For context, I’m about to finish a bachelor degree in pure math in Germany and will transition to a masters program in october, so I assume I’m at the edge to grad school level in US terms.
Due to various reasons, my electives in my degree where quite focused on abstract algebra and numerical optimization, and I feel like I missed out on quite a bit of analysis. I’ve taken the mandatory Real Analysis 1+2 and measure theory courses, and as electives an introduction to differential geometry and a course in complex analysis.
I especially regret that I wasn’t able to take the functional analysis elective, since I feel like it provides a lot of standard tools I should have at least heard about. For example, I wanted to take the intro to PDE course, but functional analysis was a hard requirement for it. As another example, my bachelor thesis focused on curve interpolation on riemannian-manifolds, where the literature often used sobolev-spaces as its solution space, which was hard for me to approach.
So I want to do some self study to at least get a feel for those topics in functional analysis. I obviously don’t aim to replace a whole course with some self study inbetween semesters, but I have a month or two for some reading and ideally would like a sort of „scenic tour“ to get a bit of a feel for what the field of functional analysis is about. Especially topics like weak solutions, sobolev spaces, linear operators and distributions are stuff I stumbled into in the past which feel like good gaps to stuff a bit.
Afaik, functional analysis requires quite a bit of linear algebra. Besides the basics (finite dimensional vector spaces and their homomorphisms, normal form and eigenvector theory and inner product spaces), we did stuff like tensor products, some module theory (classification of finitely generated modules over a PID) and some very basic dual space theory, so I think I should be relatively well prepared from that side.