Deriving the Lattice Growth Formula

In summary, the conversation discusses the lattice growth formula and how it can be derived. The formula is represented as L(n) = n^2 (n+1)^2 / 4 and it counts the number of squares and rectangles in a 2x2 or 3x3 matrix. The formula is derived by systematically searching for rectangles, with the first person to derive it using a cartesian coordinate system and a function that counts the number of rectangles. The conversation also includes a detailed explanation of the mathematics behind the formula.
  • #1
musicgold
304
19
Hi,

I am trying to understand how one can derive the lattice growth formula of

L (n) = n^2 ( n + 1)^2 / 4

I looked at 2x2 and 3x3 matrices and could count the squares and rectangles in the figure.
L (2) = 9, L (3) =36 and so on.

However, I am more interested in finding out how the first person who derived this formula would have gone about doing it. Any ideas or pointers are much appreciated.

Thanks,

MG.
 
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  • #2
What exactly is that supposed to be counting? I tried googling lattice growth formula and your post is the only place it's mentioned on the internet
 
  • #3
Office_Shredder said:
What exactly is that supposed to be counting?

Sorry about the confusion, maybe I should have been more clear. All the possible squares and rectangles in a 2x2 matrix are represented as L(2) and there are 9 such squares / rectangles. Please see the attached doc. Similarly L(3) represents all possible squares and rectangles in a 3x3 matrix.
 

Attachments

  • 2x2 matrix - Copy.doc
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  • #4
- Take for example the 2x2 square (case n=2). Mark the nodes in the grid such that you
have a total of 9 nodes. We also introduce a cartesian coordinate system such that
we can identify each node via its coordinates (see attachment).



- The question is how do you systematically search for rectangles?
We first notice that a rectangle is completely determined by its bottom-left corner and top-right corner.



- Let's leave the bottom-left corner fixed. How many rectangles are there with
the bottom-left corner fixed at (0,0)?

To answer this question we let the top-right corner move to all allowed positions:

bottom-left corner: (0,0)
=> top-right corner: (1,1), (2,1), (1,2), (2,2)
=> 4 rectangles



- To get all rectangles we also allow the bottom-left corner to move:

bottom-left corner: (1,0)
=> top-right corner: (1,2), (2,2)
=> 2 rectangles

bottom-left corner: (0,1)
=> top-right corner: (1,2), (2,2)
=> 2 rectangles

bottom-left corner: (1,1)
=> top-right corner: (2,2)
=> 1 rectangles

Total number of rectangles: 4+2+2+1 = 9

----

We now have to find a formula for the general case.
Our tactic is to move the bottom-left corner and count the number
of possible positions for the right-top corner.

A pseudo-code for a function that calculates the number
of rectangles is given below:

Code:
numberOfRectangles(n):
   counter = 0
   for(j=0...n-1):
      for(i=0...n-1):
         for(y=j+1...n):
	    for(x=i+1...n):
	       counter = counter + 1
   return counter

The first two loops describe the movement of the left-bottom corner
with (i,j) being the position of the left-bottom corner.

The next two loops describe the movment of the right-top corner
with (x,y) being the position of the right-top corner.

You can translate the pseudo-code into mathematics by using the summation symbol:
The inner loop
Code:
	    for(x=i+1...n):
	       counter = counter + 1

corresponds to:
[tex]\sum_{x=i+1}^n 1 = n-(i+1)+1 = n-1[/tex]

The next loop
Code:
         for(y=j+1...n):
	    for(x=i+1...n):
	       counter = counter + 1

corresponds to:
[tex]\sum_{y=j+1}^n \sum_{x=i+1}^n 1 = \sum_{y=j+1}^n (n-i) = (n-i) \sum_{y=j+1}^n 1 = (n-i)(n-j)[/tex]


The next loop
Code:
      for(i=0...n-1):
         for(y=j+1...n):
	    for(x=i+1...n):
	       counter = counter + 1

corresponds to:
[tex]\sum_{i=0}^{n-1} \sum_{y=j+1}^n \sum_{x=i+1}^n 1 = \sum_{i=0}^{n-1} (n-i)(n-j)
= ... = (n-j) \cdot \left( n\cdot \frac{(n+1)}{2} \right)[/tex]


The last loop
Code:
   for(j=0...n-1):
      for(i=0...n-1):
         for(y=j+1...n):
	    for(x=i+1...n):
	       counter = counter + 1


corresponds to:
[tex]\sum_{j=0}^{n-1} \sum_{i=0}^{n-1} \sum_{y=j+1}^n \sum_{x=i+1}^n 1 = \sum_{j=0}^{n-1} (n-j) \cdot \left( n\cdot \frac{(n+1)}{2} \right)
= ... = \left( n\cdot \frac{(n+1)}{2} \right)^2[/tex]

I remember having encountered this problem in the excellent book "Thinking mathematically" by John Mason.
 

