wrote about why I like algebra over analysis

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content/blog/rank-select/post.md

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+date = 2018-10-16T17:01:00+05:30
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content/blog/reading-kmett-structs.md

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 title = "Reading Kmett's `structs` library"
 date = "2018-10-04T19:53:32+05:30"
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content/blog/this-month-in-simplexhc-dec-2017.md

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 title = "This Month in Simplexhc"
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content/blog/why-i-like-algebra.md

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-title = "Why-I-Like-Algebra"
+title = "Why I like algebra over analysis"
 date = "2018-09-20T02:41:47+05:30"
-draft = true
+draft = false
 
 +++
 
-Midnight discussions with Arjun P.
+Midnight discussions with my room-mate
+[Arjun P](https://researchweb.iiit.ac.in/~arjun.p/).
 
-Algorithm vs data structure
-A proof technique is like an algorith, while an algebraic object is like
-a data structure. The existence of an algebraic object allows us to
-"meditate" on the proof technique as a separate object that does not
-move through time. Meditating on a proof technique is much harder, as is
-seeing if a proof techique can be applied in different places. 
-"Music is art in time. Art is music in space".
+This tries to explore what it is about algebra that I find appealing.
 
-On the other hand, this is probably pointless in combinatorics, because
-each proof is a technique unto itself. Or, perhaps instantiating the
-technique for each proof is difficult enough that abstracting it out
-is not useful enough in the first place. A good example of a proof
-technique that got studied on its own right is the probabilistic method. A
-more reasonable example is that of the Pigeonhole principle, which still
-requires insight to instantiate in practise.
+I think the fundamental difference to me comes down to flavour ---
+analysis and combinatorial objects feel very "algorithm", while Algebra feels
+"data structure".
+
+To expand on the analogy, a proof technique is like an algorithm, while an
+algebraic object is like a data structure. The existence of an algebraic object
+allows us to "meditate" on the proof technique as a separate object that does
+not move through time. This allows us to "get to know" the algebraic object,
+independent of how it's used. So, at least for me, I have a richness of 
+feeling when it comes to algebra that just doesn't shine through with analysis.
+The one exception maybe reading something like "by compactness", which has
+been hammered into me by exercises from Munkres :)
+
+Meditating on a proof technique is much harder, since the proof technique
+is necessarily intertwined with the problem, unlike a data structure which
+to some degree has an independent existence. 
+
+
+This reminds me of the quote: "“Art is how we decorate space;
+Music is how we decorate time.”. I'm not sure how to draw out the
+tenuous connection I feel, but it's there.
+
+Arjun comes from a background of combinatorics, and my understanding of his
+perspective is that each proof is a technique unto itself. Or, perhaps
+instantiating the technique for each proof is difficult enough that abstracting
+it out is not useful enough in the first place. 
+
+A good example of a proof technique that got studied on its own right in
+combinatorics is the probabilistic method. A more reasonable example is that of
+the Pigeonhole principle, which still requires insight to instantiate in
+practise.
 
 Not that this does not occur in algebra either, but there is something in
 algebra about how just meditating on the definitions. For example,
 Whitney trick that got pulled out of the proof of the Whitney embedding
 theorem.
 
-It's the same joy of being able to write down the type of a haskell function
-and know exactly what it does, enough that a program can automatically
-derive the function (djinn). The fact that we know the object well enough
-that just writing the type down allows us to infer the _program_!.
+To draw an analogy for the haskellers, it's the same joy of being able to write
+down the type of a haskell function and know exactly what it does, enough that
+a program can automatically derive the function (djinn). The fact that we know
+the object well enough that just writing the type down allows us to infer the
+_program_, makes it beautiful. There's something very elegant about the
+_minimality_ that algebra demands. Indeed, this calls back to another quote:
+"perfection is achieved not when there is nothing more to add, but when there
+is nothing left to take away".
+
+I'm really glad that this 2 AM discussion allowed me to finally pin down
+why I like algebra.