Math 2.0

Integral transforms, operational calculus Radon transform and tomography Theorem

Helgason support theorem

Builds on Radon transform

Statement

Let n≥2n \ge 2 and let f ⁣:ℝn→ℂf \colon \R^n \to \C be continuous and rapidly decreasing, that is, ∣x∣kf(x)\abs{x}^k f(x) is bounded on ℝn\R^n for every integer k≥0k \ge 0. Let K⊆ℝnK \subseteq \R^n be a compact convex set. Assume that the Radon transform of ff vanishes on every hyperplane that does not meet KK. That is, Rf(θ,s)=0R f(\theta, s) = 0 whenever the hyperplane x⋅θ=sx \cdot \theta = s is disjoint from KK. Then f(x)=0f(x) = 0 for every x∉Kx \notin K.

Remarks

The decay hypothesis cannot be dropped. In ℝ2=ℂ\R^2 = \C, let k≥2k \ge 2 be an integer and let ff be continuous with f(z)=z−kf(z) = z^{-k} for ∣z∣≥1\abs{z} \ge 1. Take a line z=z0+twz = z_0 + t w, t∈ℝt \in \R, that misses the closed unit disk. The function t↦(z0+tw)−kt \mapsto (z_0 + tw)^{-k} has its only pole off the real axis, and it decays like ∣t∣−k\abs{t}^{-k}. Closing the contour in the half-plane without the pole gives integral 00. So RfR f vanishes on all lines missing the unit disk, while f≠0f \ne 0 outside it; here ∣x∣kf(x)\abs{x}^k f(x) is bounded but ∣x∣k+1f(x)\abs{x}^{k+1} f(x) is not.

The convexity of KK is also needed. The hyperplanes that miss a compact set are those that miss its convex hull, so the data can only locate the support up to the convex hull.

Going deeper

For a student

The theorem gives the exterior problem of tomography its uniqueness: a body is determined outside a convex obstacle by the lines that avoid the obstacle. It is a sharper form of injectivity of the Radon transform, local in the set of hyperplanes. The example with z−kz^{-k} shows that rapid decrease is the right hypothesis. The theorem is due to Helgason and has analogues for Radon transforms on symmetric spaces.

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To understand this page from the ground up, read these 2 pages in order. The foundations come first.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Radon_transform
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AboutRadon transform
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