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Joined 1 year ago
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Cake day: July 2nd, 2023

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  • applied mathematics can get very messy: it requires performing a bunch of computations, optimizing the crap out of things, and solving tons of equations. you have to deal with actual numbers (the horror), and you have to worry about rounding errors and stuff like that.

    whereas in theoretical math, it’s just playing. you don’t need to find “exact solutions”, you just need to show that one exists. or you can show a solution doesn’t exist. sometimes you can even prove that it’s impossible to know if a solution exists, and that’s fine too. theoretical math is focused more on stuff like “what if we could formalize the concept of infinity plus one?”, or “how can we sidestep Russel’s paradox?”, or “can we turn a sphere inside out?”, or The Hairy Ball Theorem, or The Ham Sandwich Theorem, or The Snake Lemma.

    if you want to read more about what pure math is like, i strongly recommend reading A Mathematician’s Lament by Paul Lockhart. it is extremely readable (no math background required), and i thought it was pretty entertaining too.



  • yeah this is true. i should have clarified a bit better that a well ordering wouldn’t give you a “least gay” person in that sense of the word. it would be more correct to say there is a well ordering ⊰, and so there is a “⊰”-least gay person. but of course a “⊰”-least gay person could be in the middle of that spectrum.

    but the number of people on earth is finite, so in fact the usual ordering is a well-ordering in this case. so i guess those two mistakes i made cancel each other out, and the axiom of choice isn’t even needed here.




  • Infinite-dimensional vector spaces also show up in another context: functional analysis.

    If you stretch your imagination a bit, then you can think of vectors as functions. A (real) n-dimensional vector is a list of numbers (v1, v2, …, vn), which can be thought of as a function {1, 2, …, n} → ℝ, where k ∊ {1, …, n} gets sent to vk. So, an n-dimensional (real) vector space is a collection of functions {1, 2, …, n} -> ℝ, where you can add two functions together and multiply functions by a real number.

    Under this interpretation, the idea of “infinite-dimensional” vector spaces becomes much more reasonable (in my opinion anyway), since it’s not too hard to imagine that there are situations where you want to look at functions with an infinite domain. For example, you can think of an infinite sequence of numbers as a function with infinite domain. (i.e., an infinite sequence (v1, v2, …) is a function ℕ → ℝ, where k ∊ ℕ gets sent to vk.)

    and this idea works for both “countable” and “uncountable” “vectors”. i.e., you can use this framework to study a vector space where each “vector” is a function f: ℝ → ℝ. why would you want do this? because in this setting, integration and differentiation are linear maps. (e.g., if f, g: ℝ → ℝ are “vectors”, then D(f + g) = Df + Dg, and ∫*(f+g) = ∫f + ∫g, where D denotes taking the derivative.)




  • from a topological perspective, wraps and tacos are two different beasts.

    in a wrap, the bread completely surrounds (and encloses) the other ingredients, so theres a 2-dimensional hole involved (which basically means the inside is hollow).

    in a taco, no such wholes are present.

    you can also distinguish sandwiches from tacos and wraps (since sandwiches involve two pieces of bread, like you said). but unfortunately, you can’t topologically distinguish a burger from a sandwich


  • it is possible to rigorously say that 1/0 = ∞. this is commonly occurs in complex analysis when you look at things as being defined on the Riemann sphere instead of the complex plane. thinking of things as taking place on a sphere also helps to avoid the “positive”/“negative” problem: as |x| shrinks, 1 / |x| increases, so you eventually reach the top of the sphere, which is the point at infinity.