Square packing

Last updated

Square packing is a packing problem where the objective is to determine how many congruent squares can be packed into some larger shape, often a square or circle.

Contents

Square packing in a square

Square packing in a square is the problem of determining the maximum number of unit squares (squares of side length one) that can be packed inside a larger square of side length . If is an integer, the answer is but the precise – or even asymptotic – amount of unfilled space for an arbitrary non-integer is an open question. [1]

5 kvadratoj en kvadrato.svg
5 unit squares in a square of side length
10 kvadratoj en kvadrato.svg
10 unit squares in a square of side length
Packing 11 unit squares in a square with side length 3.87708359....svg
11 unit squares in a square of side length

The smallest value of that allows the packing of unit squares is known when is a perfect square (in which case it is ), as well as for 2, 3, 5, 6, 7, 8, 10, 13, 14, 15, 24, 34, 35, 46, 47, and 48. For most of these numbers (with the exceptions only of 5 and 10), the packing is the natural one with axis-aligned squares, and is , where is the ceiling (round up) function. [2] [3] The figure shows the optimal packings for 5 and 10 squares, the two smallest numbers of squares for which the optimal packing involves tilted squares. [4] [5]

The smallest unresolved case involves packing 11 unit squares into a larger square. 11 unit squares cannot be packed in a square of side length less than . By contrast, the tightest known packing of 11 squares is inside a square of side length approximately 3.877084 found by Walter Trump. [6] [4]

Asymptotic results

Unsolved problem in mathematics:

What is the asymptotic growth rate of wasted space for square packing in a half-integer square?

For larger values of the side length , the exact number of unit squares that can pack an square remains unknown. It is always possible to pack a grid of axis-aligned unit squares, but this may leave a large area, approximately , uncovered and wasted. [4] Instead, Paul Erdős and Ronald Graham showed that for a different packing by tilted unit squares, the wasted space could be significantly reduced to (here written in little o notation). [7] Later, Graham and Fan Chung further reduced the wasted space to . [8] However, as Klaus Roth and Bob Vaughan proved, all solutions must waste space at least . In particular, when is a half-integer, the wasted space is at least proportional to its square root. [9] The precise asymptotic growth rate of the wasted space, even for half-integer side lengths, remains an open problem. [1]

Some numbers of unit squares are never the optimal number in a packing. In particular, if a square of size allows the packing of unit squares, then it must be the case that and that a packing of unit squares is also possible. [2]

Square packing in a circle

Square packing in a circle is a related problem of packing n unit squares into a circle with radius as small as possible. For this problem, good solutions are known for n up to 35. Here are minimum solutions for n up to 12: [10]

Number of squaresCircle radius
10.707...
21.118...
31.288...
41.414...
51.581...
61.688...
71.802...
81.978...
92.077...
102.121...
112.214...
122.236...

See also

Related Research Articles

<span class="mw-page-title-main">Floor and ceiling functions</span> Nearest integers from a number

In mathematics and computer science, the floor function is the function that takes as input a real number x, and gives as output the greatest integer less than or equal to x, denoted x or floor(x). Similarly, the ceiling function maps x to the least integer greater than or equal to x, denoted x or ceil(x).

<span class="mw-page-title-main">Rounding</span> Replacing a number with a simpler value

Rounding means replacing a number with an approximate value that has a shorter, simpler, or more explicit representation. For example, replacing $23.4476 with $23.45, the fraction 312/937 with 1/3, or the expression 2 with 1.414.

<span class="mw-page-title-main">Packing problems</span> Problems which attempt to find the most efficient way to pack objects into containers

Packing problems are a class of optimization problems in mathematics that involve attempting to pack objects together into containers. The goal is to either pack a single container as densely as possible or pack all objects using as few containers as possible. Many of these problems can be related to real-life packaging, storage and transportation issues. Each packing problem has a dual covering problem, which asks how many of the same objects are required to completely cover every region of the container, where objects are allowed to overlap.

In computer science, the Akra–Bazzi method, or Akra–Bazzi theorem, is used to analyze the asymptotic behavior of the mathematical recurrences that appear in the analysis of divide and conquer algorithms where the sub-problems have substantially different sizes. It is a generalization of the master theorem for divide-and-conquer recurrences, which assumes that the sub-problems have equal size. It is named after mathematicians Mohamad Akra and Louay Bazzi.

The fractional part or decimal part of a non‐negative real number is the excess beyond that number's integer part. If the latter is defined as the largest integer not greater than x, called floor of x or , its fractional part can be written as:

Sperner's theorem, in discrete mathematics, describes the largest possible families of finite sets none of which contain any other sets in the family. It is one of the central results in extremal set theory. It is named after Emanuel Sperner, who published it in 1928.

In mathematics, the nth Motzkin number is the number of different ways of drawing non-intersecting chords between n points on a circle. The Motzkin numbers are named after Theodore Motzkin and have diverse applications in geometry, combinatorics and number theory.

<span class="mw-page-title-main">Heilbronn triangle problem</span> On point sets with no small-area triangles

In discrete geometry and discrepancy theory, the Heilbronn triangle problem is a problem of placing points in the plane, avoiding triangles of small area. It is named after Hans Heilbronn, who conjectured that, no matter how points are placed in a given area, the smallest triangle area will be at most inversely proportional to the square of the number of points. His conjecture was proven false, but the asymptotic growth rate of the minimum triangle area remains unknown.

