It turns out, and this is kinda crazy, but when you delete a row and a column from a matrix, it stops having the same eigenvectors. So, like, if you're trying to build something using the eigenvectors of the adjacency matrix of a graph (don't think about it too hard, it's weird), and you want the end product to be robust to the loss of a vertex in
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the only words i understood in that whole thing were "all fucked up".
How can anyone help you when we can't even read what you wrote?
;-p
j/k of course. i also understood the words deleting, build, and robust. The last of which I know often has to do with coffee.
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You start with the ingredients, do something like what's said in the recipes, and end up with a pie. But now, what happens if you're missing an ingredient? Like flour for instance.
What I'd forgotten, more or less, was that if you leave out the flour, and you follow the recipes, and you make a pie... the end product is not just a pie with no flour. You can't just throw a cup of flour on top and get a pie. The recipes combine the ingredients, so losing one of them affects the whole damn thing.
Like that, but with graphs and matrices. Sorta.
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What's it mean to have eigenvectors of an adjacency matrix? Is that something that one can have an intuitive grasp on?
(of course, my intuition about eigenvectors in general is pretty much non-existent...)
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The guys are going for their checkup on Thursday. But they had their shots last spring; do you think they're vaccinated enough?
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So... mm... this is a bit problematic, logistically. We've still got the apartment through next friday, but it'll be empty... I wonder if you could get an appointment at college mall vets sooner?
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Good luck!
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