Probability of randomly bouncing speedometer (stubborn calculus)

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SUMMARY

The discussion centers on calculating the probability density function and expected values for the x-coordinate of a broken car speedometer needle, which swings freely and bounces off pins at either end. The probability density function is established as ρ(x) = 1/(π√(r² - x²)), where r is the radius of the circular path. The average value is determined to be 0, while the expected value and standard deviation σ are derived using integrals and L'Hospital's Rule, leading to σ = r√(π/2) ≈ 1.2533r. The conversation highlights common pitfalls in integration and the importance of correctly applying mathematical principles.

PREREQUISITES
  • Understanding of uniform distribution in probability theory
  • Familiarity with polar to Cartesian coordinate transformations
  • Knowledge of calculus, specifically integration techniques and L'Hospital's Rule
  • Basic concepts of quantum mechanics, particularly expectation values
NEXT STEPS
  • Study the derivation of probability density functions in quantum mechanics
  • Learn about the application of L'Hospital's Rule in calculus
  • Explore the relationship between polar and Cartesian coordinates in mathematical modeling
  • Investigate the implications of complex numbers in probability and statistics
USEFUL FOR

This discussion is beneficial for physics students, mathematicians, and anyone interested in the application of calculus and probability theory in real-world scenarios, particularly in mechanics and quantum systems.

Yitzach
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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:\rho(x)=\frac{1}{b-a}
1. x=r\cos\theta
2. \frac{d}{du}\cos u=-\sin u du
3. \csc\arccos\frac{x}{r}=\frac{\left|r\right|}{\sqrt{r^2-x^2}}
4. \int\frac{dx}{\sqrt{a^2-x^2}}=\arcsin\frac{x}{r}
5. \left\langle x\right\rangle=\int^\infty_{-\infty}\bar{\psi}x\psi dx
6. \left\langle x^2\right\rangle=\int^\infty_{-\infty}\bar{\psi}x^2\psi dx
7. \sigma=\sqrt{\left\langle x^2\right\rangle-\left\langle x\right\rangle^2}
8. \int\frac{x^2dx}{a+bx^2}=\frac{x}{b}-\frac{a}{b}\int\frac{dx}{a+bx^2}
9. \int\frac{dx}{a+bx^2}=\frac{1}{2\sqrt{-ab}}\ln\frac{a+x\sqrt{-ab}}{a-x\sqrt{-ab}}
10. \int\frac{dx}{a+bx^2}=\frac{1}{\sqrt{-ab}}\tanh^{-1}\frac{x\sqrt{-ab}}{a}
11. \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}
12. \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)}}
13. \tanh^{-1}=.5\ln\frac{1+x}{1-x}
L'Hospital's Rule:\lim_{x\rightarrow x_0}\frac{f(x)}{g(x)}=\lim_{x\rightarrow x_0}\frac{f&#039;(x)}{g&#039;(x)}

The Attempt at a Solution


I started out with the uniform distribution and found \rho(\theta)=\frac{1}{\pi}.
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:
\arccos\frac{x}{r}=\theta
-\frac{1}{r}\csc\theta dx=d\theta
-\frac{1}{r}\csc\arccos\frac{x}{r} dx=d\theta.
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:
\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
I conclude the following from that exercise:
\rho(x)=\frac{1}{\pi\sqrt{r^2-x^2}}
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.
\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)}
The indefinite integral of that looks like or is related by algebra to this:
\int\frac{x^2dx}{r^2-x^2}=-\frac{a}{2}\ln\frac{x-r}{x+r}-x+C
I inevitably ran into one of two application of L'Hospital's Rule and limits in general:
\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.
The other look like it except it is -r, which results in:
\ln-1=\pi i
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:
\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\}
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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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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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.
\sigma=\sqrt{r^2\frac{\pi}{2}-0^2}=r\sqrt{\frac{\pi}{2}}\approx1.2533r
How can all of the distribution and then some be within one standard deviation of the expected value of x?
 
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/
 
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.
 

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