Hilbert Space: Treating Functions as Vectors
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Regulars are buzzing about a fascinating exploration of Hilbert space, where functions are treated as vectors, opening up new perspectives on mathematical concepts. Commenters riff on the implications of this abstract algebra technique, with some highlighting its connections to signal processing and quantum mechanics. As the discussion unfolds, a consensus emerges around the power of Hilbert space to unify disparate mathematical disciplines, with some debating the trade-offs between rigor and intuition in presenting these complex ideas. The thread feels particularly relevant right now, as researchers continue to push the boundaries of mathematical modeling in fields like physics and engineering.
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How can an uncountably infinite set be used as an index? I was fine with natural numbers (countably infinite) being an index obv, but a real seems a stretch. I get the mathematical definition of a function, but again, this feels like we suddenly lose the plot…
One way to think about it is that, even though you're defining an index that permits infinite amounts of subdivision, from any given house there's always a "next house up" in the vector: you can move up one space.
In a real-indexed vector, that notion doesn't apply. It's "infinity plus one" all the way down: whatever real value you pick to start with, x, there's no delta small enough to add to it such that there's no number between x and x+d.
Just to clarify, uncountability isn't necessary for this. It's true for the rational numbers too, which are countable.
I think the only thing that matters is that the indices have an ordering (which the reals obviously do) and they aren’t irrational (i.e. they have a finite precision).
Imagine you have a real number, say, e.g. 2.4. What stops us from using that as an index into an infinite, infinitely resizable list? 2.4^2 = 5.76. Depending on how fine-grained your application requires you could say 2.41 (=5.8081) is the next index OR 2.5 (=6.25) is the next index we look at or care about.
I could be misunderstanding it, though.
> and they aren’t irrational (i.e. they have a finite precision)
No, if you want only rational "indices", then your vector space has a countable basis. Interesting vector spaces in analysis are uncountably infinite dimensional. (And for this reason the usual notion of a basis is not very useful in this context.)
I'm not sure if I'm misunderstanding what you mean by 'finite precision' but the ordinary meaning of those words would seem to limit it to rational numbers?
The point is that we need some way to deal with objects that are inherently infinite-dimensional.
Asking where the smallest greater number (next number) is no longer makes sense.
Taking two numbers and asking whether one is greater than the other still makes sense. (and hence also whether they are equal)
Taking two numbers and asking how far separated from each other still makes sense.
You may already observe some uses for indexes in programming that don't use all of these properties of an index. For example, the index of a hash set "only cares about equality", and "the next index" may be an unfilled address in a hash set.
It is just unhelpful in many ways. It fixates on one particular basis and it results in a vector space with few applications and it can not explain many of the most important function vector spaces, which are of course the L^p spaces.
In most function vector spaces you encounter in mathematics, you can not say what the value of a function at a point is. They are not defined that way.
The right didactic way, in my experience, is introducing vector spaces first. Vectors are elements of vector spaces, not because they can be written in any particular basis, but because they fulfill the formal definition. And because they fullfil the formal definition they can be written in a basis.
Except just about all relevant applications that exist in computer science and physics where fixating on a representation is the standard.
If you want to talk about applications, then this representation is especially bad. Since the intuition it gives is just straight up false.
> We are in a geometry class. The teacher dictates: “A circle is the locus of points in the plane that are at the same distance from an interior point called the center.” The good student writes this sentence in his notebook; the bad student draws little stick figures in it; but neither one has understood. So the teacher takes the chalk and draws a circle on the board. “Ah!” think the students, “why didn’t he say right away: a circle is a round shape — we would have understood.”
> No doubt, it is the teacher who is right. The students’ definition would have been worthless, since it could not have served for any demonstration, and above all because it would not have given them the salutary habit of analyzing their conceptions. But they should be shown that they do not understand what they think they understand, and led to recognize the crudeness of their primitive notion, to desire on their own that it be refined and improved.
The learning comes from making the mistake and being corrected, not from being taught the definition, I think.
Anyway, it's from Science and Method, Book 2 https://fr.wikisource.org/wiki/Science_et_m%C3%A9thode/Livre...
There's more to the section that talks about the subject. I just find this particular paragraph amusingly germane.
Functions are actually a great motivating example for the definition of a vector space, precisely because they are first look nothing like what student think of as a vector.
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