Probability of randomly bouncing speedometer (stubborn calculus)

I still can't help but wonder what is happening at x=r. I guess I'll find out when I do the last part of the problem.In summary, the conversation discussed the problem of a broken car speedometer needle, which bounces perfectly off the pins at either end. It was determined that the probability density of the needle's position on the horizontal line is defined by a uniform distribution with a range of 0 to pi. The conversation then moved on to finding the expected value and standard deviation for this distribution, which involved converting from polar coordinates to Cartesian coordinates and using L'Hospital's Rule. The final answer for the standard deviation was found to be approximately 1.2533 times the radius of the circle.
  • #1
Yitzach
61
0
Welcome to Intro Quantum Mechanics:

Homework Statement


(From previous problem) The needle on a broken car speedometer is free to swing, and bounces perfectly off the pins at either end, so that of you give it a flick it is equally likely to come to rest at any angle between 0 and pi. (Next problem) We consider the same device as the previous problem, but this time we are interested in the x-coordinate of the needle point - that is, the "shadow," or "projection," of the needle on the horizontal line. (a.) What is the probability density rho of x? (b.) Compute <x>, <x^2>, and sigma (standard deviation) for this distribution.


Homework Equations


Uniform distribution:[tex]\rho(x)=\frac{1}{b-a}[/tex]
1. [tex]x=r\cos\theta[/tex]
2. [tex]\frac{d}{du}\cos u=-\sin u du[/tex]
3. [tex]\csc\arccos\frac{x}{r}=\frac{\left|r\right|}{\sqrt{r^2-x^2}}[/tex]
4. [tex]\int\frac{dx}{\sqrt{a^2-x^2}}=\arcsin\frac{x}{r}[/tex]
5. [tex]\left\langle x\right\rangle=\int^\infty_{-\infty}\bar{\psi}x\psi dx[/tex]
6. [tex]\left\langle x^2\right\rangle=\int^\infty_{-\infty}\bar{\psi}x^2\psi dx[/tex]
7. [tex]\sigma=\sqrt{\left\langle x^2\right\rangle-\left\langle x\right\rangle^2}[/tex]
8. [tex]\int\frac{x^2dx}{a+bx^2}=\frac{x}{b}-\frac{a}{b}\int\frac{dx}{a+bx^2}[/tex]
9. [tex]\int\frac{dx}{a+bx^2}=\frac{1}{2\sqrt{-ab}}\ln\frac{a+x\sqrt{-ab}}{a-x\sqrt{-ab}}[/tex]
10. [tex]\int\frac{dx}{a+bx^2}=\frac{1}{\sqrt{-ab}}\tanh^{-1}\frac{x\sqrt{-ab}}{a}[/tex]
11. [tex]\int\frac{x^2dx}{a+bx+cx^2}=\frac{x}{c}-\frac{b}{2c^2}\ln(a+bx+cx^2)+\frac{b^2-2ac}{2c^2}\int\frac{dx}{a+bx+c^2}[/tex]
12. [tex]\int\frac{dx}{a+bx+c^2}=\frac{1}{\sqrt{-(4ac-b^2)}}\ln\frac{2cx+b-\sqrt{-(4ac-b^2)}}{2cx+b+\sqrt{-(4ac-b^2)}}[/tex]
13. [tex]\tanh^{-1}=.5\ln\frac{1+x}{1-x}[/tex]
L'Hospital's Rule:[tex]\lim_{x\rightarrow x_0}\frac{f(x)}{g(x)}=\lim_{x\rightarrow x_0}\frac{f'(x)}{g'(x)}[/tex]

