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Introduction

There is a structure called sandpile. Let us introduce it in the following way. Suppose we have a set of whole points $\mathbb{Z}^2$. Next, we have a function $g:\mathbb{Z}^2 \rightarrow\mathbb{N}$, which shows how many grains are in the point $(x,y).$ Also, there is a number of a maximum possible grains in a point which leaves point stable. We will denote this number through $T$ (threshold). Now execute the following algorithm:

  1. if $g(x,y) > T$ then subtract 4 grains from $(x,y)$ and add one grain to each neighbor of $(x,y)$ i.e. $(x\pm 1, y)$ and $(x, y\pm 1)$.
  2. if there is no points with $g(x,y) > T$ then terminate. Else, start with step 1.

Simple example with $T=4$ and starting amount of grains $S$ (seed) at $(2,2)$ equals to 11 showed below. $$\begin{pmatrix} 0 & 0 & 0\\ 0 & 11 & 0\\ 0 & 0 & 0 \end{pmatrix} \rightarrow \begin{pmatrix} 0 & 2 & 0\\ 2 & 3 & 2\\ 0 & 2 & 0 \end{pmatrix}$$ More information about this here

Question

Suppose we have sandpile with $T=t$ and $S=n_0$ at (0,0). Let us denote such sandpiles through $\Delta(n_0;t)$. My question is

Given a sandpile $\Delta(n_0;t)$ find the size of this sandpile, where $$\text{size} := |\Delta(n_0;t)| =\max_{g(x,y)>0}|x|=\max_{g(x,y)>0}|y|$$

Tries

Some reasons lead me to the answer $$|\Delta(n_0;t)| \leq 3\log_{4}\frac{n_0}{t} + 1,$$ but empirical results say that for sufficiently large $n_0$ it is not true.

Pictures

Here are some pictures I made with Sage. The darker color the more grains in pixel. The first three pictures with threshold equals to 4, two last - 3. 10^3 10^4 10^5 10^3i3 10^4i3

EDIT: 1D sandpiles

Starting from the suggestion to look at 1-dim sandpile it is possible to say that there is nothing special (i.e. interesting) about that. It is almost obvious how they (1-dim SP's) look like (take a guess). More over, one can calculate the size of 1-dim SP: $$\Delta_{1}(n_0; t) \sim \frac{n_0}{2t}$$

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    You probably want the algorithm for the sandpile to also decrease the amount of grains at $(x,y)$ I'm assuming by $4$? Also $T>=4$ I take it? Furthermore the step 1 is done in some order, or all at once (i.e. evaluating $g(x,y)>T$ for all (x,y) at the beginning of the step performing the moves regardless of the changes then iterating?)2017-02-14
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    One other comment is this has some strange properties (it doesn't preserve monotonicity for one. I.e. a result of $\begin{pmatrix}0&2&0\\2&1&2\\0&2&0\end{pmatrix}$ is possible starting with a $9$ in the middle and it can get wierder if I'm looking at it correctly.) Have you tried seeing what happens if you do this in one dimension? It might be easier to model and still give some insight (though the two dimensional version will most likely be much more complex).2017-02-14
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    @DRF. Firstly, you are right about decreasing by 4. I added this condition to the description. Secondly, about order, it does not matter in what order you check points, the same result always. Thirdly, Yes, I want to have an upper bound for $|\Delta(n_0;t)|$. But, at the same time, not very large. E.g. obvious $n_0$ is very rough estimation.2017-02-14
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    I would guess the order doesn't matter, but it's not completely obvious. I will pos a quickish answer that doesn't answer the question fully.2017-02-14
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    The inequality with $\log_4(n_0/t)$ cannot hold for large $n_0$, since one must have $(2|\Delta(n_0,t)|+1)^2\ge n_0/t$. That is, $\Delta$ determines a square within which all the sand must fit.2017-06-23

2 Answers 2

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This estimate for $T = 3$ works pretty good.

I asssumed the shape is a circle. Its area is $A = \pi r^2$.

Now, the number of grains in the entire pile doesn't change, so I assumed the average number of grains per cell is $\left \lceil T / 2 \right \rceil = 2$.

Solving for $r$ gives

$$r = \sqrt{ \frac{n_0}{2 \pi} }$$

This is just a rough estimate, but it seems to work quite well.

Here is a table of values I calculated with my formula and the exact values (for $T = 3$).

i was to stupid for latex

This seems to indicate that the average number of grains isn't quite two, but it is still quite good. This may be improved by multiplying with $0.9341$.

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    +1 for your work. But it is far from obvious that *average* grains would be $\lceil T/2 \rceil$. See the pictures:)2017-06-23
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    I know, it was just a guess. I don't have tried with different values for $T$, maybe it is possible to estimate the average number of grains for an arbitrary $T$.2017-06-23
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So this doesn't answer the question fully but gives some ideas that are too long for comments.

Note that it seems (and I haven't proved this) that the area covered will always be pretty much a diamond centered at the origin i.e. $$\begin{pmatrix}0&0&x&0&0\\0&x&x&x&0\\x&x&x&x&x\\0&x&x&x&0\\0&0&x&0&0\end{pmatrix}$$ This covers $2n^2+2n+1$ places where $n=|\Delta(n_0;t)|$. A very rough upper bound then would come from assuming all the places contain 1 grain. This gives $(2n^2+2n+1)=n_0$ and solving for $n$ you would get very very roughly $O(\sqrt{n_0})$ asymptotically. Now a much more reasonable estimate though not a bound would be guessing pretty much all of them are full i.e. you solve $t(2n^2+2n+1)=n_0$ which gets you something on the order of $O(\sqrt{n_0/t})$ While this doesn't seem like it will be a perfect bound it seems more reasonable then a $\log$.

I will try to explain. Assuming the process behaves fairly reasonably, and I don't see why it shouldn't, assuming $n_0$ is much bigger then $t$ it seems the middle of the diamond should be mostly $t$'s. There might be dips though and that seems tricky to quantify, since the behavior doesn't seem to be very smooth. Looking at your original $t=4$ you can get the middle to be anything from $1-4$ depending on the remainder.

Thinking about this further though the choice of $4$ for $t$ might also be special given that $4$ is the number of neighbors.

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    I will put some pictures in a few minutes in the description, it might be useful, though probably might not.2017-02-14
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    BTW. $\Delta(n_0; t)$ is a notation for sandpile with one central point full of $n_0$ grains and threshold $t$, so it cannot be a number.2017-02-14
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    @Wolfgang Sorry meant that to have bars around it to denote the size as you defined it.2017-02-14
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    @wolfgang btw what leads you to think the answer should be roughly logarithmic. That seems impossible. Let $n=|\Delta(n_0;t)|$ again as in my answer. Then the most possible places for the sand are $4(n+1)^2$ (i.e. all of the square given by the vertices $(-n,-n),(n,n)$) and the most possible sand on any of the squares is $t$ thus the highest possible $n_0$ is $t4(n+1)^2$. In other words your best possible bound will be square root of the fraction.2017-02-14