<span class="mw-page-title-main">Sturmian word</span> Kind of infinitely long sequence of characters

In mathematics, a Sturmian word, named after Jacques Charles François Sturm, is a certain kind of infinitely long sequence of characters. Such a sequence can be generated by considering a game of English billiards on a square table. The struck ball will successively hit the vertical and horizontal edges labelled 0 and 1 generating a sequence of letters. This sequence is a Sturmian word.

The Engel expansion of a positive real number x is the unique non-decreasing sequence of positive integers such that

<span class="mw-page-title-main">Comparison sort</span> Type of sorting algorithm that works by comparing pairs of elements

A comparison sort is a type of sorting algorithm that only reads the list elements through a single abstract comparison operation that determines which of two elements should occur first in the final sorted list. The only requirement is that the operator forms a total preorder over the data, with:

  1. if ab and bc then ac (transitivity)
  2. for all a and b, ab or ba (connexity).

In mathematics, a Beatty sequence is the sequence of integers found by taking the floor of the positive multiples of a positive irrational number. Beatty sequences are named after Samuel Beatty, who wrote about them in 1926.

Discrepancy of hypergraphs is an area of discrepancy theory.

In the mathematical fields of graph theory and combinatorial optimization, the bipartite dimension or biclique cover number of a graph G = (VE) is the minimum number of bicliques (that is complete bipartite subgraphs), needed to cover all edges in E. A collection of bicliques covering all edges in G is called a biclique edge cover, or sometimes biclique cover. The bipartite dimension of G is often denoted by the symbol d(G).

<span class="mw-page-title-main">Van Houtum distribution</span>

In probability theory and statistics, the Van Houtum distribution is a discrete probability distribution named after prof. Geert-Jan van Houtum. It can be characterized by saying that all values of a finite set of possible values are equally probable, except for the smallest and largest element of this set. Since the Van Houtum distribution is a generalization of the discrete uniform distribution, i.e. it is uniform except possibly at its boundaries, it is sometimes also referred to as quasi-uniform.

In graph theory, the graph bandwidth problem is to label the n vertices vi of a graph G with distinct integers so that the quantity is minimized . The problem may be visualized as placing the vertices of a graph at distinct integer points along the x-axis so that the length of the longest edge is minimized. Such placement is called linear graph arrangement, linear graph layout or linear graph placement.

In mathematics and computer science, the sorting numbers are a sequence of numbers introduced in 1950 by Hugo Steinhaus for the analysis of comparison sort algorithms. These numbers give the worst-case number of comparisons used by both binary insertion sort and merge sort. However, there are other algorithms that use fewer comparisons.

In computer science, merge-insertion sort or the Ford–Johnson algorithm is a comparison sorting algorithm published in 1959 by L. R. Ford Jr. and Selmer M. Johnson. It uses fewer comparisons in the worst case than the best previously known algorithms, binary insertion sort and merge sort, and for 20 years it was the sorting algorithm with the fewest known comparisons. Although not of practical significance, it remains of theoretical interest in connection with the problem of sorting with a minimum number of comparisons. The same algorithm may have also been independently discovered by Stanisław Trybuła and Czen Ping.

<span class="mw-page-title-main">Tripod packing</span>

In combinatorics, tripod packing is a problem of finding many disjoint tripods in a three-dimensional grid, where a tripod is an infinite polycube, the union of the grid cubes along three positive axis-aligned rays with a shared apex.

<span class="mw-page-title-main">Blichfeldt's theorem</span> High-area shapes can shift to hold many grid points

Blichfeldt's theorem is a mathematical theorem in the geometry of numbers, stating that whenever a bounded set in the Euclidean plane has area , it can be translated so that it includes at least points of the integer lattice. Equivalently, every bounded set of area contains a set of points whose coordinates all differ by integers.

References

  1. 1 2 Brass, Peter; Moser, William; Pach, János (2005), Research Problems in Discrete Geometry, New York: Springer, p. 45, ISBN   978-0387-23815-9, LCCN   2005924022, MR   2163782
  2. 1 2 Kearney, Michael J.; Shiu, Peter (2002), "Efficient packing of unit squares in a square", Electronic Journal of Combinatorics , 9 (1), Research Paper 14, 14 pp., MR   1912796
  3. Bentz, Wolfram (2010), "Optimal packings of 13 and 46 unit squares in a square", The Electronic Journal of Combinatorics, 17 (R126), doi:10.37236/398, MR   2729375
  4. 1 2 3 Friedman, Erich (2009), "Packing unit squares in squares: a survey and new results", Electronic Journal of Combinatorics , Dynamic Survey 7, MR   1668055
  5. Stromquist, Walter (2003), "Packing 10 or 11 unit squares in a square", Electronic Journal of Combinatorics , 10, Research Paper 8, MR   2386538
  6. Gensane, Thierry; Ryckelynck, Philippe (2005), "Improved dense packings of congruent squares in a square", Discrete & Computational Geometry , 34 (1): 97–109, doi: 10.1007/s00454-004-1129-z , MR   2140885
  7. Erdős, P.; Graham, R. L. (1975), "On packing squares with equal squares" (PDF), Journal of Combinatorial Theory , Series A, 19: 119–123, doi: 10.1016/0097-3165(75)90099-0 , MR   0370368
  8. Chung, Fan; Graham, Ron (2020), "Efficient packings of unit squares in a large square" (PDF), Discrete & Computational Geometry, 64 (3): 690–699, doi:10.1007/s00454-019-00088-9
  9. Roth, K. F.; Vaughan, R. C. (1978), "Inefficiency in packing squares with unit squares", Journal of Combinatorial Theory , Series A, 24 (2): 170–186, doi: 10.1016/0097-3165(78)90005-5 , MR   0487806
  10. Friedman, Erich, Squares in Circles