Eigenfunction

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This solution of the vibrating drum problem is, at any point in time, an eigenfunction of the Laplace operator on a disk.

In mathematics, an eigenfunction of a linear operator, A, defined on some function space, is any non-zero function f in that space that returns from the operator exactly as is, except for a multiplicative scaling factor. More precisely, one has

A f = \lambda f

for some scalar, λ, the corresponding eigenvalue. The solution of the differential eigenvalue problem also depends on any boundary conditions required of f. In each case there are only certain eigenvalues λ = λn (n = 1, 2, 3, ...) that admit a corresponding solution for f  =  fn (with each fn belonging to the eigenvalue λn) when combined with the boundary conditions. Eigenfunctions are used to analyze A.

For example, fk (x) = ekx is an eigenfunction for the differential operator

A = \frac{d^2}{dx^2}

for any value of k, with corresponding eigenvalue λ = k2. Similarly, the functions  sin(kx) and  cos(kx), have eigenvalue λ = -k2. If a boundary condition is applied to this system (e.g., f(0)  = 0 or f(0)  = 3), then even fewer pairs of eigenfunctions and eigenvalues satisfy both the definition of an eigenfunction, and the boundary conditions.

Specifically, in the study of signals and systems, the eigenfunction of a system is the signal f (t) which when input into the system, produces a response y(t) = λ f (t) with the complex constant λ.[1]

Examples

Derivative operator

A widely used class of linear operators acting on function spaces are the differential operators on function spaces. As an example, on the space C of infinitely differentiable real functions of a real argument t, the process of differentiation is a linear operator since

\frac{d}{dt}(af+bg) = a \frac{df}{dt} + b \frac{dg}{dt}, \qquad f,g \in C^{\infty}, \quad a,b \in \mathbf{R}.

The eigenvalue equation for a linear differential operator D in C is then a differential equation

D f = \lambda f

The functions that satisfy this equation are commonly called eigenfunctions. For the derivative operator <templatestyles src="Sfrac/styles.css" />d/dt, an eigenfunction is a function that, when differentiated, yields a constant times the original function. That is,

\frac{d}{dt} f(t) = \lambda f(t)

for all t. This equation can be solved for any value of λ. The solution is an exponential function

f(t) = Ae^{\lambda t}.

The derivative operator is defined also for complex-valued functions of a complex argument. In the complex version of the space C, the eigenvalue equation has a solution for any complex constant λ. The spectrum of the operator <templatestyles src="Sfrac/styles.css" />d/dt is therefore the whole complex plane. This is an example of a continuous spectrum.

Applications

Vibrating strings

The shape of a standing wave in a string fixed at its boundaries is an example of an eigenfunction of a differential operator. The admissible eigenvalues are governed by the length of the string and determine the frequency of oscillation.

Let h(x, t) denote the sideways displacement of a stressed elastic chord, such as the vibrating strings of a string instrument, as a function of the position x along the string and of time t. From the laws of mechanics, applied to infinitesimal portions of the string, one can deduce that the function h satisfies the partial differential equation

\frac{\partial^2 h}{\partial t^2} = c^2\frac{\partial^2 h}{\partial x^2},

which is called the (one-dimensional) wave equation. Here c is a constant that depends on the tension and mass of the string.

This problem is amenable to the method of separation of variables. If we assume that h(x, t) can be written as the product of the form X(x)T(t), we can form a pair of ordinary differential equations:

\frac{d^2}{dx^2}X=-\frac{\omega^2}{c^2}X \qquad \frac{d^2}{dt^2}T=-\omega^2 T.

Each of these is an eigenvalue equation, for eigenvalues -\tfrac{\omega^2}{c^2} and ω2, respectively. For any values of ω and c, the equations are satisfied by the functions

X(x) = \sin \left(\frac{\omega x}{c} + \varphi \right),
T(t) = \sin(\omega t + \psi),

where φ and ψ are arbitrary real constants. If we impose boundary conditions (that the ends of the string are fixed with X(x) = 0 at x = 0 and x = L, for example) we can constrain the eigenvalues. For those boundary conditions, we find sin(φ) = 0, and so the phase angle φ = 0 and

\sin\left(\frac{\omega L}{c}\right) = 0.

Thus, the constant ω is constrained to take one of the values ωn = <templatestyles src="Sfrac/styles.css" />ncπ/L, where n is any integer. Thus, the clamped string supports a family of standing waves of the form

h(x,t) = \sin \left (\frac{n\pi x}{L} \right )\sin(\omega_n t).

From the point of view of our musical instrument, the frequency ωn is the frequency of the n-th harmonic, which is called the (n − 1)-th overtone.

Quantum mechanics

Eigenfunctions play an important role in many branches of physics. An important example is quantum mechanics, where the Schrödinger equation

 H\psi = E \psi,

with

 H = -\frac{\hbar^2}{2m}\nabla^2+ V(\mathbf{r},t)

has solutions of the form

\psi(t) = \sum_k e^{-\frac{i E_k t}{\hbar}} \varphi_k,

where φk are eigenfunctions of the operator H with eigenvalues Ek. The fact that only certain eigenvalues Ek with associated eigenfunctions φk satisfy Schrödinger's equation leads to a natural basis for quantum mechanics and the periodic table of the elements, with each Ek an allowable energy state of the system. The success of this equation in explaining the spectral characteristics of hydrogen is considered one of the greatest triumphs of 20th century physics.

Since the Hamiltonian operator H is a Hermitian Operator, its eigenfunctions are orthogonal functions. This is not necessarily the case for eigenfunctions of other operators (such as the example A mentioned above). Orthogonal functions fi  (i = 1, 2, ...) have the property that

0 = \langle f_i , f_j \rangle = \int d \mathbf{r} \overline{f_i} f_j

where fi is the complex conjugate of fi.

whenever ij, in which case the set { fi  | iI} is said to be orthogonal. Also, it is linearly independent.

See also

Notes

  1. Bernd Girod, Rudolf Rabenstein, Alexander Stenger, Signals and systems, 2nd ed., Wiley, 2001, ISBN 0-471-98800-6 p. 49

References

External links