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Probability of measuring muons is a particular setup

  1. May 24, 2015 #1

    ChrisVer

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    1. The problem statement, all variables and given/known data

    You want to measure the momentum of muons with the help of a proportional chamber, that is a chamber
    that applies an electric field inside its cavity and produces a signal current when a charged particle passes
    through it. The probability of generation such a signal for a single chamber is 97%. For a momentum
    measurement you need to measure the position of a muon in at least three points inside the detector, i.e.
    three proportional chambers provide a signal. What is the minimum number of chambers required to provide
    a momentum measurement for at least 99% of muons that pass through your detector?

    2. Relevant equations


    3. The attempt at a solution

    The probability of a signal of a muon per chamber is: [itex] p = 0.97 \times \frac{1}{3} = 0.323[/itex].
    My problem however is that I don't know the number of the muons... Any feedback of what method I could use? I thought about using a Gaussian and integrating it from [itex]0.99N[/itex] to [itex]N[/itex] ([itex]N[/itex] is the total number of muons passing through and an unknown parameter).
     
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  3. May 24, 2015 #2

    mfb

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    It is not. It is 97 % as given in the problem statement.

    How would that matter? If you have a coin that shows head 50 % of the time, do you need the number of coin tosses to use that value of 50 %?

    You are overthinking this.

    What is the probability to detect a muon three times if you have three chambers (assuming muons pass through all of them)?
     
  4. May 24, 2015 #3

    ChrisVer

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    Oops sorry, I was wrong.

    If I have 3 chambers the probability is [itex]p= (0.97)^3[/itex] and also that's the probability of a single signal. Now if I have to do it three times.... I guess I can use the binomial [itex]B= \begin{pmatrix} n \\ k \end{pmatrix} p^n (1-p)^{n-k} [/itex] with [itex]n=3[/itex] but I don't understand what's the meaning of [itex]k[/itex] here.
    In the coin toss example, [itex]k[/itex] stands for the number of successes in [itex]n[/itex] trials.
     
    Last edited: May 24, 2015
  5. May 24, 2015 #4

    mfb

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    Let's call it "probability to get a momentum measurement" as signal is used for single chambers in the problem statement.
    Right. 0.97^3 < 0.99 so three chambers are not sufficient.

    What is the probability to detect a muon three or four times if you have four chambers (assuming muons pass through all of them)?
    The decimal number could be interesting here.
     
  6. May 24, 2015 #5

    ChrisVer

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    It's that probability times the probability to get the right number of 3 signals out of 4 chambers?
     
  7. May 24, 2015 #6

    mfb

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    No. You try 4 times, with 0.97 success probability each time. What is the probability to succeed 3 or 4 times?
     
  8. May 24, 2015 #7

    ChrisVer

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    [itex]0.97^3[/itex] or [itex]0.97^4[/itex]...

    My conceptual problem comes when I add more chambers though... Because with four chambers I have the possible outcomes:
    x : no signal ... o : signal in each chamber:

    x x x x - fail
    x x x o +3 permutations of o = fail
    x x o o + 4 permutations of o = fail
    x o o o + 3 permutations of x = success
    o o o o = sucess


    The appearence of each o is 97% probable... Looking at this scheme then the probability would be:
    [itex] p^4 + 4 p^3[/itex] ? (this doesn't look right)

    I think I'm trying to build up that:
    [itex] \begin{pmatrix} 4 \\ 4 \end{pmatrix} p^4 + \begin{pmatrix} 4 \\ 3 \end{pmatrix} p^3 [/itex]
    But I'm missing the [itex]q=1-p[/itex] probability in this.
     
    Last edited: May 24, 2015
  9. May 24, 2015 #8

    Ray Vickson

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    Right, because you copied down the ##B##-formula incorrectly. Go back and read your post #3 again, putting in ##n = 4## and ##k = 3## plus ##k = 4##.
     
  10. May 24, 2015 #9

    ChrisVer

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    My problem then is why didn't 1-p appear? Where did I lose it in the logic?
     
  11. May 24, 2015 #10

    mfb

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    You just forgot to add it? It was present in the original formula.
     
  12. May 24, 2015 #11

    ChrisVer

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    Yes it was...
    So for 4 chambers I obtain:
    [itex] 0.97^4 + 4 \times 0.97^4 \times (0.03) =0.991..[/itex]
    I think I got the idea of the problem: "need the k>=3 success in n trials probability to be > 99%"...
     
  13. May 24, 2015 #12

    Ray Vickson

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    As I said: go back and read your own post #3 again. Really do it, and carefully this time.
     
  14. May 24, 2015 #13

    ChrisVer

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    No it's OK... In each row I didn't count the probability (when it appeared) that the muon wouldn't interact, and that's why I was losing the (1-p) factors...:wink:

    Eg for this: o o - o , I would have p*p*(1-p)*p ...
     
  15. May 24, 2015 #14

    ChrisVer

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    Well the solution would be:

    [itex] 0.99 \le P = \sum_{k=3}^n \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} = 1 - \sum_{k=0}^2 \begin{pmatrix} n \\ k \end{pmatrix} p^k (1-p)^{n-k} [/itex]

    Where I would have to solve for ##x## (and ##p=0.97##):

    [itex] (1-p)^x + p (1-p)^{x-1} x +\frac{x(x-1)}{2} p^2 (1-p)^{x-2} \le 0.01[/itex]

    Wolfram solves this with [itex] x \in [0.00202302, 0.936647][/itex] (which actually doesn't make sense since the number of chambers must be an integer... and [itex]x\ge 3.77 ... [/itex] whose right next integer is 4 (verifying the result of 0.991... I got above)
     
  16. May 24, 2015 #15

    Ray Vickson

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    For your given ##p## the equation ##P_n \equiv (1-p)^n + p(1-p)^{n-1}\,n + \frac{1}{2} p^2 (1-p)^{n-1} \,n(n-1) = 0.01## has three solutions for ##n \geq 0##, namely, ##n \doteq 0.002023##, ##n \doteq.93616## and ##n \doteq 3.77439##. Wolfram has found the two smallest and has taken the interval between the two. Algebraically, that is correct, but probabilistically it is invalid. If there is a way in Wolfram to tell it to restrict n to ##n \geq 1## then it should find the other root, and all ##n## values greater than that root will satisfy the inequality (because of the shape of the graph of ##P_n## vs. ##n##.

    In Maple, the command 'fsolve(Pn = 0.01, n=1..10)' finds the largest root; here Pn is the formula above, with p = 0.97 and q = 0.03 in it.
     
    Last edited: May 24, 2015
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