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Data structures as topological spaces (2002) [pdf]

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Re: Data structures as topological spaces (2002) [pdf]

#31
post #29
post #20

Earlier quoted context omitted.

Perhaps the confusion is that I should have said topological spaces can be continuous. There are discrete topological spaces. Topologies (which I believe is typically used to refer to the collection of open sets in a topological space) are not functions or relations themselves, so I'm not sure a useful notion of continuity applies there, but if I'm wrong, please inform.

There isn't really such a thing as a 'continuous topological space'. Technically speaking, continuity is a property of functions between topological spaces. I think you're being tempted to use the terms continuous and discrete in a more colloquial sense mapping more to uncountable vs countable/countable and finite perhaps. But yeah, you really wouldn't use the term continuous to describe a topological space or a topo…

The classic middle-thirds Cantor Set being a topologically set is one of the easiest counter examples to the above misconception that the sets need to be continuous themselves.

Being able to define a neighborhood or a concept of closeness is required, but the concept of distance is not required.

If you can define a distance a topological space is a metric space

If it is locally euclidean it may be a manifold.

Really the union and finite intersection of subsets is the formal way of showing something is a topological space. Too har do describe here but that is where the concept of continuity arises.

Re: Data structures as topological spaces (2002) [pdf]

#32
post #3

Earlier quoted context omitted.

Graphs are discrete, topologies are potentially continuous. Moreover, you can do different things with them such as create homeomorphisms to another topology much more easily than you can create bijections between graphs. In general, continuity lets you assume things that are impossible in discrete spaces. For example, many optimization problems are really easy in continuous spaces but really hard in discrete ones (l…

Topologies are necessarily continuous

You're going to tell me the discrete topology is continuous!?

Re: Data structures as topological spaces (2002) [pdf]

#33
post #29
post #20

Earlier quoted context omitted.

Perhaps the confusion is that I should have said topological spaces can be continuous. There are discrete topological spaces. Topologies (which I believe is typically used to refer to the collection of open sets in a topological space) are not functions or relations themselves, so I'm not sure a useful notion of continuity applies there, but if I'm wrong, please inform.

There isn't really such a thing as a 'continuous topological space'. Technically speaking, continuity is a property of functions between topological spaces. I think you're being tempted to use the terms continuous and discrete in a more colloquial sense mapping more to uncountable vs countable/countable and finite perhaps. But yeah, you really wouldn't use the term continuous to describe a topological space or a topo…

Connected or complete then.

Re: Data structures as topological spaces (2002) [pdf]

#34
post #27

Stephen Wolfram's ruliad seems to be some sort of concurrent topological computations. There are some beautiful pictures. https://content.wolfram.com/sites/43/2021/11/1110swimg46.png https://writings.stephenwolfram.com/2021/11/the-concept-of-t...

Fascinating, so would this mean an LLM is an approximator of a certain proportion of a 'ruliad'? Apologies for using GPT here, but it's a bit beyond my math to make a statement like that without reaching for my sidekick..."in a broad sense, one could conceptualize a Large Language Model (LLM) as an approximator of a specific, limited subsection of the ruliad" so I guess so, ish?

Considering the ruliad consists of all possible rules and their applications, you could say that. But it's oh so much more!

Re: Data structures as topological spaces (2002) [pdf]

#35

> 1. selects a sub-collection B of A whose elements match the path pattern β, > 2. computes a new collection C as a function f of B and its neighbors, > 3. and specifies the insertion of C in place of B into A. This sounds a lot like the presentation of comonads as directed containers (e.g. https://arxiv.org/abs/1408.5809 ).

I wish I understood what this paper was saying.

Re: Data structures as topological spaces (2002) [pdf]

#36
post #15

It feels like the following PDF better expresses what they're trying to accomplish. http://mgs.spatial-computing.org/PUBLICATIONS/lami-RR72--com... As far as I can tell, they're trying to model things like chemical reactions (and other stuff) where given a bunch of "stuff" in some solution it will combine with other "stuff" if it's in the same topological neighborhood (which I think is basically the idea that ALL of…

Is this for modeling a single reaction or chain of reactions? ie you don’t need neighborhoods if you are modeling 7 trillion of one thing combined with 14 trillion of another?

Re: Data structures as topological spaces (2002) [pdf]

#37
post #15

It feels like the following PDF better expresses what they're trying to accomplish. http://mgs.spatial-computing.org/PUBLICATIONS/lami-RR72--com... As far as I can tell, they're trying to model things like chemical reactions (and other stuff) where given a bunch of "stuff" in some solution it will combine with other "stuff" if it's in the same topological neighborhood (which I think is basically the idea that ALL of…

I'm puzzled by what's happening on page 9 of that PDF.

Ok, I quickly browsed through it, but a chemical reaction where two identical molecules react into those same molecules plus another molecule? How can this be possible?

Re: Data structures as topological spaces (2002) [pdf]

#38
post #3
post #2

How is this fundamentally different than considering data structures as graphs?

Graphs are discrete, topologies are potentially continuous. Moreover, you can do different things with them such as create homeomorphisms to another topology much more easily than you can create bijections between graphs. In general, continuity lets you assume things that are impossible in discrete spaces. For example, many optimization problems are really easy in continuous spaces but really hard in discrete ones (l…

so topologies are grids (e.g. coordinates) in this case? it's not a great naming choice as "topology" is frequently used to describe network/graph

Re: Data structures as topological spaces (2002) [pdf]

#39
post #15

It feels like the following PDF better expresses what they're trying to accomplish. http://mgs.spatial-computing.org/PUBLICATIONS/lami-RR72--com... As far as I can tell, they're trying to model things like chemical reactions (and other stuff) where given a bunch of "stuff" in some solution it will combine with other "stuff" if it's in the same topological neighborhood (which I think is basically the idea that ALL of…

Figure 5 kinda reminds me of...Datalog? Where you have rules and a data set. Given the rules, you iteratively compute on the data set until there are no more rules that match the given data--the fixed point.

Is that right?

Re: Data structures as topological spaces (2002) [pdf]

#40
post #36
post #15

It feels like the following PDF better expresses what they're trying to accomplish. http://mgs.spatial-computing.org/PUBLICATIONS/lami-RR72--com... As far as I can tell, they're trying to model things like chemical reactions (and other stuff) where given a bunch of "stuff" in some solution it will combine with other "stuff" if it's in the same topological neighborhood (which I think is basically the idea that ALL of…

Is this for modeling a single reaction or chain of reactions? ie you don’t need neighborhoods if you are modeling 7 trillion of one thing combined with 14 trillion of another?

It looks like chains of reactions etc. As you say for something simple you don't need something complex.

It's a DSL for computational biology where very little documentation has apparently made it to a public forum. I can decode the programming language part of it but I'm not up to scratch on computational biology so I'm not sure exactly what they want it for.

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