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Convergence of Distributions to the Dirac Delta Distribution 📂Distribution Theory

Convergence of Distributions to the Dirac Delta Distribution

Theorem1

Let’s assume that ff is a function satisfying Rnf(x)dx=1\int_{\mathbb{R}^{n}} f(\mathbf{x})d\mathbf{x}=1. And let fϵ(x)=1ϵnf(xϵ)f_{\epsilon}(\mathbf{x})=\dfrac{ 1 }{ \epsilon^{n} }f\left( \dfrac{\mathbf{x}}{\epsilon} \right). Then, the corresponding regular antifunction Tϵ=TfϵT_{\epsilon}=T_{f_{\epsilon}} of ff weakly converges to the Dirac delta antifunction. That is, the following holds.

limϵ0Tϵ=δ \lim \limits_{\epsilon \to 0} T_{\epsilon}=\delta

Proof

Let f~(x)=f(x)\tilde{f}(\mathbf{x})=f(-\mathbf{x}). Then, the following holds.

fϵ~(x)=1ϵf(xϵ)andRnfϵ~dx=1 \tilde{f_{\epsilon}}(\mathbf{x})=\frac{1}{\epsilon}f\left( -\frac{\mathbf{x}}{\epsilon} \right) \quad \text{and} \quad \int_{\mathbb{R}^{n}}\tilde{f_{\epsilon}}d\mathbf{x}=1

Furthermore, the test function ϕ\phi is a continuous function with a compact support and therefore is bounded. Thus, according to the convolution convergence theorem, the following holds.

limϵ0ϕfϵ~(x)=ϕ(x)xRn \lim \limits_{\epsilon \to 0} \phi * \tilde{f_{\epsilon}} (\mathbf{x})=\phi (\mathbf{x})\quad \forall \mathbf{x} \in \mathbb{R}^{n}

Therefore, for any test function ϕ\phi, the following holds.

$$ \begin{align*} \lim \limits _{\epsilon \to 0} T_{\epsilon}(\phi) &=\lim \limits_{\epsilon \to 0} \int f_{\epsilon}(\mathbf{x})\phi (\mathbf{x})d\mathbf{x} \\ &=\lim \limits_{\epsilon \to 0} \int \tilde{f_{\epsilon}}(\mathbf{0}-\mathbf{x})\phi (\mathbf{x})d\mathbf{x} \\ &= \lim \limits_{\epsilon \to 0} \tilde{f_{\epsilon}}\phi (\mathbf{0}) \\ &=\phi (\mathbf{0}) \\ &=\delta (\phi) \end{align} $$

Thus, it is as follows.

Tϵwδ T_{\epsilon} \overset{\text{w}}{\to} \delta


  1. Gerald B. Folland, Fourier Analysis and Its Applications (1992), p314 ↩︎