Completeness of orthonormal functions

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In summary, the completeness condition for a set of orthonormal functions in a function space, as given by Jackson, is expressed as the summation of the product of the complex conjugate of the functions and the functions themselves being equal to the Dirac delta function. This condition allows us to expand any function in the space in terms of these orthonormal functions. However, if this summation does not go to zero, it means that the orthogonal functions do not span the entire space. In vector space, there is a corresponding relation that can provide a better understanding of this concept, known as Dirac's formalism of bras and kets.
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Karthiksrao
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In many areas (say, electrodynamics) we come across expansions of any function in terms of a series of orthonormal functions that span the space. Now the condition for completeness of a set of orthonormal functions in that space is given by (as given in Jackson)

[tex]\sum_{n=1}^\infty U_n^*(x') U_n(x) = \delta(x'-x)[/tex]

where x and x' are two points in the function space.

I am not able to understand what this is intuitively due to.

Why would the orthogonal functions not span the entire space if the summation does not go to zero ?

Finally, is there a corresponding relation in vector space ? That will probably give me a better understanding of what is happening, if we extend it to function space..

Thanks a ton!
 
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  • #2
Karthiksrao said:
In many areas (say, electrodynamics) we come across expansions of any function in terms of a series of orthonormal functions that span the space. Now the condition for completeness of a set of orthonormal functions in that space is given by (as given in Jackson)

[tex]\sum_{n=1}^\infty U_n^*(x') U_n(x) = \delta(x'-x)[/tex]

where x and x' are two points in the function space.

I am not able to understand what this is intuitively due to.

Why would the orthogonal functions not span the entire space if the summation does not go to zero ?

Finally, is there a corresponding relation in vector space ? That will probably give me a better understanding of what is happening, if we extend it to function space..

Thanks a ton!

I strongly suggest you to study the Dirac's formalism of bras and kets, it makes all theese relations much clearer.

Anyway, if U_n is complete and orthonormal, you must have, for every f belonging to the space:

[itex]f=\sum_nU_n(U_n,f)[/itex]

or, in the x-representation

[itex]f(x)=\sum_n U_n(x)\int U^*_N(x')f(x')dx'[/itex]

but we also have

[itex]f(x)=\int f(x')\delta(x-x')dx'[/itex]

so...
 

Related to Completeness of orthonormal functions

1. What is the definition of completeness of orthonormal functions?

Completeness of orthonormal functions is a mathematical concept that refers to a set of functions that are both orthogonal and normalized. This means that the functions are mutually perpendicular and have a magnitude of 1. When a set of orthonormal functions is complete, it means that any function can be expressed as a linear combination of these functions.

2. How is the completeness of orthonormal functions useful in mathematics and science?

The completeness of orthonormal functions is useful in many branches of mathematics and science, including calculus, linear algebra, and quantum mechanics. It allows for the representation of complex functions in terms of simpler, orthogonal functions, making calculations and analyses easier and more efficient.

3. Can a set of orthonormal functions be both complete and infinite?

Yes, a set of orthonormal functions can be both complete and infinite. In fact, many commonly used sets of orthonormal functions, such as the Fourier series and the Legendre polynomials, are infinite.

4. How is the completeness of orthonormal functions proven?

The completeness of orthonormal functions is typically proven using mathematical methods, such as the Gram-Schmidt process or the Parseval's identity. These methods involve showing that any function can be represented as a linear combination of the orthonormal functions, and that the coefficients of this representation can be determined using the inner product of the functions.

5. What are some real-world applications of the completeness of orthonormal functions?

The completeness of orthonormal functions has numerous real-world applications, including image and signal processing, data compression, and solving differential equations. It is also used in fields such as optics, acoustics, and quantum mechanics to describe the behavior of waves and particles.

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