Why do RDF plots have the probability at a particular distance >1. How can probability be more than one?
I am asking this because I want to understand what do the peaks of different length but at the same position on the x axis mean
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Sign up to join this communityWhy do RDF plots have the probability at a particular distance >1. How can probability be more than one?
I am asking this because I want to understand what do the peaks of different length but at the same position on the x axis mean
The radial distribution function isn't a probability or a probability density. The usual definition is $$g(r)=\frac{\rho(r)}{\rho_0}$$ where $\rho(r)$ is the number density at a particular distance $r$ away from some specified atom and $\rho_0$ is the bulk density of the material.
It can be larger than one if the local density is greater than the bulk (which you see in the first peak of your graph), so it can't be a probability. It also can't be a probability density, as integrating the RDF from $0$ to $r$ should give you the number of particles (divided by the bulk density) in that spherical volume, which should continue to increase even up to macroscopic distances (in contrast to a probability density which should integrate to $1$).
So what does the RDF tell you? Well if you integrate it over a spherical shell and multiply by the bulk density, you obtain the number of atoms in that shell. One particular shell we are often interested in is the first coordination sphere. Using the RDF, we can define the number of particles in the first coordination sphere as $$n(r')=4\pi\rho_0\int_0^{r'}g(r)r^2dr$$ where $r'$ is the location of the first minimum of the RDF. We can similarly determine the number of atoms in the $n^{\text{th}}$ coordination sphere by integrating from the$(n-1)^{\text{th}}$ minimum to the $n^{\text{th}}$ minimum.