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I have a Cantor Set where I begin with a unit interval $[0,1]$.

I will remove a middle piece, and the remaining pieces are scaled by $r_1 = \frac{1}{9}, r_2 = \frac{3}{9} $

I am trying to determine the dimension through the Box Dimension method.

What I do is to choose a cover size of $\epsilon_1 = \frac{1}{9}$ which gives the number of covers $N(\epsilon_1)= 4 $

If I iterate it further and further, I get a general formula

$\epsilon_n = \frac{1}{9^n}$ and $N(\epsilon_n)= 4^n $

This gives me

$D= \frac{lnN(\epsilon)}{ln(\frac{1}{\epsilon})} \approx 0.63$

This value is exactly the same as the triadic cantor set (i.e $r_1=r_2 = \frac{1}{3}$ ) So I must have done something wrong.

Additionally, further reading from http://www.uvm.edu/~pdodds/files/papers/others/1988/tel1988a.pdf , from Equation 12, I find $D=0.43$ for $r_1 = \frac{1}{9}, r_2 = \frac{3}{9} $

Can anyone direct me to where my error is?

Candy Man
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  • The right-side piece after the first iteration has length $1/3$, and the left piece has length $1/9$. After the second iteration, the right piece will be split into a piece of length $1/27$ and a piece of length $1/9$, and the left piece will be split into a piece of length $1/81$ and a piece of length $1/27$. If we use $\epsilon_2 = 1/81$ as you suggest, we get $$N(\epsilon_2) = 3 + 9 + 1 + 3 = 16 = 4^2$$

    Your calculation of the number of boxes is correct.

    – Zubin Mukerjee Apr 06 '15 at 17:23
  • @ZubinMukerjee That's correct, but extremely misleading. The fractal dimension is about the spacing of the elements of the iterates of the fractal as the number of iterates tends to infinity. This does not lead to the correct dimension if done in the current fashion. – Zach466920 Apr 06 '15 at 17:28
  • @Zach466920 I don't understand. I am finding this dimension, not the Hausdorff or whichever other ones ... and we can take the limit as $n$ goes to infinity to get the same answer that OP got:

    $$\lim_{n\to\infty} \frac{\ln N(\epsilon_n)}{\ln(1/\epsilon_n)} = \lim_{n\to\infty} \displaystyle\frac{\ln(4^n)}{\ln\left(\displaystyle\frac{1}{1/9}\right)^n} = \lim_{n\to\infty} \frac{4n}{9n} = \log_9 4 $$

    I think this is what OP did ... what exactly is wrong with it?

    – Zubin Mukerjee Apr 06 '15 at 17:35
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    $N(1/9)$ is not 4, it's 3. In general, $N(1/3^k)$ is the $k^{th}$ Fibonacci number and the dimension is $\log(\varphi)/\log(3)$, where $\varphi$ is the the golden ratio. – Mark McClure Apr 06 '15 at 19:10
  • @CandyMan improved my answer a lot – Zach466920 Apr 06 '15 at 19:29
  • I understand where the error was, and a whole lot more now :) – Zubin Mukerjee Apr 07 '15 at 11:50

2 Answers2

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As Zach points out in his answer, the dimension of this set is easily computed using Moran's formula. However, the dimension can also be computed via box counting, as the question specifies. The result, $\log(\varphi))/\log(3)$ is kinda of cool in its own right and there's a neat connection with Fibonacci numbers that arise when we compute the dimension this way.

Denote your set by $E$ and let $N_{\varepsilon}(E)$ denote the number of closed intervals of length not exceeding $\varepsilon$ required to cover $E$. Let's compute $N_{3^{-k}}(E)$ by inspection for several small values of $k$ and see if we can spot a pattern.

$E$ is a non-empty subset of the unit interval so, for $k=0$, we get $N_{1}(E)=1$. For $k=1$, we get $N_{1/3}(E)=2$; one of these sets must have length $1/3$ but the other need only have length $1/9$:

enter image description here

For $k=2$, we get $N_{1/9}(E)=3$; two of these sets must have length $1/9$ and one need only have length $1/27$:

enter image description here

It's a little harder to see but, for $k=3$, we get $N_{1/27}(E)=5$; three of these sets must have length $1/27$ and two need only have length $1/81$:

