Fourier Methods - Main Theorem
The convergence and inversion theorems for Fourier series and transforms establish when these representations are valid and how they can be used rigorously.
TheoremFourier Inversion Theorem
Let fβL1(Rn) with f^ββL1(Rn). Then for almost every x:
f(x)=β«Rnβf^β(ΞΎ)e2Οixβ
ΞΎdΞΎ
If additionally f is continuous, this holds for all x.
This theorem guarantees that the Fourier transform is invertible under appropriate conditions, making it a legitimate tool for solving PDEs.
TheoremPlancherel's Theorem
The Fourier transform extends uniquely from L1β©L2 to a unitary operator on L2(Rn):
F:L2(Rn)βL2(Rn)
satisfying β₯F[f]β₯L2β=β₯fβ₯L2β and Fβ1=Fβ (adjoint).
Moreover, for f,gβL2:
β«Rnβf(x)g(x)βdx=β«Rnβf^β(ΞΎ)g^β(ΞΎ)βdΞΎ
Remark
Plancherel's theorem is crucial for PDE theory because PDEs preserve energy (measured in L2), and Fourier transform preserves this structure. It allows us to work in whichever space (physical or frequency) is more convenient.
TheoremPointwise Convergence of Fourier Series
Let f be piecewise smooth and 2Ο-periodic. Then the Fourier series converges pointwise to:
21β[f(x+)+f(xβ)]
where f(x+) and f(xβ) are right and left limits.
If f is continuous at x, the series converges to f(x).
TheoremSobolev Embedding via Fourier Transform
For fβHs(Rn) (Sobolev space with s derivatives in L2), defined by:
β₯fβ₯Hs2β=β«Rnβ(1+β£ΞΎβ£2)sβ£f^β(ΞΎ)β£2dΞΎ<β
If s>n/2, then fβC0(Rn)β©Lβ and:
β£f(x)β£β€Cβ₯fβ₯Hsβ
This explains why solutions with sufficient regularity in Sobolev spaces are automatically continuous.
These foundational theorems justify using Fourier methods rigorously and reveal deep connections between regularity in physical space and decay in frequency space.