Random walk in spherical coordinates

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SUMMARY

This discussion focuses on modeling a random walk of receptors on a cell surface using spherical coordinates. The user seeks to adapt a Cartesian model, defined by the equations for x, y, and z, to spherical coordinates by fixing the radius (r) and focusing on the angles theta (θ) and phi (φ). The proposed method for uniformly selecting points on the sphere involves setting θ uniformly between 0 and 2π, and φ using the sine function to ensure uniform distribution across the surface.

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arandall
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Hi,

I'm modeling receptors moving along a cell surface that interact with proteins inside of a cell. I figured it would be easier to model the receptors in spherical coordinates, however I'm unsure of how to model a random walk. In cartesian coordinates, I basically model a step as:

x = x + sqrt(6*D*timeStep)*randn
y = y + sqrt(6*D*timeStep)*randn
z = z + sqrt(6*D*timeStep)*randn

Where D is my diffusion constant. How can I do this just using theta and phi? Modeling random walk in spherical coordinates will be really nice, because I can fix r such that the receptors can't leave the membrane of the cell, and just focus on how it moves in 2D with respect to the membrane.
 
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Because the receptors are so much smaller than the size of the cell, it should be fine if you treat theta and phi just like x-y; i.e. pretend its a 2D random walk in Cartesian coordinates.
 
To choose points on the surface of a sphere uniformly, the two angles should be chosen as follows (I'll call them latitude and longitude):

Longitude (θ) - θ uniform between 0 and 2π.
Latitude (φ) - sinφ uniform between -1 and 1.
 

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