(mathematics) Also known as characteristic function. An eigenvector for a linear operator on a vector space whose vectors are functions. Also known as proper function. A solution to the Sturm-Liouville partial differential equation.
| Sci-Tech Dictionary: eigenfunction |
(mathematics) Also known as characteristic function. An eigenvector for a linear operator on a vector space whose vectors are functions. Also known as proper function. A solution to the Sturm-Liouville partial differential equation.
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| Sci-Tech Encyclopedia: Eigenfunction |
One of the solutions of an eigenvalue equation. A parameter-dependent equation that possesses nonvanishing solutions only for particular values (eigenvalues) of the parameter is an eigenvalue equation, the associated solutions being the eigenfunctions (sometimes eigenvectors). In older usage the terms characteristic equation and characteristic values (functions) are common. Eigenvalue equations appear in many contexts, including the solution of systems of linear algebraic equations (matrix equations), differential or partial differential equations, and integral equations. The importance of eigenfunctions and eigenvalues in applied mathematics results from the widespread applicability of linear equations as exact or approximate descriptions of physical systems. However, the most fundamental application of these concepts is in quantum mechanics where they enter into the definition and physical interpretation of the theory. Only linear eigenvalue equations will be discussed. See also Eigenvalue (quantum mechanics); Energy level (quantum mechanics);
| Wikipedia: Eigenfunction |
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

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. The existence of eigenfunctions is typically the most insightful way to analyze A.
For example, fk(x) = ekx is an eigenfunction for the differential operator

for any value of k, with a corresponding eigenvalue λ = k2 − k. If boundary conditions are applied to this system (e.g., f = 0 at two physical locations in space), then only certain values of k = kn satisfy the boundary conditions, generating corresponding discrete eigenvalues
.
Specifically, in signals and systems, the eigenfunction of a system is the signal f(t) which when input into the system, produces a response y(t) = λf(t) with the complex constant λ.
Eigenfunctions play an important role in many branches of physics. An important example is quantum mechanics, where the Schrödinger equation
,
with

has solutions of the form

where φk are eigenfunctions of the operator
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 great triumphs of 20th century physics.
Due to the nature of the Hamiltonian 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,
have the property that

where
is the complex conjugate of fi
whenever
, in which case the set
is said to be orthogonal. Also, it is linearly independent.
This entry is from Wikipedia, the leading user-contributed encyclopedia. It may not have been reviewed by professional editors (see full disclaimer)
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