What is the Computational Complexity of Rearranging a Crossword Puzzle Grid?

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Discussion Overview

The discussion revolves around the computational complexity of rearranging a crossword puzzle grid to determine the size of the largest square of black boxes that can be formed. Participants explore the implications of this problem in relation to the P=NP question, particularly focusing on the runtime complexity of algorithms that could solve it.

Discussion Character

  • Debate/contested, Technical explanation

Main Points Raised

  • One participant presents a problem involving an n*n crossword puzzle grid and seeks to determine the lower bound on the runtime of any algorithm solving it, suggesting that the problem becomes more complex as the size of the grid increases.
  • Another participant questions whether the initial post is a challenge or a request for help, indicating a potential ambiguity in the thread's purpose.
  • A participant notes that the problem, when generalized, relates to the P=NP question, cautioning against attempting to solve it directly. They propose that demonstrating a sequence of m's with increasing k's could imply P!=NP, but also express skepticism about the conclusiveness of such a strategy.
  • A later reply expresses a lack of interest in engaging with NP problems, indicating a personal boundary regarding the complexity of the discussion.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are differing views on the nature of the problem and its implications for the P=NP question. Some express interest in the challenge, while others are hesitant to engage with NP-related complexities.

Contextual Notes

The discussion includes assumptions about the relationship between the problem and the P=NP question, as well as the implications of polynomial sequences in proving complexity classes, which remain unresolved.

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Given an n*n crossword puzzle grid composed of n^2 boxes (black and white), consider the problem of determining the size of the biggest square composed entirely of black boxes that can be created by first rearranging the rows and then the columns.
Determine the smallest k such that O(n^k) is the lower bound on the run time of any algorithm claimed to solve all instances of the above problem (with n<=m, where m is any positive integer).

This problem gets really hard as m gets bigger.
 
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Is this a challenge or do you need help with the problem?
 
It's a challenge, good luck. :)
You should note that the instance of the problem where n= [any integer] is the P=NP problem, so don't try to solve that one. If you can give a sequence of m's where the corresponding k's increase as points in an exponential function then that would imply, though not prove, that P!=NP.
I wonder suppose i have an enormous sequence of m's and corresponding k's and the k's exhibit exponential behavior. No matter how big my sequence is, because it is finite, i can always find a polynomial that can produce those points, so this strategy will never prove P!=NP, or otherwise.

[EDIT: i take that back, for a large enough sequence you can get yourself $1 Million]
 
Last edited:
Thanks, but I don't have time to be messing with NP problems.
 

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