Distribution of particles, given a function

In summary, the problem being discussed is the distribution of particles over a radial distance from an emitting point on a flat world with a gravitational field. The function r(ϕ) represents the distance a particle can move away from the emitting point in a random direction ϕ. The question is how to get a mathematical formulation for the density of the radial function f(ϕ) in order to calculate the likelihood of a particle reaching a certain distance. The solution involves using a histogram to graphically represent the distribution and using the derivative of the inverse function to calculate the density. This example highlights the difference between mathematics and physics, as the mathematical solution may not be precise enough for the physical phenomenon being studied.
  • #1
Omega0
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TL;DR Summary
distribution gravitation chemical reaction statistic histogram particel
I am not that super expert of statistics, so feel free to shift my formulation of the problem into the right one.First, for a physicist, the basic formulation of the problem. Let us say that you have a gravitational field and you have a fully symmetric problem on a flat world without other forces. Now let us have an emitter of particles (like an explosion) on the surface. We have a perfect symmetry, so it is okay to just take 0≤ϕ≤π2 into account, where ##\phi## is the angle from the surface of the planet to the normal.Now we take arbitrary functions into account which represent the distance which a particle can move away from the emmitting point. Probably the easiest example is if you throw away objects for perfectly random angles ϕ with a constant absolute speed v where you get the normalized solution (distance from emitting point):$$r\left( \phi \right) = \sin(2\phi)$$

Naturally, it could be something more complex like, just to stress my problem:

$$r\left( \phi \right) = \sin \left( \frac{2 \phi}{1 + 0.1 \sin(\phi)} \right)$$

but let us go for the simple problem first.My question is the following. I am happy to have the function r(ϕ) but what I really want to have is the distribution of particles over r, in the perfect case as a function. I mean I want to be able to do an integral from r1 to r2 to tell how likely it is that a particle goes there.Just for visualization please check this example:
distri1.png


The obvious solution for this problem (correct me, if I am wrong!) is a histogram. It clearly tells me - given by numerics - the distribution over the range. Here we have the simple case sin⁡(2ϕ) where I plottet a line instead of bars. Please note that the integral here would not be perfectly correct:

distribution.png
Just as a note apart: This tells me why a crater looks like a crater, doesn't it? But this is not my question.My question is: How do I get a mathematical formulation for the density of the radial function f(ϕ)?Thanks!

PS: I have to show you another plot, so cool, with a jump. Just to demonstrate that this is not easy to see from the original function (or is it?). I used $$r\left( \phi \right) = \sin \left( \frac{2 \phi}{1 + 0.1 \sin(\phi)} \right)$$

distribution2.png
 
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  • #2
Though I am not sure I understand what you stated, please find below what I thought.

img20210627_15533631.jpg


It is the case for ##\phi(r_1) < \phi(r_2) < \frac`{\pi}{4}##. For other cases the integral area is a little more complicated. The case you say random angle is ##p(\phi)=\frac{2}{\pi}##.
 
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  • #3
To give myself a correct reply... Here again a picture which tells everything I needed:
distri.png

The blue line is the inverse "function". It is from 0 to ##\pi /4## the function but then we can take into account that it is mirrored. This means the density of particels meating the ground can simply be multiplied by 2. What we can see is that the density depends from the derivative of the inverse function ##\arcsin##, so after normalization the solution is easily:

$$\rho(r) = \frac{2}{\pi}\frac{1}{\sqrt{1-r^2}}$$

I like to play around with numerics and graphics so here I just wanted to see the comparison with the linearly smoothed histogram where 2000 points have been used:

histogr_0701_1.png

I like this little problem. I think it shows two things. The first thing is that the closed solution depends completely from the existence of the inverse function. Here we could trick around, I could mirror but this is almost always impossible. No problem, we have the histogram! It always works - altogether with other statistical tools.
The second thing I like about this example is that it shows the difference between mathematics and physics, in my eyes. For me as a physicist this picture looks a little bit like a crater after an impact but not too precise. We have so many things to take into account, for example that all the particles around ##r=1## feel gravitation and have volume, now let us assume that those particles are balls with friction etc., now we may have a way better model for the crater.
Please don't get me wrong, I am not that expert in this field of physics. I just love physics and if I am wrong in anything, just let me know!

PS: I think I will have fun the next days to calculate some crater models :smile:
 
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1. What is the distribution of particles?

The distribution of particles refers to the arrangement or spread of particles in a given system or space. It can be described in terms of their positions, velocities, or energies.

2. How is the distribution of particles determined?

The distribution of particles is determined by a mathematical function that describes the probability of finding a particle at a given position, velocity, or energy. This function is known as the probability distribution function.

3. What factors affect the distribution of particles?

The distribution of particles can be affected by various factors, such as temperature, pressure, and external forces. These factors can alter the energy levels and interactions between particles, resulting in changes in their distribution.

4. Can the distribution of particles change over time?

Yes, the distribution of particles can change over time due to various factors, such as diffusion, chemical reactions, and phase transitions. These processes can cause particles to move and interact with each other, leading to changes in their distribution.

5. How is the distribution of particles used in scientific research?

The distribution of particles is a fundamental concept in many fields of science, including physics, chemistry, and biology. It is used to understand and predict the behavior of particles in different systems, such as gases, liquids, and solids. It is also used in statistical mechanics to study the properties of large systems of particles.

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