Harmonic analysis

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The harmonics of color. The harmonic-analysis chart shows how the different wavelengths interact with red light. At a difference of λ/2 (wavelength/2), red is perfectly in sync with its second-generation harmonic in the ultraviolet. All other wavelengths in the visual spectrum have less than a λ/2 difference between them, forming harmonic oscillations in the combined waves. At λ/14, the oscillations will cycle every fourteenth wave, while at λ/8 they will cycle every eighth. The oscillations are most rapid at λ/4, cycling every fourth wave, while at λ/3 they cycle every seventh wave, and at λ/2.5 they cycle every thirteenth. The lower section shows how the λ/4 harmonic interacts in visible light (green and red), as photographed in an optical flat.

Harmonic analysis is a branch of mathematics concerned with the representation of functions or signals as the superposition of basic waves, and the study of and generalization of the notions of Fourier series and Fourier transforms (i.e. an extended form of Fourier analysis). In the past two centuries, it has become a vast subject with applications in areas as diverse as signal processing, quantum mechanics, and neuroscience.

The term "harmonics" originated as the ancient Greek word, "harmonikos," meaning "skilled in music."[1] It arose in physical eigenvalue-problems to mean waves whose frequencies are integer multiples of one another, as are the frequencies of the harmonics of music notes, but the term has been generalized beyond its original meaning.

The classical Fourier transform on Rn is still an area of ongoing research, particularly concerning Fourier transformation on more general objects such as tempered distributions. For instance, if we impose some requirements on a distribution f, we can attempt to translate these requirements in terms of the Fourier transform of f. The Paley–Wiener theorem is an example of this. The Paley–Wiener theorem immediately implies that if f is a nonzero distribution of compact support (these include functions of compact support), then its Fourier transform is never compactly supported. This is a very elementary form of an uncertainty principle in a harmonic analysis setting. See also: Convergence of Fourier series.

Fourier series can be conveniently studied in the context of Hilbert spaces, which provides a connection between harmonic analysis and functional analysis.

Abstract harmonic analysis

One of the most modern branches of harmonic analysis, having its roots in the mid-twentieth century, is analysis on topological groups. The core motivating ideas are the various Fourier transforms, which can be generalized to a transform of functions defined on Hausdorff locally compact topological groups.

The theory for abelian locally compact groups is called Pontryagin duality.

Harmonic analysis studies the properties of that duality and Fourier transform, and attempts to extend those features to different settings, for instance to the case of non-abelian Lie groups.

For general non-abelian locally compact groups, harmonic analysis is closely related to the theory of unitary group representations. For compact groups, the Peter–Weyl theorem explains how one may get harmonics by choosing one irreducible representation out of each equivalence class of representations. This choice of harmonics enjoys some of the useful properties of the classical Fourier transform in terms of carrying convolutions to pointwise products, or otherwise showing a certain understanding of the underlying group structure. See also: Non-commutative harmonic analysis.

If the group is neither abelian nor compact, no general satisfactory theory is currently known. By "satisfactory" one would mean at least the equivalent of Plancherel theorem. However, many specific cases have been analyzed, for example SLn. In this case, representations in infinite dimensions play a crucial role.