Random walk in spherical coordinates

In summary, the conversation discusses modeling receptors on a cell surface using spherical coordinates and how to incorporate a random walk in this modeling. It is suggested to use theta and phi instead of cartesian coordinates, and to choose points uniformly on the surface of a sphere.
  • #1
arandall
1
0
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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  • #2
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.
 
  • #3
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.
 

1. What is a random walk in spherical coordinates?

A random walk in spherical coordinates is a type of mathematical model used to describe the movement of a particle in three-dimensional space. It involves randomly choosing a direction and distance for the particle to move in each step, resulting in a series of movements that can be plotted as a path or trajectory.

2. How is a random walk in spherical coordinates different from a random walk in Cartesian coordinates?

The main difference between a random walk in spherical coordinates and a random walk in Cartesian coordinates is the coordinate system used. In spherical coordinates, the position of the particle is described using a radius, an angle from the origin, and an angle from a reference plane, while in Cartesian coordinates, the position is described using x, y, and z coordinates. Additionally, the distance traveled in each step is calculated differently in the two systems.

3. What applications does a random walk in spherical coordinates have?

A random walk in spherical coordinates has many applications in fields such as physics, chemistry, biology, and finance. It can be used to model the diffusion of particles, the movement of cells or microorganisms, the behavior of stock prices, and more.

4. What are the limitations of a random walk in spherical coordinates?

One limitation of a random walk in spherical coordinates is that it assumes the movement of the particle is completely random and does not take into account any external factors or forces that may influence its motion. Additionally, the accuracy of the model may decrease as the number of steps increases.

5. How is a random walk in spherical coordinates simulated?

A random walk in spherical coordinates can be simulated using computer programs or mathematical algorithms. The simulation involves generating a random direction and distance for each step and updating the position of the particle accordingly. This process is repeated multiple times to create a trajectory that represents the random walk in spherical coordinates.

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