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I am studying eigenvalues and eigenvectors of operators on infinite-dimensional spaces, and I am struggling to understand generalized eigenvectors.

In order to explain myself better, I'm going to refer to an exercise we did during class. We had to find a basis for $L^2(R)$ using eigenvectors and generalized eigenvectors of the operator $P=-i\frac{d}{dx}$ defined on $D=\{f, f' \in L^2(R), f \space absolutely\space continuous\}$. In this way, P is self-adjoint. So we use the eigenvalues equation: $$-i\frac{df}{dx}=\lambda f$$ And we find the eigenvectors: $$f_n=a_\lambda e^{i\lambda x}$$ where $\lambda$ is a real number and $a_\lambda$ is a coefficient. These functions though $\notin L^2(R)$, so they're generalized eigenvectors and they're part of the continuous spectrum.

And this is the part I didn't understand. First of all, during lesson, my professor said that generalized eigenvectors are not functions but distributions.

My first doubt is the following: she said that $L^2(R) \subset S'(R)$ (where $S'(R)$ is the space of tempered distributions) and that $L^2(R)$ is dense in $S'(R)$. So, I know distributions are also known as generalized functions, but I really don't understand why, and I don't understand in which way we can say that $L^2(R)$ that is a space of functions can be included in a space of distributions. So, in particular, knowing that the generalized eigenvector we found should be a distribution, I don't understand how $f_n=a_\lambda e^{i\lambda x}$ can be seen as a distribution.

I get the idea that $$\int_{-\infty}^{+\infty}|f_n(x)|^2dx$$ is infinite, while $$\int_{-\infty}^{+\infty}|f_n(x)\phi(x)|^2dx$$ where $\phi$ is a test function, is finite. But we defined a distribution as follows: $$T_f(\phi)=\int_{-\infty}^{+\infty}f(x)\phi(x)dx$$ So if T is defined as that integral, how can it be seen as a function?

In addition, we also said that, for a self-adjoint operator, the set of the eigenvectors united to the set of the generalized eigenvectors forms an orthogonal basis of $L^2(R)$: but how is it possible that the generalized eigenvectors, which are not in $L^2(R)$, are a part of its basis?

Fede
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  • Not a complete answer but a nice reference for the first question: https://math.stackexchange.com/a/1946353/998803 – Andreas Tsevas Jun 02 '23 at 16:41
  • Well, $\Psi_{\lambda}(x)=e^{i\lambda x}$ cannot be a basis for $L^2(\mathbb{R})$ since they are not square integrable functions. Making an appropriate basis out of these generalized eigenvectors may require a "smoothing procedure" that makes them $L^2$ integrable see the answer by DisintegratingByParts here – K. Grammatikos Jun 02 '23 at 17:02
  • How to see functions as distributions: https://math.stackexchange.com/questions/4527480/proof-that-the-dirac-delta-function-is-the-sum-of-exponentials-distributions-up/ – LL 3.14 Jun 03 '23 at 02:54

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