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American Journal of Physics

Consistent analogs of the Fourier uncertainty relation

G. W. Forbes, Miguel Angel Alonso

Published Oct 1, 2001• 11 citations
Publisher

Abstract

To resolve an issue that was raised in our earlier paper in this journal [69, 340–347 (2001)], a direct analog of the standard uncertainty relation is derived for the discrete Fourier transform (DFT). This inequality gives a simple lower bound for the degree of localization of the DFT of any sequence in terms of just the localization of the original sequence. It is also shown that the earlier uncertainty relations for the Fourier transform and the Fourier series can be derived from this new relation by taking appropriate limits. Because the same cannot be said of the others, this new relation is arguably the most fundamental of the three.

DOI
10.1119/1.1383599

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To resolve an issue that was raised in our earlier paper in this journal [69, 340–347 (2001)], a direct analog of the standard uncertainty relation is derived for the discrete Fourier transform (DFT). This inequality gives a simple lower bound for the degree of localization of the DFT of any sequence in terms of just the localization of the original sequence. It is also shown that the earlier uncertainty relations for the Fourier transform and the Fourier series can be derived from this new relation by taking appropriate limits. Because the same cannot be said of the others, this new relation is arguably the most fundamental of the three.
The conventional Fourier transform has a well-known uncertainty relation that is defined in terms of the first and second moments of both a function and its Fourier transform. It is also well known that Gaussian functions, when translated to an arbitrary centre and supplemented by a linear phase factor, provide a complete set of minimum uncertainty states (MUSs) that exactly achieves the lower bound set by this uncertainty relation. A similarly general set of MUSs and uncertainty relations are derived here for discrete and/or periodic generalizations of the Fourier transform, namely for the discrete Fourier transform and the Fourier series. These extensions require a modified definition for the width of a periodic distribution, and they lead to more complex uncertainty relations that turn out to depend on the centroid location and mean frequency of the distribution. The derivations lead to novel generalizations of Hermite–Gaussian functions and, like Gaussians, the MUSs can play a special role in a range of Fourier applications.
A physicist’s intuition in Fourier theory is generally established from the parallels between Fourier series and transforms. Remarkably, one element of this theory that is especially significant in physics, namely the uncertainty principle, is never treated for Fourier series. We resolve this by first showing that a natural measure of spread for a periodic distribution follows simply upon regarding the distribution as a mass density on a ring. Even though the centroid of this ring is expressed in terms of just a first moment, its distance from the geometric center gives a close analog of variance. We then derive direct analogs of the uncertainty principle for both the Fourier series of a continuous periodic function as well as the fast Fourier transform of discrete data. The results have similar applications to those of the standard uncertainty principle.
A sharper uncertainty inequality which exhibits a lower bound larger than that in the classical N -dimensional Heisenberg’s uncertainty principle is obtained, and extended from N -dimensional Fourier transform domain to two N -dimensional fractional Fourier transform domains. The conditions that reach the equality relation of the uncertainty inequalities are deduced. Example and simulation are performed to illustrate that the newly derived uncertainty principles are truly sharper than the existing ones in the literature. The new proposals’ applications in time-frequency analysis and optical system analysis are also given.
We derive an uncertainty relation for two unitary operators which obey a commutation relation of the form UV=e(i phi) VU. Its most important application is to constrain how much a quantum state can be localized simultaneously in two mutually unbiased bases related by a discrete fourier transform. It provides an uncertainty relation which smoothly interpolates between the well-known cases of the Pauli operators in two dimensions and the continuous variables position and momentum. This work also provides an uncertainty relation for modular variables, and could find applications in signal processing. In the finite dimensional case the minimum uncertainty states, discrete analogues of coherent and squeezed states, are minimum energy solutions of Harper's equation, a discrete version of the harmonic oscillator equation.
The focus of this article is to propose two different versions of the Heisenberg uncertainty principle related to the fractional Fourier transform (FrFT). The first version is directly derived using the basic connection between the traditional Fourier transform (FT) and the FrFT, and the second is derived by exploiting time differentiation property and Parseval’s formula for the FrFT. In addition, a weighted uncertainty inequality related to this transformation is investigated. As a simple illustration of the use of the obtained results, we design the fractional characteristic function. An inequality describing the relation between the probability density function and its fractional characteristic function is presented.