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Think of a cryptic crossword puzzle.

It consists of a grid of overlapping slots and for each slot there is a clue.

The question that sheaf theory addresses is what constraints do you have to put on the clues to ensure that the overall puzzle has a single solution.



Is that related to #P complexity at all, the complexity class of counting the number of solutions to an NP-complete instance?


No


Why not, they sound like similar problems and the latter would motivate computer scientists to learn about sheafs as per the approach taken in OP's book which is applied/example driven.




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