Attachments

  • lattice.png
    lattice.png
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  • #5
Edgardo,

First of all, thanks from the bottom of my heart. That is really helpful.
I understood the most of your solution except two points.

[tex]\sum_{x=i+1}^n 1 = n-(i+1)+1 = n-1[/tex]

I feel that this should be [tex] n-i [/tex]

Also in the following equation,

[tex] \sum_{i=0}^{n-1} (n-i)(n-j)= ... = (n-j) \cdot \left( n\cdot \frac{(n+1)}{2} \right)[/tex]
I am not sure how you got the second part of the answer. I think

[tex] \sum_{i=0}^{n-1} 1= (n-i) [/tex]
 
  • #6
musicgold said:
Edgardo,

First of all, thanks from the bottom of my heart. That is really helpful.
I understood the most of your solution except two points.

[tex]\sum_{x=i+1}^n 1 = n-(i+1)+1 = n-1[/tex]

I feel that this should be [tex] n-i [/tex]

Oops, you are right, that's a typo. It should indeed be [tex]n-i [/tex] .


musicgold said:
Also in the following equation,

[tex] \sum_{i=0}^{n-1} (n-i)(n-j)= ... = (n-j) \cdot \left( n\cdot \frac{(n+1)}{2} \right)[/tex]
I am not sure how you got the second part of the answer. I think

[tex] \sum_{i=0}^{n-1} 1= (n-i) [/tex]

Let's examine the expression
[tex] \sum_{i=0}^{n-1} (n-i)(n-j)[/tex]

Since we sum over the index i we can pull things that are independent of i
in front of the summation symbol. We see that (n-j) is independent of i:
[tex] \sum_{i=0}^{n-1} (n-i)(n-j) = (n-j) \sum_{i=0}^{n-1} (n-i) [/tex]

Let's concentrate on the sub-expression
[tex] \sum_{i=0}^{n-1} (n-i) [/tex]

The sum is applied to n and to (-i) and we get:
[tex] \sum_{i=0}^{n-1} (n-i) = \sum_{i=0}^{n-1} n - \sum_{i=0}^{n-1} i[/tex]

These sums are evaluated:
[tex]\sum_{i=0}^{n-1} n = n \sum_{i=0}^{n-1} 1 = n \cdot n = n^2 [/tex]

[tex]\sum_{i=0}^{n-1} i = \frac{(n-1)n}{2}[/tex]

For the last evaluation I've used http://www.ugrad.math.ubc.ca/coursedoc/math101/notes/integration/sums.html".
We get for the sub-expression:
[tex] \sum_{i=0}^{n-1} (n-i) = \sum_{i=0}^{n-1} n - \sum_{i=0}^{n-1} i = n^2 - \frac{(n-1)n}{2} = n^2 - \frac{n^2-n}{2} = \frac{n^2+n}{2}= \left( n\cdot \frac{(n+1)}{2} \right)[/tex]

Plugging this sub-expression into the expression yields:
[tex] \sum_{i=0}^{n-1} (n-i)(n-j) = (n-j) \sum_{i=0}^{n-1} (n-i) = (n-j) \left( n\cdot \frac{(n+1)}{2} \right)[/tex]
 
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  • #7
Edgardo,

Now it is clear to me. Thank you very much. Appreciate your efforts.
 

FAQ: Deriving the Lattice Growth Formula

What is the lattice growth formula?

The lattice growth formula is a mathematical equation used to model the growth of crystals in a lattice structure. It takes into account factors such as temperature, pressure, and concentration of the crystal's components to predict the rate and direction of crystal growth.

How is the lattice growth formula used in science?

The lattice growth formula is used in various fields of science, including materials science, geology, chemistry, and physics. It helps researchers understand and predict the growth patterns of crystals, which is crucial for developing new materials and studying natural processes.

What variables are included in the lattice growth formula?

The lattice growth formula includes variables such as temperature, pressure, concentration of components, and the lattice structure of the crystal. These variables can be changed to simulate different growth conditions and predict the resulting crystal formation.

What are the limitations of the lattice growth formula?

While the lattice growth formula is a useful tool, it has some limitations. It assumes that the crystal growth occurs in a perfect lattice structure with no defects, which may not always be the case in real-life scenarios. Additionally, it does not take into account other factors such as impurities or external forces that may affect crystal growth.

Can the lattice growth formula be applied to all types of crystals?

The lattice growth formula is best suited for crystals with a regular and well-defined lattice structure, such as metals, semiconductors, and ionic solids. It may not accurately predict the growth of complex or amorphous crystals, which do not have a distinct lattice pattern.

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