^**Hermite, C. (1864). "Sur un nouveau développement en série de fonctions" [On a new development in function series].*C. R. Acad. Sci. Paris*.**58**: 93–100. Collected in*Œuvres***II**, 293–303.**^**Tom H. Koornwinder, Roderick S. C. Wong, and Roelof Koekoek et al. (2010) and Abramowitz & Stegun.**^**"18. Orthogonal Polynomials, Classical Orthogonal Polynomials, Sums".*Digital Library of Mathematical Functions*. National Institute of Standards and Technology. Retrieved 30 January 2015.**^**Abramowitz & Stegun 1983, p. 508–510, 13.6.38 and 13.5.16.**^**Szegő 1955, p. 201**^**Roman, Steven (1984).*The Umbral Calculus*. Pure and Applied Mathematics.**111**(1st ed.). Academic Press. pp. 87–93. ISBN 978-0-12-594380-2.**^**Erdélyi et al. 1955, p. 207.**^**Szegő 1955.**^**In this case, we used the unitary version of the Fourier transform, so the eigenvalues are (−*i*)^{n}. The ensuing resolution of the identity then serves to define powers, including fractional ones, of the Fourier transform, to wit a Fractional Fourier transform generalization, in effect a Mehler kernel.**^**Folland, G. B. (1989).*Harmonic Analysis in Phase Space*. Princeton University Press.^{[ISBN missing]}^{[page needed]}**^**Groenewold, H. J. (1946). "On the Principles of elementary quantum mechanics".*Physica*.**12**: 405–460. Bibcode:1946Phy....12..405G. doi:10.1016/S0031-8914(46)80059-4.**^**Banderier, Cyril; Bousquet-Mélou, Mireille; Denise, Alain; Flajolet, Philippe; Gardy, Danièle; Gouyou-Beauchamps, Dominique (2002), "Generating functions for generating trees",*Discrete Mathematics*,**246**(1–3): 29–55, arXiv:math/0411250, doi:10.1016/S0012-365X(01)00250-3, MR 1884885**^**Mehler, F. G. (1866), "Ueber die Entwicklung einer Function von beliebig vielen Variabeln nach Laplaceschen Functionen höherer Ordnung" [On the development of a function of arbitrarily many variables according to higher-order Laplace functions],*Journal für die Reine und Angewandte Mathematik*(in German) (66): 161–176, ISSN 0075-4102, ERAM 066.1720cj. See p. 174, eq. (18) and p. 173, eq. (13).**^**Erdélyi et al. 1955, p. 194, 10.13 (22).

## ReferencesEdit

- Abramowitz, Milton; Stegun, Irene Ann, eds. (1983) [June 1964]. "Chapter 22".
*Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables*. Applied Mathematics Series.**55**(Ninth reprint with additional corrections of tenth original printing with corrections (December 1972); first ed.). Washington D.C.; New York: United States Department of Commerce, National Bureau of Standards; Dover Publications. p. 773. ISBN 978-0-486-61272-0. LCCN 64-60036. MR 0167642. LCCN 65-12253. - Courant, Richard; Hilbert, David (1953),
*Methods of Mathematical Physics, Volume I*, Wiley-Interscience - Erdélyi, Arthur; Magnus, Wilhelm; Oberhettinger, Fritz; Tricomi, Francesco G. (1955),
*Higher transcendental functions*(PDF),**II**, McGraw-Hill - Fedoryuk, M.V. (2001) [1994], "Hermite functions", in Hazewinkel, Michiel,
*Encyclopedia of Mathematics*, Springer Science+Business Media B.V. / Kluwer Academic Publishers, ISBN 978-1-55608-010-4 - Koornwinder, Tom H.; Wong, Roderick S. C.; Koekoek, Roelof; Swarttouw, René F. (2010), "Orthogonal Polynomials", in Olver, Frank W. J.; Lozier, Daniel M.; Boisvert, Ronald F.; Clark, Charles W.,
*NIST Handbook of Mathematical Functions*, Cambridge University Press, ISBN 978-0521192255, MR 2723248 - Shohat; Hille; Walsh (1940).
*Bibliography on Hermite polynomials*. (2000 references) - Laplace, P. S. (1810),
*Mém. Cl. Sci. Math. Phys. Inst. France*,**58**: 279–347 Missing or empty`|title=`

(help) - Suetin, P. K. (2001) [1994], "H/h047010", in Hazewinkel, Michiel,
*Encyclopedia of Mathematics*, Springer Science+Business Media B.V. / Kluwer Academic Publishers, ISBN 978-1-55608-010-4 - Szegő, Gábor (1955) [1939],
*Orthogonal Polynomials*, American Mathematical Society - Wiener, Norbert (1958) [1933],
*The Fourier Integral and Certain of its Applications*(revised ed.), New York: Dover Publications, ISBN 0-486-60272-9 - Whittaker, E. T.; Watson, G. N. (1962), 4th, ed.,
*A Course of Modern Analysis*, London: Cambridge University Press - Temme, Nico (1996).
*Special Functions: An Introduction to the Classical Functions of Mathematical Physics*. New York: Wiley.^{[ISBN missing]}

## External linksEdit

- Weisstein, Eric W. "Hermite Polynomial".
*MathWorld*. - GNU Scientific Library — includes C version of Hermite polynomials, functions, their derivatives and zeros (see also GNU Scientific Library)