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## Summary:

- Simulate 1d percolation. I have to show that the probability of any site belonging to the largest cluster vanishes as N -> infinity

Hello

I am struggeling with a problem, or perhaps more with understanding the problem.

I have to simulate a one dimensional percolation in Python and that part I can do. The issue is understanding the next line of the problem, which I will post here:

"For the largest cluster size S, use finite size scaling, i.e., allow N to increase and plot s ≡ S/N vs. 1/N, to show that the probability of any site to belong to the largest cluster vanishes in the thermodynamic limit. Hint: Use N raised to some power between 2 and 5".

So, the way I understand this is to, let N increase some amount each iteration and find the largest cluster. I save these values and plot S/N vs. 1/N ending up with the attached plot.

I'm just unsure wheter or not this is correctly interpreted and would love to hear others input

Thanks!

I am struggeling with a problem, or perhaps more with understanding the problem.

I have to simulate a one dimensional percolation in Python and that part I can do. The issue is understanding the next line of the problem, which I will post here:

"For the largest cluster size S, use finite size scaling, i.e., allow N to increase and plot s ≡ S/N vs. 1/N, to show that the probability of any site to belong to the largest cluster vanishes in the thermodynamic limit. Hint: Use N raised to some power between 2 and 5".

So, the way I understand this is to, let N increase some amount each iteration and find the largest cluster. I save these values and plot S/N vs. 1/N ending up with the attached plot.

I'm just unsure wheter or not this is correctly interpreted and would love to hear others input

Thanks!