enter image description here

It appears that $N_{3^{-k}}(E)$ is always a Fibonacci number. In fact, if we index the Fibonacci numbers such that $F_0=F_1=1$ and $F_k=F_{k-1}+F_{k-2}$, then it looks like $N_{3^{-k}}(E)=F_k$. Let's call this a level $k$ cover. It looks like a level $k$ cover consists of two types of intervals depending on their length relative to $k$: $F_{k-1}$ type 1 intervals of length $3^{-k}$ and $F_{k-2}$ type 2 intervals of length $3^{-(k+1)}$. Suppose, for induction, that this supposition is true for a fixed $k$. Then, the $F_{k-1}$ type 1 intervals in the level $k$ cover decompose into $F_{k-1}$ type 1 intervals of length $3^{-(k+1)}$ and $F_{k-1}$ type 2 intervals of length $3^{-(k+2)}$ in the induced level $k+1$ cover. The $F_{k-2}$ type $2$ intervals in the level $k$ cover become $F_{k-2}$ type $1$ intervals in the level $k+1$ cover. Thus, the level $k+1$ cover has $F_{k-1}+F_{k-2}=F_k$ type 1 intervals and $F_{k-1}$ type 2 intervals for a total of $F_{k}+F_{k-1}=F_{k+1}$ intervals. We conclude that $$N_{3^{-k}}(E) = F_k$$ for all $k\in \mathbb N$.

Now, it's well known that $F_k \sim \varphi^k$, where $\varphi$ is the golden ratio. As a result, $$\dim(E) = \lim_{k\rightarrow\infty} \frac{\log(\varphi^k)}{\log(3^k)} = \lim_{k\rightarrow\infty} \frac{k\log(\varphi)}{k\log(3)} = \frac{\log(\varphi)}{\log(3)}.$$

Mark McClure
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    Wow. One of my favorite answers on this site. – Zubin Mukerjee Apr 07 '15 at 03:41
  • @MarkMcClure Thank you for the very interesting answer. However I have a question regarding how you split up the pieces. As we know, this particular problem (loosely speaking) splits up a continuous piece into two other pieces in the proportions given. So 1 line --leads to-- > 2 parts --leads to --> 4 parts. ...i.e k = 0, 1 part. k = 1, 2 parts, k = 2, 4 parts, k = 3, 8 parts. In your reply, you appear to split up the right side piece (from k = 1) to form 3 pieces (when k = 2). Why would it not be 4 pieces? – Candy Man Apr 08 '15 at 18:52
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    was thinking of something very much like Figure 2.2(b) given here https://books.google.com/books?id=l2E4ciBQ9qEC&pg=PA10&lpg=PA10&dq=two+scale+cantor+set&source=bl&ots=7HHtdJyL40&sig=TK_TaIB7OL1Ydjd2P8H4WdLh2dA&hl=en&sa=X&ei=nnElVYiSDITguQSX2YDgCA&redir_esc=y#v=onepage&q=two%20scale%20cantor%20set&f=false

    Edit: I think I see what you're doing. You're splitting the largest interval at each k!

    – Candy Man Apr 08 '15 at 19:00
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    @CandyMan You seem to be assuming that each interval in a level $k$ cover must be split into smaller pieces when we move to a level $k+1$ cover. In my setup, a level $k$ cover consists of some intervals of length $3^{-k}$ (type 1) and some of length $3^{-(k+1)}$ (type 2). To generate a level $k+1$ cover, I choose to decompose only the intervals of length $3^{-k}$ leaving the others alone because they are already small enough as far as $N_{3^{-(k+1)}}$ is concerned. As a result, all the intervals in the covers are of relatively similar sizes (within a constant multiple, in fact). – Mark McClure Apr 08 '15 at 19:14
  • @CandyMan I just noticed your edit - it looks like you've got it! – Mark McClure Apr 08 '15 at 19:19
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Exactly self similar fractals have a very easy formula to find their fractal dimension. This example fits the category, use the Moran equation. You're error was only in assuming that you're formula would hold for all iterations, but in reality, the $1 \over 9$ shrinks by a different amount than the $3 \over 9$ part. $$1=\left ({1 \over 9} \right)^D +\left({3 \over 9} \right)^D$$ This will solve for D, the fractal dimension. $$D=0.4380...$$

