Fourier inversion theorem (${\mathcal{F}}^{-1}$)

The Fourier inversion theorem makes decomposition into frequencies reversible: a complete Fourier transform, including its wave phases, determines the original function up to equality almost everywhere. With the angular-frequency conventionif $f$ and $\hat{f}$ belong to the L1 space, thenalmost everywhere. The right side is a continuous representative of $f$. If $f$ itself is continuous, equality holds everywhere, as explained by the continuous version of Fourier inversion. The integrability hypotheses ensure that both displayed integrals are ordinary absolutely convergent integrals. For arbitrary elements of the L2 space, the Plancherel theorem instead supplies inversion in the L2 space norm.

Each factor $e^{ix\cdot \xi }$ is a Fourier mode; the inverse integral adds them with the complex weights $\hat{f}(\xi )/(2\pi {)}^n$. The normalization is part of the recipe. In one dimension, writing ordinary frequency as $\nu =\xi /(2\pi )$ gives the equivalent pairwhere $F(\nu )=\hat{f}(2\pi \nu )$. Reversing both exponential signs gives another equivalent convention, but the forward and inverse formulas must use opposite signs consistently.

For example, the Fourier transform of a Gaussian givesFourier inversion says that a weighted continuum of oscillations reconstructs this smooth Gaussian function. Narrowing the original Gaussian function by increasing $a$ broadens its frequency spectrum. This is a concrete demonstration that a sharply localized shape needs a wider range of frequencies.

Inversion is what makes a frequency calculation useful: transform a function, solve the simpler problem there, then return to the original variables. A brief proof outline is to multiply $\hat{f}(\xi )$ by $e^{-ϵ|\xi {|}^2}$, $ϵ>0$. The inverse integral becomes convolution with a normalized Gaussian function, an approximate identity. As $ϵ$ tends to zero, dominated convergence gives the unregularized inverse integral, while the approximate identity recovers $f$ almost everywhere. Joseph Fourier's Théorie analytique de la chaleur (1822), Chapter IX, article 417, contains a cosine double-integral representation antecedent to this modern formula; the hypotheses above are the modern statement.^[ref]

When $\hat{f}\in L^1$, its inverse Fourier integral is continuous by dominated convergence. If $f$ is also continuous and Fourier inversion identifies the two functions almost everywhere, then they agree everywhere.

For a Schwartz function, with the angular-frequency convention,More generally, the identity holds when integration by parts is justified and the boundary term vanishes. Repeated differentiation gives $\widehat{f^{(m)}}(k)=(ik{)}^m\hat{f}(k)$. The short proof transfers the derivative from $f$ to $e^{-ikx}$ by integration by parts. High frequencies receive larger multipliers, so rapid ripples contribute more strongly to a derivative. For the heat equation, the second derivative becomes multiplication by $-k^2$, directly explaining the faster decay of fine spatial structure.

For the angular-frequency convention,Consequently cosine transforms to the half-sum of the two shifted deltas, while sine transforms to their signed difference divided by $2i$.

For an integrable function and the angular-frequency convention,so a translation multiplies each frequency component by a factor of modulus one. The amplitude of every component stays the same, while its wave phase changes by $-ka$. For example, delaying $\cos (2\pi \nu t)$ by $a$ produces $\cos (2\pi \nu t-2\pi \nu a)$: faster oscillations accumulate a larger wave phase shift for the same delay. Substituting $y=x-a$ in the defining Fourier transform is the entire proof. Conversely, this multiplier in the Fourier transform produces a translation after Fourier inversion.