--- title: "Schwartz distribution" sort_title: "Schwartz distribution" date: 2021-02-25 categories: - Mathematics layout: "concept" --- A **Schwartz distribution**, also known as a **generalized function**, is a generalization of a function, allowing us to work with otherwise pathological definitions. Notable examples of distributions are the [Dirac delta function](/know/concept/dirac-delta-function/) and the [Heaviside step function](/know/concept/heaviside-step-function/), whose unusual properties are justified by this generalization. We define the **Schwartz space** $$\mathcal{S}$$ of functions, whose members are often called **test functions**. Every such $$\phi(x) \in \mathcal{S}$$ must satisfy the following constraint for any $$p, q \in \mathbb{N}$$: $$\begin{aligned} \mathrm{max} \big| x^p \phi^{(q)}(x) \big| < \infty \end{aligned}$$ In other words, a test function and its derivatives decay faster than any polynomial. Furthermore, all test functions must be infinitely differentiable. These are quite strict requirements. The **space of distributions** $$\mathcal{S}'$$ (note the prime) is then said to consist of *functionals* $$f[\phi]$$ which map a test function $$\phi$$ from $$\mathcal{S}$$, to a number from $$\mathbb{C}$$; this is often written as $$\Inprod{f}{\phi}$$. This notation looks like the inner product of a [Hilbert space](/know/concept/hilbert-space/), for good reason: any well-behaved function $$f(x)$$ can be embedded into $$\mathcal{S}'$$ by defining the corresponding functional $$f[\phi]$$ as follows: $$\begin{aligned} f[\phi] = \Inprod{f}{\phi} = \int_{-\infty}^\infty f(x) \: \phi(x) \dd{x} \end{aligned}$$ Not all functionals qualify for $$\mathcal{S}'$$: they also need to be linear in $$\phi$$, and **continuous**, which in this context means: if a series $$\phi_n$$ converges to $$\phi$$, then $$\Inprod{f}{\phi_n}$$ converges to $$\Inprod{f}{\phi}$$ for all $$f$$. The power of this generalization is that $$f(x)$$ does not need to be well-behaved: for example, the Dirac delta function can also be used, whose definition is nonsensical *outside* of an integral, but perfectly reasonable *inside* one. By treating it as a distribution, we gain the ability to sanely define e.g. its derivatives. Using the example of embedding a well-behaved function $$f(x)$$ into $$\mathcal{S}$$, we can work out what the derivative of a distribution is: $$\begin{aligned} \Inprod{f'}{\phi} = \int_{-\infty}^\infty f'(x) \: \phi(x) \dd{x} = \Big[ f(x) \: \phi(x) \Big]_{-\infty}^\infty - \int_{-\infty}^\infty f(x) \: \phi'(x) \dd{x} \end{aligned}$$ The test function removes the boundary term, yielding the result $$- \Inprod{f}{\phi'}$$. Although this was an example for a specific $$f(x)$$, we use it to define the derivative of any distribution: $$\begin{aligned} \boxed{ \Inprod{f'}{\phi} = - \Inprod{f}{\phi'} } \end{aligned}$$ Using the same trick, we can find the [Fourier transform](/know/concept/fourier-transform/) (FT) of a generalized function. We define the FT as follows, but be prepared for some switching of the names $$k$$ and $$x$$: $$\begin{aligned} \tilde{\phi}(x) = \int_{-\infty}^\infty \phi(k) \exp(- i k x) \dd{k} \end{aligned}$$ The FT of a Schwartz distribution $$f$$ then turns out to be as follows: $$\begin{aligned} \inprod{\tilde{f}}{\phi} &= \int_{-\infty}^\infty \tilde{f}(k) \: \phi(k) \dd{k} = \iint_{-\infty}^\infty f(x) \exp(- i k x) \: \phi(k) \dd{x} \dd{k} \\ &= \int_{-\infty}^\infty f(x) \: \tilde{\phi}(x) \dd{x} = \inprod{f}{\tilde{\phi}} \end{aligned}$$ Note that the ordinary FT $$\tilde{f}(k) = \hat{\mathcal{F}}\{f(x)\}$$ is already a 1:1 mapping of test functions $$\phi \leftrightarrow \tilde{\phi}$$. As it turns out, in this generalization it is also a 1:1 mapping of distributions in $$\mathcal{S}'$$, defined as: $$\begin{aligned} \boxed{ \inprod{\tilde{f}}{\phi} = \inprod{f}{\tilde{\phi}} } \end{aligned}$$ ## References 1. K.W. Jacobsen, *Note on generalized functions (distributions)*, 2020, unpublished.