The Attempt at a Solution


I started out with the uniform distribution and found [tex]\rho(\theta)=\frac{1}{\pi}[/tex].
Then I found the conversions from polar r and theta to Cartesian x and for polar dtheta to Cartesian dx using 1 and 2 and manipulated them thus:
[tex]\arccos\frac{x}{r}=\theta[/tex]
[tex]-\frac{1}{r}\csc\theta dx=d\theta[/tex]
[tex]-\frac{1}{r}\csc\arccos\frac{x}{r} dx=d\theta[/tex].
I put that conversion in the integral of rho of theta dtheta for all space and checked the handy work with the help of 3, 4, and the fact that r is a positive real number thus:
[tex]\int^\pi_0\frac{1}{\pi}d\theta=\int^{-r}_r-\frac{1}{r}\csc\arccos\frac{x}{r} dx=\frac{1}{\pi}\int^r_{-r}\frac{dx}{\sqrt{r^2-x^2}}=1[/tex]
I conclude the following from that exercise:
[tex]\rho(x)=\frac{1}{\pi\sqrt{r^2-x^2}}[/tex]
I then go to find the expected/average value of x (<x>) and find it to be 0 meters from center. Makes sense as it is a symmetric distribution about x=0.
I then attempt to find <x^2> using 6, 8-13, and L'Hospital's Rule.
[tex]\int^\infty_{-\infty}\bar{\psi}x^2\psi dx=\int^r_{-r}\frac{1}{\pi\sqrt{r^2-x^2}}x^2\frac{1}{\pi\sqrt{r^2-x^2}}dx=\int^r_{-r}\frac{x^2dx}{\pi^2(r^2-x^2)}[/tex]
The indefinite integral of that looks like or is related by algebra to this:
[tex]\int\frac{x^2dx}{r^2-x^2}=-\frac{a}{2}\ln\frac{x-r}{x+r}-x+C[/tex]
I inevitably ran into one of two application of L'Hospital's Rule and limits in general:
[tex]\lim_{x\rightarrow r}r\ln\frac{x-r}{x+r}=r\ln\lim_{x\rightarrow r}\frac{x-r}{x+r}=r\ln\lim_{x\rightarrow r}\frac{1}{1}=0.[/tex]
The other look like it except it is -r, which results in:
[tex]\ln-1=\pi i[/tex]
I consistently came up with answers that made no sense. The difference between the first, third and fourth answers are if I used logarithm laws to simplify addition or not. And I think I had a few adding errors between the last two. The first answer was the most popular:
[tex]\left\langle x^2\right\rangle=\left\{-2\frac{r}{\pi},-2r\infty,-2\frac{r}{\pi}+\frac{r i}{2\pi},-2\frac{r}{\pi}+\frac{r i}{\pi}\right\}[/tex]
Negative and complex answers would result in complex or imaginary standard deviations which make no sense either. My calculator tells me that my answers should be real positive numbers. But it can't tell me that for certain. Weird stuff starts happening when you use limits of integration where the points are at infinity or not included in the normal function. I found two more entries for 13 in my math tables that I haven't tried yet, but I don't expect to get better results out of them.
 
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  • #2
Don't square the distribution!

Equation 6 is specific to 1-d quantum mechanics where dP = |ψ|^2 dx. Yet you're NOT dealing with a wavefunction. You have dP = ρ(x) dx = [π*sqrt(r^2-x^2)]^-1 dx. The expectation value is

<x^2> = ∫ x^2 dP, (all space)

Now take the integral. The integrand is even, so you have symmetry about the y-axis.

(Everything else looks good!)
 
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  • #3
That makes more sense, that is a mean trick to pull. And I'm know I'm not the only one who fell for it.
The resulting sigma make more sense, but not complete sense. Rho of x is defined between -r and r.
[tex]\sigma=\sqrt{r^2\frac{\pi}{2}-0^2}=r\sqrt{\frac{\pi}{2}}\approx1.2533r[/tex]
How can all of the distribution and then some be within one standard deviation of the expected value of x?
 
  • #4
Hmmm.. Wolfram Alpha shows me a little different answer.. Did you forget the 1/π?This was my calculation:
Integral[2*(π*sqrt(r^2-x^2))^(-1)*x^2,{x,0,r}]

http://www.wolframalpha.com/
 
  • #5
I did drop the pi^-1. GIGO. TI-89 Titanium only knows what I tell it. Nicely caught. And that sigma makes complete sense now that it is less than one whole r.
 

1. What is the probability of a speedometer bouncing randomly?

The probability of a speedometer bouncing randomly cannot be accurately determined without specific information about the speedometer's design and the conditions in which it is being used. It is possible to make assumptions and estimations, but without precise data, the probability cannot be determined.

2. How does calculus relate to the probability of a randomly bouncing speedometer?

Calculus is a branch of mathematics that deals with the measurement of change and is often used in physics and engineering to analyze and predict the behavior of systems, including speedometers. Calculus can be used to model the motion of the speedometer's needle and determine the probability of it bouncing randomly.

3. Are there any factors that can affect the probability of a speedometer bouncing randomly?

Yes, there are several factors that can affect the probability of a speedometer bouncing randomly, including the design and quality of the speedometer, the condition of the road or surface it is being used on, and the speed at which the vehicle is traveling. Other environmental factors such as temperature and humidity may also play a role.

4. Can the probability of a randomly bouncing speedometer be reduced?

It is possible to reduce the probability of a speedometer bouncing randomly by using a high-quality speedometer with a well-designed suspension system and ensuring proper maintenance and calibration. Additionally, driving on smooth roads and avoiding sudden acceleration or deceleration can help reduce the chances of the speedometer bouncing.

5. Is there a way to calculate the exact probability of a randomly bouncing speedometer?

As mentioned earlier, the exact probability of a randomly bouncing speedometer cannot be calculated without precise data. However, using mathematical models and statistical analysis, it is possible to make estimations and determine a range of probabilities for a specific speedometer under certain conditions.

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