How Many Squares Fit in 1000.25mm Square? Ask Aaardvark!

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Discussion Overview

The discussion revolves around the problem of determining how many 1mm squares can fit within a larger square measuring 1000.25mm on each side. Participants explore mathematical reasoning, potential complexities, and references to relevant literature.

Discussion Character

  • Exploratory
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Aaardvark initially asks if the answer is simply 1000^2, suggesting a straightforward calculation.
  • Some participants indicate that the presence of the additional 0.25mm complicates the calculation, implying that the answer may not be as simple as squaring the integer value.
  • A participant describes a method to visualize the problem by drawing lines within the square, concluding that only 1,000,000 small squares can fit, leaving a 0.25mm margin where no squares can fit.
  • Aaardvark shares links to papers discussing packing squares, indicating a search for deeper understanding and potential complexities in the problem.
  • Another participant explains a theorem related to maximizing the area of packed unit squares and introduces a function W(α) that represents the "waste" in packing, suggesting that the problem is more complex than it appears.
  • Some participants express uncertainty about the mathematical details and seek clarification on the theorem's proof and its implications.
  • A later reply mentions the Erdos-Graham method as potentially applicable but admits difficulty in understanding the geometric aspects involved.

Areas of Agreement / Disagreement

Participants express differing views on the complexity of the problem, with some suggesting a straightforward approach while others highlight the nuances introduced by the additional 0.25mm. The discussion remains unresolved, with multiple competing perspectives on how to approach the problem.

Contextual Notes

The discussion includes references to mathematical literature and theorems that may not be fully understood by all participants, indicating potential gaps in knowledge or assumptions about the problem's complexity.

aaardvark
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Hi,

does anyone know how many squares of side 1 millimeter can fit in a big square of side 1000.25 millimeters ?

Cheers,

Aaardvark.
 
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aaardvark - I don't know your background, so I'm not sure if the answer is more complicated than [tex]1000^2[/tex]?
 
Apparently when the the big square is a large number of times plus a quarter bigger than the small square then the answer is not just that large numer squared. But I can't find out much more than this, ie how big does the large numer have to be etc.

Aaardvark.
 
Draw a line, perpendicular to a side, exactly 1000mm from one end a side, leaving 0.25 mm. Draw a second line, perpendicular to that line, exactly 1000 mm from one end of a side, leaving 0.25 mm. Those two lines, together with the opposite sides of the square form a square exactly 1000 mm on a side and so will fit exactly 10002= 1000000 small squares. The two portions outside the new drawn lines have width only .25 mm and so NO such squares will fit with them.
 
Page 8 touches on the subject but I can't find much else :frown:

http://www.math.ucsd.edu/~sbutler/ron/78_07_scheduling.pdf

Aaardvark.
 
Last edited by a moderator:
Here's a link to a paper by Erdos and Graham (On Packing Squares with Equal Squares):

www.math.ucsd.edu/~sbutler/ron/75_06_squares.pdf[/URL]

(At second glance, it comes from the same source as the pdf file in your last post, so perhaps you already know of it.)
 
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No, I hadn't found that one. Looks useful :smile:

But in case my little brain isn't up to the job maybe some of you geniuses (genii ?)
could have a go and give me an executive summary :-p

Aaardvark.
 
I think I can explain the statement of the theorem, but not the proof.

The problem is to maximize the sum of the areas of unit squares when packed into a square of side [tex]\alpha[/tex]. If [tex]\alpha[/tex] is an integer, then the maximum area of the packed unit squares is obviously [tex]\alpha^2[/tex].

For each positive real number [tex]\alpha[/tex], the author defines a function W([tex]\alpha[/tex]). W represents the difference between the optimal packed area [tex]\alpha^2[/tex] and the supremum (least upper bound) of the areas of all possible packings. (I think of W as representing the "waste".) The theorem states

W([tex]\alpha[/tex]) = O([tex]\alpha^\frac{7}{11}[/tex])

The so-called "big Oh" notation means that there exists a constant c such that

W([tex]\alpha[/tex]) [tex]\leq[/tex] c[tex]\alpha^\frac{7}{11}[/tex]

Intuitively, that means that W([tex]\alpha[/tex]) has the same "order" as [tex]\alpha^\frac{7}{11}[/tex]. As the author points out, for large [tex]\alpha[/tex], [tex]\alpha^\frac{7}{11}[/tex] is much smaller than the area of the packing obtained by placing the unit squares in rows and columns that are parallel to the sides of the big square.

The proof doesn't seem to use any advanced math, but I haven't tried to read it.

HTH

EDIT: Can anyone explain why my alphas aren't lining up correctly? I'm just learning Tex, so I assume I'm doing something wrong, but can't figure out what.
 
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Here's a much more up-to-date survey:
http://www.combinatorics.org/Surveys/ds7.html

The problem, in general, is quite hard.
 
Last edited by a moderator:
  • #10
CRGreathouse said:
Here's a much more up-to-date survey:
http://www.combinatorics.org/Surveys/ds7.html

The problem, in general, is quite hard.

Nice link. What a fascinating problem!
 
Last edited by a moderator:
  • #11
Petek said:
I think I can explain the statement of the theorem, but not the proof.

The problem is to maximize the sum of the areas of unit squares when packed into a square of side [tex]\alpha[/tex]. If [tex]\alpha[/tex] is an integer, then the maximum area of the packed unit squares is obviously [tex]\alpha^2[/tex].

For each positive real number [tex]\alpha[/tex], the author defines a function W([tex]\alpha[/tex]). W represents the difference between the optimal packed area [tex]\alpha^2[/tex] and the supremum (least upper bound) of the areas of all possible packings. (I think of W as representing the "waste".) The theorem states

W([tex]\alpha[/tex]) = O([tex]\alpha^\frac{7}{11}[/tex])

The so-called "big Oh" notation means that there exists a constant c such that

W([tex]\alpha[/tex]) [tex]\leq[/tex] c[tex]\alpha^\frac{7}{11}[/tex]

Intuitively, that means that W([tex]\alpha[/tex]) has the same "order" as [tex]\alpha^\frac{7}{11}[/tex]. As the author points out, for large [tex]\alpha[/tex], [tex]\alpha^\frac{7}{11}[/tex] is much smaller than the area of the packing obtained by placing the unit squares in rows and columns that are parallel to the sides of the big square.

The proof doesn't seem to use any advanced math, but I haven't tried to read it.

HTH

EDIT: Can anyone explain why my alphas aren't lining up correctly? I'm just learning Tex, so I assume I'm doing something wrong, but can't figure out what.

Thanks Petek.
 
  • #12
It looks like the Erdos-Graham method or a simpler variant would apply here, but I can't quite get through the details beyond the first trapezoids -- geometry's not my thing. Anyone want to take a stab at it?
 

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