I am nerd-sniped with the computability claims here. The last paragraph sums up what I think about what you wrote more broadly.

That description of a "hyper Turing machine" is pretty boring and ridiculous, such a machine trivially solves any computational problem we have because you can embed the problem into the transition function. Here is a sketch of how to do it: Let's call the heads on each tape 0, 1, ...; and let the input be on tape 0. Then the following is a machine that _decides_ a given language:

1. read the input and place the first symbol to tape 1, the second table to tape 2, ... . This takes a single step!

2. Read the whole input by reading a single symbol from each tape, and accept it if it is in the language. This can be done because the transition function can map each string to accept or reject state directly now.

Now, here is the kicker: there are uncountably many "hyper" Turing machines but only countably many strings, so almost all of these machines cannot be described, and there cannot be a universal "hyper" Turing machine. So, I don't think they are that interesting.

Note that the alphabet here is still finite, the infinity is handled by having infinitely many tapes (this is equivalent to going through the trouble of building up something like Goedel encoding). Moreover, I didn't specify the number of tapes here, but countably infinitely many tapes are enough, so you don't need to build an "uncountably-wide" tape. The point I'm trying to make is that if you let a Turing machine-like thing to have countably infinite descriptions, then the description may as well be "look up the solution" so it gets boring from that point on. We need only countably infinite descriptions because a language is countably infinite (because it is a subset of the set of all strings). If one tries to do some shenanigans like making the languages also have higher cardinalities, well just pump up the cardinality of the "hyper" Turing machine to match and you'd end up with the same proofs with slight changes.

> The alphabet our math uses is pretty much all finite. What percent of the axioms and theorems that you know are infinitely long? Shouldn't the overwhelming majority of axioms and theorems be infinitely long (and in particular map onto an uncountable set? (e.g. transcendental numbers).

As for this, we _want_ all of that (and proofs) to be finite. That gives a lot of nice structure we can work with when dealing with first-order logic and proving stuff like compactness and (in)completeness. All of our axioms and theorems are finite (assuming using FOL), we just have countably infinitely many of them (building countably infinitely many theorems is trivial, as for axioms: axiom schemas are just a countably infinite collection of axioms).

This was all to set the record straight when it comes to computability theory.
If you want tamer examples of hypercomputation, there is a lot of work on oracle machines and Turing machines that can take infinitely many steps. I think those would be better examples for the "we can reason about 'supra-mathematical' entities using plain old math." claim you are making. Although, I am not buying into this because these are all mathematical entities. We do mathematics because it is an interesting endeavor, and computability is important only in that it helps us understand the math we are doing (can we prove all "true" statements? can we devise an algorithm to solve X?), anything beyond that is still math, and a lot of the notions here (Turing machine as a proxy for algorithm, using first order logic, picking a particular set of axioms) are arbitrary choices that work well so that we can do math with a foundation that won't make us lose much sleep.