Derivation

The similarity dimension for a fractal with similitude $\epsilon={1 \over S}$ is given by $$D_s={{\ln(N)} \over {\ln(S)}}$$ If the fractal has more than one similitude, as in the case of the cantor set variant, this equation won't work. What we need to do, is transform this equation so that it incorporates each of the similitudes. Manipulate the equation... $$D_s \cdot \ln(S)=\ln(N)$$ $$\ln(S^{D_s})=\ln(N)$$ $$S^{D_s}={\epsilon}^{-D_s}=N$$ $$1=N \cdot {\epsilon}^{D_s}$$ Here's the step that is interesting. The above result says that there are $N$ copies of a similitude to the power of the fractal dimension that when added together equals one. The above derivation justifies that. However, if there is more than one similitude multiplying by $N$ doesn't make very much sense. Instead you'd just manually add each similitude. So write out the multiplication by $N$ $$1= {\epsilon_1}^{D_s}+ {\epsilon_2}^{D_s}...+ {\epsilon_N}^{D_s}$$ If ${\epsilon_k}={\epsilon_m}$ where $1 \le (k$ and $m) \le N $ then we just have the regular formula, and by extension it can be readily solved. Otherwise you have the above equation, which is called Moran's equation.

Solution Techniques This equation can be very hard or very easy to solve depending on the similitudes given. For instance, similitudes that are equal to each other or are multiples of each other are generally easier to solve than random similitudes. Using your question as an example... $$1=\left ({1 \over 9} \right)^D +\left({3 \over 9} \right)^D$$ $$1=\left ({3} \right)^{-2D} +\left({3} \right)^{-D}$$ Use the substitution, $u=3^{-D}$ $$1=u^2+u$$ $$u^2+u-1=0$$ which yields $u=\phi$, where $\phi$ is the golden ratio. $$\phi=3^{-D}$$ which finally solves to $${{\ln({\phi})} \over {\ln(3)}}=0.4380...$$

Bonus Information For harder to solve cases use this unorthodox method. Lets solve... $$1=\left ({1 \over a} \right)^D +\left({1 \over b} \right)^D$$ This will give the fractal dimension of every Cantor set that can be made. $$a^{-D}=1-b^{-D}$$ Take the log of both sides $$-D \cdot \ln(a)=\ln(1-b^{-D})$$ $$D= {{-\ln(1-b^{-D})} \over {\ln(a)}}$$ Now, solve a fractal equation with a fractal. Use the fact that we know $D$ in terms of $D$ to solve... $$D= {{-\ln \left(1-b^{{{\ln(1-b^{{{\ln(1-b^{.^{.^{.}}})} \over {\ln(a)}}})} \over {\ln(a)}}} \right)} \over {\ln(a)}}$$ Bet you've never seen that! (Had a great time writing this)

Zach466920
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  • How do you solve the Moran equation once you've written it down? – Zubin Mukerjee Apr 06 '15 at 17:40
  • @ZubinMukerjee Zach is correct that the value of $D$ such that $1/9^D+1/3^D=1$ will return the dimension (so you might consider giving him an upvote). Since $1/3$ and $1/9$ are exponentially commensurable, $D$ may be solved for in closed form, as in my answer here. On the other hand, you might also try to compute $N(3^{-k})$ in closed form. It's a Fibonacci number, as in my comment to the original question. – Mark McClure Apr 06 '15 at 19:18
  • @ZubinMukerjee look at my edits, it should answer all your questions. – Zach466920 Apr 06 '15 at 19:29
  • @Zach466920 Cute. I wonder if your iterative technique to find $D$ generally converges? – Mark McClure Apr 06 '15 at 19:42
  • @MarkMcClure I'm no expert at convergence, so I went and plotted graphs of this iterative approach for various iteration levels. I used D as a variable. For instance, using $D=ln(3)/ln(2)$ the method converges. Although I only went to the 4th iteration, All guesses for D seemed to get closer to the true value in a oscillatory and semi linear way. So this most likely provides bounds on the dimension. It might also be worth it to mention that the expansion can be written as a nested root inside of a logarithm. It almost goes without saying though that newton's method is superior. – Zach466920 Apr 06 '15 at 20:15
  • @Zach466920 I really like the iterative technique and I think it can genrally work but not automatically. Specifically, I think we need $b<a$ (which can be arranged, if $a\neq b$) to get it to work. It's worth thinking about more. – Mark McClure Apr 06 '15 at 20:26
  • @Zach466920 Thank you, great explanation (+1). – Zubin Mukerjee Apr 06 '15 at 20:29
  • @MarkMcClure Thanks. That definitely seems to be the case. If $a=b$ you just get D and the original equation as simplifications. So the method seems to work only if other techniques fail. I'll look deeper into the convergence properties. – Zach466920 Apr 06 '15 at 20:38
  • Thanks for the interesting explanation! – Candy Man Apr 08 '15 at 18:24