Radial Distribution of Points over the Area of a Circle

In summary: Thanks again!In summary, the conversation discusses the distribution of points generated by choosing a random radius and choosing points along it with a uniform distribution. The question is how this can be extrapolated to the area of a circle. The solution given by ET Jaynes is f(r)=\frac{1}{2πRr}, which can be derived by considering the probability of picking a point in an area element on the circle. The conversation also includes a discussion on the formal proof for this equation and clarifies the role of the midpoints mentioned in the original construction.
  • #1
SaintsTheMeta
12
0
This is a tiny part of a presentation I am giving Friday, any and all help is appreciated.

Homework Statement


Suppose we have a circle centered on O. We are looking for the distribution of the points generated by the following method:

We choose a random radius of the circle, and then choose points along that radius with a uniform distribution. i.e. for any arbitrary radius of the circle, we will have a uniform distribution of points [itex]f(r)=\frac{1}{R}[/itex].

My question is how do we extrapolate this to the area of a circle, to account for all "random radiuses?"

ET Jaynes gives a solution: [itex]f(r)=\frac{1}{2πRr}[/itex]
here: http://www.google.com/url?sa=t&rct=...OQeRMbfgQ&sig2=goMBcl6Cr-jKjCMYz11G_g&cad=rja
page 5, last sentence before the section 4 header.

Homework Equations



[itex]f(r)=\frac{1}{2πRr}[/itex]

The Attempt at a Solution



This solution seems logical. But I need to be able to give a FORMAL proof of where this comes from. I just CAN'T seem to understand exactly where this equation comes from.

My thinking is it is a uniform distribution over circumference [itex]f(r)=\frac{1}{2\pi r}[/itex] multiplied with the uniform distribution of each radius [itex]\frac{1}{R}[/itex]

Or, we could integrate [itex]\frac{1}{R}[/itex] over angles 0 to 2pi which would give what we want, but Whyyyy

Can anyone help me PRECISELY understand this? This is the kind of thing that is almost always "hand waved" in physics, and while it seems logical, formalism is difficult for me after my studies focused on physics.

Thank you!

edit: My best explanation at this point would be a series of "rings" with circumference 2∏r, then multiplied with the uniform distribution 1/R. But still, this is not logically sound, argh... Why would it be 1 over 2piR?? And what could allow you to just multiply these expressions together??
 
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  • #2
You mention midpoints, but there's no reference to such in the construction.
(The pdf link crashed Firefox.)
 
  • #3
haruspex said:
You mention midpoints, but there's no reference to such in the construction.
(The pdf link crashed Firefox.)

sorry, I meant just points. Updated in first post..

Will post any alternate link to Jaynes' paper I can find, for now I have updated the OP to a new link from Google, which at least doesn't crash my Firefox..
http://books.google.com/books?id=3f...v=onepage&q=jaynes well posed problem&f=false page 139 has the same page I cited in OP, but the previous 2 pages are removed. Best I could find other than the original link in OP

In case I was unclear, it's pretty simple in theory. Every radius of the circle has a uniform distribution of points on it. ie if we let x=the distance along the radius from the center of the circle O, then we have the pdf:

f(x)=1/R when x is an element of [0,R], else =0

If we then consider infinitely many radii with distributions as such, according to ET Jaynes we see a distribution function over the entire circle of 1/2∏Rr
 
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  • #4
BUMP

I'm thinking I need to somehow integrate 1/R over the circumference of infinitesimal rings to get an equation:

normalized to equal 1 of course...
1=f(r)*(2pi*r)(R)

But how and why could I do this? What would allow me to integrate this way?

Thank you!
 
  • #5
I don't see why it's so hard. You want a pdf over the circle which is only a function of r, so f = f(r). The probability of picking a point in an area element dA = r dr dθ is f(r)dA. For a given θ, that means the probability of picking a radius in the range (r, r+dr) is f(r)rdr. Since you need that to be a uniform distribution, f(r) is proportional to 1/r.
 
  • #6
haruspex said:
I don't see why it's so hard. You want a pdf over the circle which is only a function of r, so f = f(r). The probability of picking a point in an area element dA = r dr dθ is f(r)dA. For a given θ, that means the probability of picking a radius in the range (r, r+dr) is f(r)rdr. Since you need that to be a uniform distribution, f(r) is proportional to 1/r.

yes that is understood... but how do we go from f(r)~1/r to f(r)~1/(2πRr) ??

if we set up an integral normalized to 1 with limits of integration are 0 to R and 0 to 2π, we would have
1 = ∫∫f(r) * r * dr *dθ ... add in a term of 1/r and we have
1 = ∫∫f(r) * 1/r * r * dr *dθ ...
1 = ∫∫f(r) dr *dθ ...
1 = f(r) * R * 2π
which gives f(r)=1/2πR ... missing a term of r (!)
how do we end up with a dependence on both 1/r AND 1/R ??
again, I need to arrive at this solution: [itex]f(r)=\frac{1}{2πRr}[/itex]

Thanks a million if you or anyone can help clear this up by tomorrow morning :)
 
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  • #7
SaintsTheMeta said:
1 = ∫∫f(r) * r * dr *dθ ... add in a term of 1/r and we have
1 = ∫∫f(r) * 1/r * r * dr *dθ ...
No, that's redefining f. You mean f(r) = k/r, 1 = ∫∫f(r) * r * dr *dθ = ∫∫k * dr *dθ = 2πRk. So k = 1/2πR, f(r) = 1/2πRr
 
  • #8
haruspex said:
No, that's redefining f. You mean f(r) = k/r, 1 = ∫∫f(r) * r * dr *dθ = ∫∫k * dr *dθ = 2πRk. So k = 1/2πR, f(r) = 1/2πRr

Wow thank you! I don't know why I got so confused by that... totally over-thought it..

Amazing how much my mathematics skills have left me in just 1.5 years of not using them...
 

1. What is the purpose of studying the radial distribution of points over the area of a circle?

The purpose of studying the radial distribution of points over the area of a circle is to understand the pattern and distribution of points within a circle. This can have practical applications in fields such as physics, mathematics, and statistics.

2. How is the radial distribution of points over the area of a circle calculated?

The radial distribution of points over the area of a circle is calculated by dividing the circle into smaller sections, determining the number of points within each section, and then plotting the number of points against the distance from the center of the circle. This creates a radial distribution curve, which can be used to analyze the distribution of points within the circle.

3. What factors can affect the radial distribution of points over the area of a circle?

There are several factors that can affect the radial distribution of points over the area of a circle, including the number of points, the size of the circle, and the distribution pattern of the points. Other factors such as the shape of the circle and the method of point generation can also have an impact on the radial distribution.

4. How is the radial distribution of points over the area of a circle useful in real-world applications?

The radial distribution of points over the area of a circle can be useful in a variety of real-world applications. For example, it can be used to analyze the distribution of stars within a galaxy, to understand the distribution of particles in a chemical compound, or to study the spread of a disease within a population.

5. Can the radial distribution of points over the area of a circle be applied to other shapes besides a circle?

Yes, the concept of radial distribution can be applied to other shapes besides a circle. For example, it can be used to study the distribution of points within a square or a triangle. However, the calculation method may differ depending on the shape, as well as the distribution pattern of the points within the shape.

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